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PPRREEVVAALLEENNCCEE,, CCLLIINNIICCAALL CCHHAARRAACCTTEERRIISSTTIICCSS
AANNDD GGEENNEETTIICC MMAARRKKEERRSS OOFF IINNCCIIPPIIEENNTT
DDIIAABBEETTIICC NNEEPPHHRROOPPAATTHHYY IINN CCHHIILLDDRREENN AANNDD
AADDOOLLEESSCCEENNTTSS WWIITTHH TTYYPPEE 11 DDIIAABBEETTEESS IINN
WWEESSTTEERRNN AAUUSSTTRRAALLIIAA
Patricia Herold Gallego
MD, MSc Paediatrics
Fellow of the Royal Australasian College of Physicians
2010
This thesis is submitted for the degree of Doctor of Philosophy at The
University of Western Australia
School of Paediatics and Child Health
ii
DDEEDDIICCAATTIIOONN
This thesis is dedicated to my parents,
MANOEL GUILHERME MEUL GALLEGO
AND
DULCI HEROLD GALLEGO
For their endless love, support and encouragement
iii
EETTHHIICCSS CCLLEEAARRAANNCCEE
All studies in this thesis were approved by the Ethics Committee at Princess
Margaret Hospital for Children, Subiaco, Western Australia. All subjects, and
their parents, gave written, informed consent for their results to be analysed.
iv
SSTTAATTEEMMEENNTT OOFF CCOONNTTRRIIBBUUTTIIOONN
The work presented in this thesis was performed primarily by Dr Patricia H
Gallego (the candidate) at the Department of Endocrinology and Diabetes at
Princess Margaret Hospital for Children, The University of Western Australia,
Perth, Australia. The candidate planned the design of all studies with Dr Tim
Jones (the candidate’s supervisor). The candidate undertook the planning,
the elaboration of ethics protocol, the structuring of the data, the data
collection and checking, the statistical analysis, the literature review, the
interpretation of results, discussions and conclusions included in this thesis
which comprises about 80-90% of the work. In the first paper (chapter 3), Dr
Fiona Frazer, Dr Antony Lafferty and Dr Elizabeth Davis were co-authors
and provided feedback for drafts of manuscripts. Dr Max Bulsara provided
statistical advice for all manuscripts. In the second paper (chapter 4), Andrea
Gilbey and Mary Grat collaborated in the recruitment of participants. Due to
the nature of the research of chaper 5, the manuscript had collaborators
from the research team at Princess Margaret Hospital, Western Australia
Instiitute for Medical Research and University of Western Australia, including
Neil Shepard, Frank von Bockxmeer, Brenda Powell, John Beilby, Gillian
Arscott, Michael Le Page, Lyle Palmer, Elizabeth Davis and Catherine
Choong, who are liested as co-authors. Permission was sought and granted
by all collaborators to include the publications in the thesis.
Dr Patricia H Gallego
(Candidate)
Dr Tim Jones
(Supervisor)
v
AABBSSTTRRAACCTT
Diabetic nephropathy (DN) is an important cause of morbidity and mortality
among subjects with type 1 diabetes mellitus (T1DM). Early elevation of
albumin excretion rate (AER) and the presence of microalbuminuria (MA)
are early signs of DN and predictors for the progression of diabetic
nephropathy and the development of cardiovascular disease.
The overall aim of this work was to define potential clinical and genetic
markers for the appearance of persistent MA among children and
adolescents with T1DM. The main hypothesis was that both environmental
and genetic factors are contributors to the appearance of DN and that these
factors can be identified at very early stages of T1DM in childhood.
MA in children and adolescents with T1DM was examined in four different
settings:
1) In the first study (Chapter 3), the natural history of incipient nephropathy
was assessed in a population-based sample of 955 children and
adolescents aged less than 16 years at diabetes onset who were followed
longitudinally until the development of MA. The prevalence and the clinical
factors that predicted the development of MA were studied. MA was
prevalent in 13.4%. The major clinical contributors were glycaemic control as
reflected by mean HbA1c; age at diagnosis of T1DM and the presence of
puberty. HbA1c increased the risk for MA by 21% after adjusting for other
covariates. Age at diagnosis increased the risk by 25% whereas puberty
increased by 8-fold the risk for persistent MA. Furthermore, the contribution
of diabetes duration for the appearance of persistent MA was not uniform
over time with subjects diagnosed under the age of 5 years presenting a
vi
prolonged survival time without MA in comparison with those diagnosed
between 5-11 and > 11 years.
2) In the second study (Chapter 4), the relationship between AER and 24-
hour blood pressure (BP) measurements was determined in a sub-group of
75 T1DM children with normal AER. By studying 24-hour BP, early changes
in both systolic and diastolic BP occurred concomitantly with a rise in AER
even prior to the development of MA.
3) The third study (Chapter 5) examined the relationship between changes
of AER over a decade in a cohort of 620 children and adolescents. A decline
in the prevalence of MA was noticed over time in parallel to improvements in
diabetes control.
4) The study number four (Chapter 6) investigated the genetic risk of
polymorphisms at the renin-angiotensin system (RAS) in relation to the
appearance of persistent MA. In this study, the angiotensinogen (AGT) and
angiotensin 1-converting enzyme (ACE) genes conferred a higher risk for
persistent MA. Young subjects homozygous for the T allele at the AGT
T235M gene presented a 4-fold increased risk for MA and the survival time
without persistent MA was shorter for those subjects homozygous for the
deletion (D) allele at the ACE insertion/deletion (ACE I/D) gene.
The results of this work highlight the effects of both environmental and
genetic variables identifiable at early stages of T1DM as main contributors to
the development of persistent MA. The contribution of pre and post pubertal
duration of diabetes to the development of persistent MA was non-uniform.
By identifying these predictors for incipient DN, prevention strategies can be
targeted to high-risk adolescents with T1DM earlier in the course of the
disease.
vii
AACCKKNNOOWWLLEEDDGGEEMMEENNTTSS
I am extremely grateful to my supervisors Dr Timothy W Jones who has
always supported me and has provided me with encouragement and
strength for this work, and Dr Catherine C Choong who, as well, has guided
me and provided me with support over the last few years.
I have very much appreciated the endless assistance and support from my
colleagues from the department of Endocrinology at the Mater Children’s
Hospital, Dr Andrew Cotterill, Dr Mark Harris and Dr Gary Leong.
I would also like to thank Max Bulsara who has given me not only his
friendship but also the most valuable statistical advice through all this work.
Max has tirelessly helped me with data management and statistical analysis.
I have very much appreciated the assistance, support and friendship I have
had from the co-authors of the published manuscripts Fiona Frazer, Anthony
Lafferty, Elisabeth Davis, Andrea Gilbey, Mary Grant, Geoff Byrne, Neil
Shephard, Frank van Bockxmeer, Brenda Powell, John Beilby and Lyle
Palmer.
I would also like to thank the research assistants that helped performing the
DNA extraction and genetic polymorphisms, Michael Le Page and Gillian
Arscott.
I am also particularly grateful to all past and present staff of the Department
of Endocrinology and Diabetes at Princess Margaret Hospital for Children;
Jacqueline Curran, Sarah McMahon, Aveni Haynes, Niru Paramalingam,
Aris Siafarikas, Vanessa Baker, Alisha Thompson, Leanne Youngs, Glynis
viii
Price, Stefan Riedl for their friendship and support. These people have
taught me new skills and have generously given me their advice and
friendship when I needed the most, which I have greatly valued.
I am extremely grateful to the children and families who have participated in
the studies described in this thesis, without which none of this research
could have been conducted. To them, I extend my heartfelt thanks.
Finally, I wish to thank to my parents, brother, sister-in-law and lovely
nephews who living geographically so far away have supported me at each
step of this remarkable experience. They gave me the light and the strength
I needed to overcome all the obstacles and to arrive at the end of this
journey.
ix
CCOONNTTEENNTTSS
DEDICATION --------------------------------------------------------------------------------ii
ETHICS CLEARANCE--------------------------------------------------------------------iii
STATEMENT OF CONTRIBUTION---------------------------------------------------iv
ABSTRACT-----------------------------------------------------------------------------------v
ACKNOWLEDGEMENTS---------------------------------------------------------------vii
CONTENTS----------------------------------------------------------------------------------ix
LIST OF TABLES------------------------------------------------------------------------xvi
LIST OF FIGURES----------------------------------------------------------------------xvii
ABBREVIATIONS------------------------------------------------------------------------xix
DEFINITIONS------------------------------------------------------------------------------xxi
CHAPTER 1: INTRODUCTION---------------------------------------------------------2
1.1 Outline of thesis--------------------------------------------------------------- 3
1.2 Research aims-----------------------------------------------------------------4
1.3 Hypotheses---------------------------------------------------------------------4
1.4 Publications arising from this thesis--------------------------------------5
CHAPTER 2: BACKGROUND----------------------------------------------------------7
TYPE 1 DIABETES MELLITUS---------------------------------------------------------7
2.1 Definition and Classification of Diabetes in Childhood------------7
2.2 Global and Australian Incidence of Type 1 Diabetes----------------7
COMPLICATIONS OF TYPE 1 DIABETES----------------------------------------10
2.3 Overview of Complications in T1DM------------------------------------10
2.4 Long-term complications in T1DM---------------------------------------10
x
DIABETIC NEPHROPATHY-----------------------------------------------------------15
2.5 Defining Diabetic Nephropathy (DN)------------------------------------15
2.5.1 Microalbuminuia (MA)-------------------------------------------15
2.5.2 Borderline Albuminuria------------------------------------------16
2.5.3 Macroalbuminuria------------------------------------------------16
2.6 Classification or Stages of DN--------------------------------------------16
2.6.1 Stage I - Early Hypertrophy-hyperfunction-----------------16
2.6.2 Stage II - Glomerular Lesions without Clinical Disease----
-------------------------------------------------------------------------------17
2.6.3 Stage III - Incipient DN-----------------------------------------17
2.6.4 Stage IV - Overt DN---------------------------------------------18
2.6.5 Stage V - End Stage Renal Disease (ESDR)-------------18
2.7 Pathogenesis of Diabetic Nephropathy--------------------------------19
2.7.1 HYPERGLYCAEMIA AND DN-------------------------------19
2.7.1.1Formation of Advanced Glycation End-products
(AGEs): The Glycation Hypothesis-------------------------20
2.7.1.2 Activation of Aldose Reductase (Polyol)
Pathway-----------------------------------------------------------21
2.7.1.3 Activation of Protein Kinase C (PKC) Theory-----
----------------------------------------------------------------------22
2.7.1.4 Other mechanisms-----------------------------------24
a) Oxidative stress-induced vascular pathology--------24
b) Changes in expression and action of growth factors--
----------------------------------------------------------------------24
2.7.2 HEAMODYNAMIC CHANGES AND DN------------------24
2.7.2.1 The Role of Systemic Hypertension-------------24
2.7.2.2 The Role of Glomerular Capillary Hypertension
and Glomerular Hyperfiltration in DN----------------------26
xi
2.7.2.3 Treatment of Glomerular Hyperfiltration--------28
2.8 Genetics of Diabetic Nephropathy---------------------------------------29
2.8.1 Genes of the Renin-Angiotensin System (RAS)---------30
2.8.1.1 The angiotensin I-converting enzyme (ACE)
gene and DN-----------------------------------------------------31
2.8.1.2 The angiotensinogen (AGT) gene and DN-----32
2.8.1.3 The angiotensin II receptor type 1 (AGTR1)
gene and DN-----------------------------------------------------33
2.8.2 Other candidate genes------------------------------------------34
2.9 DN in Children with T1DM------------------------------------------------37
2.9.1 Risk factors for DN and microvascular complications in children
with T1DM -------------------------------------------------------------------------37
Glycaemic control-------------------------------------------------------37
Duration of diabetes and the effect of puberty-------------------42
Blood pressure ----------------------------------------------------------44
Lipids------------------------------------------------------------------------46
Smoking--------------------------------------------------------------------46
Family history of vascular complications---------------------------46
Obesity---------------------------------------------------------------------46
2.10 Screening guidelines for diabetes complications in T1DM
children------------------------------------------------------------------------------47
CHAPTER 3: STUDY I: “Prevalence and risk factors for
microalbuminuria in a population-based sample of children and
adolescents with T1DM in Western Australia”---------------------------------49
3.1 PREFACE------------------------------------------------------------------------------49
3.2 Abstract---------------------------------------------------------------------------------50
3.3 Introduction-----------------------------------------------------------------------------51
xii
3.4 Methods---------------------------------------------------------------------------------52
3.4.1 Definition of micro albuminuria-----------------------------------------52
3.4.2 Laboratory evaluation----------------------------------------------------53
3.4.3 Statistical analysis--------------------------------------------------------54
3.5 Results----------------------------------------------------------------------------------55
3.5.1 Clinical characteristics---------------------------------------------------55
3.5.2 Microalbuminuria, metabolic control, age at diagnosis, gender,
duration of diabetes and puberty---------------------------------------------55
3.5.3 Contribution of the different risk factors for developing MA----60
3.6 Discussion------------------------------------------------------------------------------61
3.7 Acknowledgements------------------------------------------------------------------64
CHAPTER 4: STUDY II: “Early changes in 24-hour ambulatory blood
pressure are associated with high normal albumin excretion rate in
children with type 1 diabetes”-------------------------------------------------------66
4.1 PREFACE------------------------------------------------------------------------------66
4.2 Abstract---------------------------------------------------------------------------------67
4.3 Introduction-----------------------------------------------------------------------------68
4.4 Research design and methods----------------------------------------------------69
4.4.1 Urinary AER assay--------------------------------------------------------69
4.4.2 Mean HbA1c levels-------------------------------------------------------69
4.4.3 Assessment of BP--------------------------------------------------------70
4.4.4 Statistical analysis--------------------------------------------------------70
4.5 Results----------------------------------------------------------------------------------72
4.5.1 Characteristics of the patients at the time of enrolment---------72
4.5.2 Subgroup analysis according to AER--------------------------------72
xiii
4.5.3 Subgroup analysis according to glycosilated hemoglobin
level----------------------------------------------------------------------------------76
4.5.4 Subgroup analysis on dippers and non-dippers-------------------76
4.6 Discussion------------------------------------------------------------------------------77
CHAPTER 5: STUDY III: “Declining Trends of albumin excretion rate in
Children and Adolescents with Type 1 Diabetes Mellitus”----------------80
5.1 PREFACE------------------------------------------------------------------------------80
5.2 Abstract---------------------------------------------------------------------------------81
5.3 Introduction-----------------------------------------------------------------------------82
5.4 Patient and methods-----------------------------------------------------------------83
5.4.1 Study design and patients----------------------------------------------83
5.4.2 Laboratory tests-----------------------------------------------------------84
AER-------------------------------------------------------------------------84
HbA1c----------------------------------------------------------------------85
Total cholesterol---------------------------------------------------------85
Anthropometric data and blood pressure--------------------------85
5.4.3 Statistical analysis--------------------------------------------------------86
5.5 Results----------------------------------------------------------------------------------87
5.5.1 Patients’ characteristics-------------------------------------------------87
5.5.2 Albumin excretion rate and MA----------------------------------------89
5.5.3 Metabolic control, insulin management and hypoglycaemic
events--------------------------------------------------------------------------------90
5.5.4 Blood pressure, cholesterol levels and anthropometric data---91
5.5.5 Univariate and multiple logistic regression-------------------------91
5.6 Discussion------------------------------------------------------------------------------94
xiv
CHAPTER 6: STUDY IV: “Angiotensinogen gene T235 variant: a marker
for the development of microalbuminuria in children and adolescents
with type 1 diabetes mellitus”-------------------------------------------------------99
6.1 PREFACE------------------------------------------------------------------------------99
6.2 Abstract--------------------------------------------------------------------------------100
6.3 Introduction---------------------------------------------------------------------------101
6.4 Patients and methods--------------------------------------------------------------102
6.4.1 Design and procedures------------------------------------------------103
6.4.2 Laboratory tests----------------------------------------------------------103
6.4.3 Genotyping----------------------------------------------------------------104
6.4.4 Statistical analysis-------------------------------------------------------105
6.5 Results---------------------------------------------------------------------------------107
6.6 Discussion----------------------------------------------------------------------------112
6.7 Acknowledgment--------------------------------------------------------------------114
CHAPTER 7: GENERAL DISCUSSION-------------------------------------------116
7.1 Summary and Conclusions-------------------------------------------------------116
7.2 Limitations----------------------------------------------------------------------------119
7.3 Implications and Future Directions---------------------------------------------122
7.3.1 Intervention Directed to T1DM Children and Adolescents---123
7.3.1.1 Glycaemic control--------------------------------------------123
7.3.1.2 The use of antihypertensive treatment-----------------124
ACE Inhibitors (ACEI)----------------------------------------125
Angiotensin II receptor blocker (ARB)-------------------125
7.3.1.3 The use of lipid agents--------------------------------------126
7.3.2 Genetic Screening for DN---------------------------------------------126
xv
REFERENCES---------------------------------------------------------------------------128
Appendix A Information Sheets and Consent Forms-------------157
Appendix B Classification and characteristic features of T1DM
in children; screening guidelines for vascular
complications in the pediatric and adolescent T1DM
group------------------------------------------------------------163
Appendix C PDF published manuscripts related to this thesis----
---------------------------------------------------------------------166
Appendix D Other Diabetes Related PDF Publications----------190
xvi
LLIISSTT OOFF TTAABBLLEESS
Table 2.1 Candidate genes in which polymorphisms have
demonstrated association with T1DM diabetic nephropathy--
-----------------------------------------------------------------------------36
Table 2.2 Target indicators of glycaemic control in T1DM children and
adolescents-------------------------------------------------------------41
Table 3.1 Gender, HbA1c, incidence density and postpubertal
incidence density of MA for subjects aged < 5, 5-11 and > 11
years at diabetes onset----------------------------------------------56
Table 3.2 Proportional contribution of gender, puberty, age at diabetes
onset and HbA1c as risk factors for the development of MA
with duration of diabetes as the time variable (n= 949)------60
Table 4.1 Characteristics of children and adolescents with type 1
diabetes with low and high normal AER-------------------------73
Table 5.1 Characteristics of adolescents with T1DM in the three
study periods----------------------------------------------------------88
Table 5.2 Univariate logistic regression analysis for high AER---------91
Table 5.3 Univariate logistic regression analysis for microalbuminuria--
-----------------------------------------------------------------------------92
Table 5.4 Multiple logistic regression analysis for high AER------------92
Table 5.5 Multiple logistic regression analysis for micro albuminuria-----
-----------------------------------------------------------------------------93
Table 6.1 Clinical characteristics of participants----------------------------107
Table 6.2 ACE, AGT and AGTR1 genotypes of participants------------108
Table 6.3 Cox regression multivariate analysis on the risk of persistent
MA in T1DM children---------------------------------------------------111
xvii
LLIISSTT OOFF FFIIGGUURREESS
Figure 2.1 New cases of Type 1 Diabetes Mellitus in children 0-14 years
(per 100 000 population) in 2010--------------------------------------8
Figure 2.2 Incidence rate of T1DM per 100 000 population aged 0-14
years old in OECD countries. Data survey from late 1990s to
early 2000s------------------------------------------------------------------9
Figure 2.3 Decline in the cumulative proportion of severe (laser-treated)
retinopathy in a population of patients with T1DM
diagnosed before the age of 15 years according to the year of
onset of diabetes---------------------------------------------------------12
Figure 2.4 Three main pathways implicated in the link between
hyperglycaemia and diabetic microvascular complications---19
Figure 2.5 Activation of aldose reductase or polyol in diabetes------------22
Figure 2.6 Activation of diacylglycerol (DAG)-PKC pathway in the
pathogenesis of diabetic microvascular complications---------23
Figure 2.7 Mechanisms of extracellular matrix deposition in mesangial
cells caused by mechanical stretch in DN-------------------------28
Figure 2.8 The renin angiotensisn system (RAS) and the role of ACE---31
Figure 2.9 Potential genetic and environmental risk factors for the
development of long-term diabetes complications--------------37
Figure 2.10 Distribution of HbA1c concentration by randomized treatment
group at the end of the DCCT and in each year of EDIC study-
--------------------------------------------------------------------------------39
xviii
Figure 2.11 Prevalence and cumulative incidence of MA---------------------39
Figure 2.12 Cumulative percentage of borderline AER by age in T1DM
with diabetes duration of 6 years------------------------------------42
Figure 3.1 Cumulative probability (Kaplan-Meier survival curves, log-rank
test, P=0.03) for the development of microalbuminuria for boys
and girls during puberty (○ females, □ males)--------------------58
Figure 3.2 Cumulative probability (Kaplan-Meier survival curves, log-rank
test, P<0.001) for the development of microalbuminuria for
each year since diabetes onset in three groups divided by
age at diagnosis (+ < 5 years, □ 5 to 11 years and ○> 11
years)-----------------------------------------------------------------------59
Figure 4.1 Effect of increments of AER on systolic blood pressure
during daytime and nighttime-----------------------------------------75
Figure 4.2 Effect of increments of AER on diastolic
blood pressure during daytime and nighttime--------------------75
Figure 5.1 Percentage of subjects with high AER (1a) and
microalbuminuria (1b) over the three study periods------------89
Figure 5.2 Median AER by age, comparing P1+ P2 (1993-2000) versus
P3 (2001-2004)-----------------------------------------------------------90
Figure 6.1 Kaplan-Meier estimation for the development of persistent MA
according to ACE genotype in the recessive model (DD versus
ID/II)-----------------------------------------------------------------------109
Figure 6.2 Kaplan-Meier estimation for the development of persistent MA
according to AGT genotype in the recessive model (TT versus
MT/MM)-------------------------------------------------------------------110
xix
AABBBBRREEVVIIAATTIIOONNSS
ABP Ambulatory Blood Pressure
ACE Angiotensin 1-converting enzyme
ACEI Angiotensin 1-converting enzyme inhibitor
ACR Albumin Creatinine Ratio
AER Albumin excretion rate
AGE Advanced Glycation End Product
AGT Angiotensinogen
AGTR1 Angiotensin II receptor type 1
ARB Angiotensin II receptor blocker
BP Blood Pressure
CI 95% Confidence Intervals
CVD Cardiovascular Disease
DAN Diabetic Autonomic Neuropathy
DBP Diastolic Blood Pressure
DCCT Diabetes Control and Complications Trial
DKA Diabetes Ketoacidosis
DN Diabetic Nephropathy
DPN Diabetic Polineuropathy
DR Diabetic Retinopathy
ESRD End Stage Renal Disease
EDIC Epidemiology of Diabetes Interventions and
Complications
GFR Glomerular Filtration Rate
HbA1c Glycated Haemoglobin
xx
HR Hazard Ratio
I/D Insertion/Deletion
IQR Interquartile range
MA Microalbuminuria
ORPS Oxford Regional Prospective Study
PKC Protein Kinase C
RAS Renin-Angiotensin System
SBP Systolic Blood Pressure
T1DM Type 1 Diabetes Mellitus
T2DM Type 2 Diabetes Mellitus
UKPDS United Kingdom Prospective Diabetes Study
xxi
DDEEFFIINNIITTIIOONNSS
Microalbuminuria
Presence of albumin excretion rate greater or equal to
20µg/min but lower than 200 µg/min in two out of three
overnight timed urine collections unless otherwise
stated.
High normal AER or Borderline AER
Mean albumin excretion rate greater than 7 and lower
than 20 µg/min collected from three overnight timed
urine collections.
Low normal AER
Mean albumin excretion rate lower or equal to 7 µg/min
collected from three overnight timed urine collections.
CCHHAAPPTTEERR OONNEE
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CCHHAAPPTTEERR 11.. IINNTTRROODDUUCCTTIIOONN
This work contains a series of four related manuscripts dealing with the
development of MA or incipient DN (DN) in children and adolescents with
T1DM.
MA is an early sign and predictor of DN among people with T1DM. Although
improvements in diabetes management have occurred over the last
decades, DN is still the leading cause of end-stage renal disease (ESRD) in
US and Europe (1) and the second most common cause in Australia (2). DN
typically develops after 15 to 20 years of diabetes duration but the presence
of persistent MA, an early sign of DN, is a predictor of cardiovascular
disease and early mortality (3-7).
MA may be detected in adolescents who have T1DM but is rarely present in
pre-pubertal children who have diabetes. During adolescence, between 5%
and 25% of patients with T1DM have MA (8-13). Even though persistent MA
is predictive for overt nephropathy in adults with diabetes, its prognostic
value among children and adolescents with diabetes are less well defined.
The main objective of this study is to identify potential predictors for the
development of MA in children and adolescents with T1DM aiming to
minimize the development of diabetes microvascular complications,
particularly nephropathy, by early detection and possible intervention among
those considered at high risk.
Unfortunately, primary prevention and cure for T1DM is still not available.
Improvements in diabetes management with intensive insulin therapy for
optimizing glycaemic control is still the best available treatment for T1DM
and the most effective way of preventing long term vascular complications.
3
However, several studies demonstrate that despite dramatic improvements
in diabetes care and glycaemic control, some still develop microvascular
disease.
Hence, this study provides a unique opportunity not only to explore the
natural history of persistent MA in a large population-based sample of
children with T1DM followed prospectively from diagnosis but also to identify
clinical and genetic markers for the development of this complication. The
results of this study will allow the identification of those at risk and the
development of prevention strategies for DN.
1.1 Outline of thesis
The following chapter outlines the background of T1DM starting with an
overview of the global incidence and in Australia then moving to an overview
of complications associated with T1DM. This is followed by literature review
on DN, the focus of this research.
The next four chapters following background are structured as papers.
Three of these chapters were published in peer-reviewd journals.
Chapter 3 describes the prevalence and the natural history of MA in a
population-based sample of children and adolescents with T1DM. This
paper highlights potential clinical predictors for the development of MA in a
large cohort of children followed prospectively from diagnosis.
In Chapter 4, the effect of blood pressure on AER is examined more closely
in a sub-group of children and adolescents randomly selected from the
Children’s Diabetic clinic at Princess Margaret Hospital for Children.
In Chapter 5 (not published), the changes in the prevalence of AER and MA
between the years 1993 and 2004 were examined in a large cohort of young
people with T1DM. A decline occurred at times of improvement in diabetes
management and particularly in glycaemic control. In Chapter 6, the
relationship between genetic variants at the renin-angiotensin system,
4
mainly the angiotensin-converting enzyme, angiotensinogen and angiotensin
II receptor type 1 genes, were studied in a large cohort as candidate genes
implicated in the development of incipient DN.
1.2 Research aims
1) To examine the natural history and to identify clinical predictors for
the development of persistent MA in childhood onset diabetes;
2) To assess the relative risk of diabetes duration in relation to puberty
for the development of MA in children and adolescents with T1DM;
3) To examine the effect of blood pressure in relation to AER in a sub-
group of T1DM children and adolescents
4) To examine the changes of AER and persistent MA over time
5) To identify potential genetic markers that contribute to the
development of early DN early in the course of diabetes;
1.3 Hypotheses
1) That clinical and genetic risk factors for the development of incipient
nephropathy are recognizable in children and adolescents with T1DM
at early stages of the disease;
2) That the duration of diabetes before and after the onset of puberty
have a non-uniform effect towards the development of MA in children
diagnosed with T1DM;
3) That changes in BP precede the appearance of persistent MA;
5
4) That changes in the prevalence of MA over time will parallel the
modifications in diabetes management and improvements in
glycaemic control;
5) That specific polymorphisms at genes from the renin-angiotensin
system are contributors to the development of incipient nephropathy
in children and adolescents with T1DM
1.4 Publications arising from this thesis
1) Prevalence and risk factors for MA in a population-based sample of
children and adolescents with T1DM in Western Australia (chapter 3).
Gallego PH, Bulsara MK, Frazer F, Lafferty AR, Davis EA, Jones TW.
Pediatric Diabetes 2006:7:165-172.
2) Early changes in 24-hour ambulatory blood pressure (ABP) are
associated with high normal AER in children with T1DM (chapter 4).
Gallego PH, Gilbey AJ, Grant MT, Bulsara MK, Byrne GC, Jones TW,
Frazer FL. Journal of Pediatric Endocrinology and Metabolism 2005:
3) Angiotensinogen gene T235 variant: a marker for the development of MA
in children and adolescents with T1DM mellitus (chapter 6). Gallego PH,
Shepard N, Bulsara MK, van Bockxmeer FM, Powell BL,Beilby JP, Arscott
G, Le Page M, Palmer LJ, Davis EA, Jones TW, Choong CSY. Jurnal of
Diabetes Complications 2007:
6
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CCHHAAPPTTEERR 22.. BBAACCKKGGRROOUUNNDD
TYPE 1 DIABETES MELLITUS
2.1 Definition and Classification of Diabetes in Childhood
Diabetes Mellitus has a long history and it was first described in Egyptian
documents from 1552 BC. In the 1st century, Arateus described diabetes as
“the melting down of flesh and limbs into urine” but it was not until the 1940s
that the link between diabetes and long-term complications was stablished
(14).
Type 1 diabetes (T1DM) results from auto-immunity T–cell mediated
destruction of the insulin producing pancreatic beta cells causing insulin
deficiency and leading to chronic hyperglycaemia (15). T1DM is the most
prevalent form of diabetes among young people under the age of 10 years
and the most common chronic disease in childhood, affecting up to 1% of
the general population during their lifespan (16).
Although type 1 and type 2 diabetes can occur in childhood, they present
different disease patterns and require different management. In T1DM
children require daily insulin, which is a life-saving treatment while in T2DM,
depending on clinical parameters, children may not necessarily require
insulin and modifications in lifestyle as well as the use of oral hypoglycaemic
agents may be sufficient for clinical management.
The aetiological classification of disorders of glycaemia in childhood and
adolescence and the characteristic features of type 1 diabetes compared to
type 2 in childhood are shown in Appendix A.
2.2 Global and Australian Incidence of Type 1 Diabetes
T1DM is not restricted by geographical boundaries, nationality, age or
gender. It is been recognized in almost every country with no region being
exempt from the disease (Figure 2.1).
8
Figure 2.1 New cases of T1DM in children 0-14 years (per 100 000
population) in 2010
[Source: Diabetes Atlas, International Federation]
The mean annual incidence rates for T1DM in children 0-14 years of age is
summarized in Figure 2.2. Between the years 1990 and 1994, low incidence
rates of 0.1 per 100 000 per annum were observed in countries like China
while higher rates close to 56 per 100 000 per annum were reported in
Finland (17). In 2007, the International Diabetes Federation estimated that
among children aged 0-14 years, some 70 000 children worldwide are
expected to develop T1DM annually. Increasing incidence rates ranging
from 2-5% per annum have been reported, particularly in the under 4-yr-old
age group (18). These changes in incidence rates have been described in
countries with both high and low prevalences but with some indication of a
more rapid increase in low-prevalence countries.
From the late 1990s to early 2000s, the Australian Institute of Health and
Welfare reported the Australia’s incidence rate for T1DM as in the upper end
of range. A survey covering the period 2000-2006 estimated the age-
standardized incidence rate of T1DM to be 22.4 per 100 000 population
aged 0-14 years (19). This incidence places Australia in a similar category to
other countries such as the United Kingdom and Canada (Figure 2.2).
9
Figure 2.2 Incidence rate of T1DM per 100 000 population aged 0-14 years
old in OECD countries. Data survey from late 1990s to early 2000s.
[Source: Australian Institute of Health and Welfare, 2008]
Studies in the incidence of T1DM in childhood have reported that the trends
in Australia reflect what has been observed in other countries. In Sweden,
time trends analysis in the incidence T1DM from 1983 to 2007 in individuals
aged 0-34yrs revealed an increase by calendar year in both sexes under the
age of 15yrs (20). Similarly, a prospective study of twenty-one years in
Hungary reported that the overall incidence rate has doubled from 1989 to
2009, with the highest rate in the very young children (21).
Overall the annual incidence of type 1 diabetes has increased on average by
3.2% per year from 1990 to 1996 in New South Wales (22).
In Western Australia, the incidence increased on average by 3.1% a year
over the period between 1985 to 2002 (23).
In Victoria, the rate of increase of T1DM was much higher and reported as
close to 9% but it was measured over a shorter period of time in comparison
to the previous studies (24).
10
COMPLICATIONS OF TYPE 1 DIABETES
2.3 Overview of Complications in T1DM
In T1DM, insulin therapy is essential for maintaining plasma glucose levels
within a normal range. Insulin is delivered subcutaneously by intermittent
injections or by continuous delivery via an insulin pump. Although there have
been advances in methods of insulin delivery as well as an improvement in
the quality of available insulin, injecting exogenous insulin does not perfectly
replicate the normal biological variation in insulin secretion and the
development of short and long-term complications is commomly seen
among those who suffer the disease.
Short-term complications result from either acute severe insulin deficiency
causing diabetes ketoacidosis or are due to relative insulin excess causing
hypoglycaemia. A discussion of acute complications associated with the
management of children with T1DM is beyond the scope of this work.
The long-term complications of diabetes include macrovascular disease
(cerebrovascular disease, ischaemic heart disease and peripheral arterial
disease) and microvascular complications (nephropathy, retinopathy and
neuropathy).
2.4 Long-term complications in T1DM
In adults and adolescents, it has been established that poor glycemic control
is causally associated with long-term vascular sequelae of T1DM. These
complications include nephropathy, retinopathy, neuropathy and
cardiovascular disease.
Although clinically evident diabetes–related vascular complications are rare
in childhood and adolescence, early signs of functional and structural
abnormalities may be detected a few years after the onset of the disease.
For example, increased vascular stiffness is seen in children with type 1
diabetes compared with healthy controls (25).
11
In regards to macrovascular complications, T1DM is associated with a three
to fourfold increased mortality risk in all age-bands when compared to the
non-diabetic population (26). Cardiovascular disease (CVD) including
myocardial infarction, ischaemic heart disease and strokes accounts for half
of all deaths with similar mortality rates observed in men and women under
the age of 40 years (27). The incidence rates of CVD are substantially
higher in the T1DM population at 1-2% per year when compared with the
general population incidence rates of 0.1-0.5% per year (28, 29).
Despite improvements in diabetes care, the Pittsburgh Epidemiology of
Diabetes Complications (EDC) study, a prospective observational study of
childhood-onset diabetes, demonstrated a decreasing trend for
complications such as mortality, renal failure and neuropathy but no
changes in rates of coronary artery disease. Improvement in glycaemic
control was not associated with a decline in CVD over time. These data
suggest that focus on other risk factors for CVD such as blood pressure and
lipids are important in T1DM (29). Supporting these data, the EURODIAB
Prospective Complications Study showed that the strongest risk factors for
coronary heart disease were baseline albuminuria, blood pressure, fasting
tryglicerides and waist-to-hip circumference (30).
Persistent proteinuria is also a strong predictor for the development of CVD
(4, 29). Atherosclerosis has been documented to start in childhood with
increased thickness of intima-media of carotids and aorta; silent coronary
atherosclerosis has also been demonstrated in young adults with childhood-
onset diabetes (31). Cholesterol is an important factor for the initiation of
atherosclerosis. In diabetes, a more atherogenic profile is observed despite
well-controlled glycaemia (32) but poor glycaemic control is associated with
a more atherogenic profile (33).
Microvascular complications are a major cause of morbidity in young people
with T1DM. Diabetic retinopathy (DR) affects the majority of patients with
T1DM after 15 years duration (34). Although recent data indicates a
reduction in the incidence of severe retinopathy (Figure 2.3) (35), studies
suggest that 24% to 27% of children and adolescents with T1DM present
12
early background retinopathy after 6 to 13 years of diabetes duration (36,
37).
Onset of diabetes: 1961-1965 (▲), 1966-1977 (◄), 1971-1975 (○), 1976-1980 (◊), 1981-1985 (●).
Figure 2.3 Decline in the cumulative proportion of severe (laser-treated)
retinopathy in a population of patients with T1DM diagnosed before the age
of 15 years according to the year of onset of diabetes
[Source: The Linköping Diabetes Complications Study, Diabetologia, 2004]
Hyperglycaemia plays a major role in the development of DR by impairing
the mechanism of retinal perfusion auto regulation, which protects the eye
from systemic hypertension (38). Two major clinical trials, the DCCT and
the UKPDS, have demonstrated the beneficial effects of intensive glycaemic
control in reducing the onset and progression of DR in type 1 (39-41) and
type 2 diabetes (42).
The Wiscosin Epidemiology Study of Diabetic Retinopathy (WESDR)
reported the 14-year incidence and progression of DR in a large cohort of
“younger-onset” persons with diabetes (diagnosed before 30 years of age).
This group showed a very high 14-yr incidence of any retinopathy (96%) and
a 86% incidence of progression of retinopathy (43). In addition to
hyperglycaemia being the main trigger for DR, higher diastolic blood
pressure and male gender were risk factors for DR in this study.
13
In T1DM adolescents, long-term glycaemic control, both before and after
puberty, is the major risk factor for retinal changes. But other factors such as
age of onset of diabetes, puberty, lipids, blood pressure and genetic factors
will also have varying relevance at a individual level (44).
Diabetic neuropathy described the involvement of the peripheral and
autonomic nervous systems commonly seen in T1DM. The somatic
neuropathies associated with diabetes fall into two categories: focal
neuropathies and sensorimotor polyneuropathies.
One of the largest studies of diabetic neuropathy, the EURODIAB baseline
diabetic polyneuropathy (DPN) study, was conducted between 1989-1991
and involved 3250 subjects with T1DM from 16 countries (mean age of 33
years; mean duration of diabetes of 15 years). Diabetic neuropathy was
present in 19% of 15-29 yr olds; 28% of 30-44 yr olds and 57% of 45-61 yr
old subjects at baseline. Glycaemic control was the major correlate of
neuropathy, even after adjusting for duration of diabetes. A substantial
prevalence of DPN was also found in those whose control was very good
(A1C < 7%) (45).
The EURODIAB prospective study followed 1172 subjects for 7.3 years.
The cumulative incidence of neuropathy was 23.5% and risk factors included
glycaemic contro, diabetes duration, hypertension, smoking, BMI and
triglycerdides (45). The DCCT also shed light on the effect of glycaemic
control on the rates of neuropathy in young people with T1DM (41). The
EDIC study confirmed lower rates of diabetic neuropathy in the intensive
group with benefits extending for at least 8 years beyond the end of the
DCCT (46).
The prevalence of diabetic neuropathy in the paediatric population is less
clear probably due to the lack of large epidemiological studies in the
paediatric T1DM group. In epidemiological studies involving both adult and
paediatric patients, the prevalence of DPN varies, ranging from 7 to 57%
(47). This large difference is likely due to the lack of appropriate diagnostic
criteria. The most complete evaluation using electrophysiological testing
reported a prevalence of 57% of subclinical neuropathy in children and
adolescents with T1DM (48).
14
Hereafter the literature review on microvascular complications will refer to
the development of DN detailed in the following pages of this review.
15
DIABETIC NEPHROPATHY
2.5 Defining Diabetic Nephropathy (DN)
The earliest clinical evidence of DN is the appearance of low but abnormal
levels of albumin in the urine, known as micro albuminuria (MA). Patients
with MA are referred to as having incipient DN. All definitions of MA are
somewhat arbitrary.
2.5.1 Microalbuminuia (MA)
Definitions of MA include an AER of 20 to 200 μg per minute in urine
collected over 24 hours.; an AER of 15 to 150 μg/min in urine collected
overnight; or an AER of 30 to 300 mg/24hr in 24-h urine collections (49).
Classically, and by consensus of many investigators, MA has been defined
as an overnight urinary AER of 20-200 μg/min (50).
According to ISPAD guidelines, the accepted definitions for MA in childhood
onset diabetes are:
1) AER 20-200 μg/min in timed overnight urine collection; or AER 30-300
mg/24h in 24-h urine collections;
2) Albumin concentration of 30-300 mg/l (early morning urine sample);
3) Albumin/creatinine ratio (ACR) 2.5 – 25 mg/mmol or 30-300 mg/g (spot
urine) in males and 3.5 - 25 mg/mmol in females (because of their lower
creatinine excretion)
Irrespective of the definition used, MA needs to be confirmed by the finding
of two out of three abnormal samples collected over a 3-6 months period. In
addition to its being the earliest manifestation of DN, persistent MA is also a
marker of end-stage renal disease (ESRD) and of increased cardiovascular
morbidity and mortality in T1DM (4, 51, 52).
16
2.5.2 Borderline Albuminuria
Borderline albuminuria is considered an AER between the upper 95th
percentile of normal AER (levels reported between 7.2 to 7.6 μg/min) and
the lowest value predictive of nephropathy (20 μg/min) in at least one of
three consecutive timed collections (53, 54).
In childhood, early elevations of AER within the normal range, or borderline
AER, also identify patients at risk of progression to renal damage and is
associated with changes in glomerular filtration rates (54, 55).
2.5.3 Macroalbuminuria
Macroalbuminuria, clinical albuminuria or overt nephropathy is defined as
AER above or equal to 200 μg/min or 300 mg/24h.
Overt nephropathy is associated with a gradual reduction in the glomerular
filtration rates, which is variable from individual to individual in the course of
several years. End stage renal disease (ESRD) is characterized by uraemia
and by glomerular filtration rates less than 15mL/min per 1.73 m2 or when
treatment by dyalisis is required (56). End stage renal disease (ESRD)
develops in about 50% of T1DM individuals with overt nephropathy within 10
years (57).
2.6 Classification or Stages of DN
Alterations in renal function in T1DM follow a very characteristic pattern and
five different stages have been described in the course of development of
DN (56).
2.6.1 Stage I - Early Hypertrophy-hyperfunction
This stage, characterized by early hyperfunction and hypertrophy, is present
at diagnosis of T1DM even before the start of insulin treatment. The main
structural changes are increased kidney volume, increased glomerular size,
nephron hypertrophy and hyperplasia (56). Insulin treatment leads to
reduction in both renal size and glomerular filtration rate (GFR) suggesting
17
that these changes are due to metabolic effects and partly reversible by
insulin treatment (58).
Both increased kidney volume and faster GFR during the first years of
diagnosis are associated with poor renal prognosis (59-62). Two hypotheses
have been proposed to explain these early renal dysfunctions induced by
diabetes. The “vascular hypothesis” claims that hyperfiltration is the primary
event due to abnormalities in vascular control, including increments in
plasma flow and intra-glomerular pressure. Hypertrophy would follow, after
compensatory tubular changes, aiming to prevent loss of water and
electrolytes (63-65). The “tubular hypothesis” suggests that the primary
event is renal hypertrophy, which is a consequence of hyperglycaemia and
hyperglycaemia-induced overproduction of growth factors and cytokines (66-
68).
2.6.2 Stage II - Glomerular Lesions without Clinical Disease
The second stage develops silently over many years. It is characterized by
histological changes without signs of clinical disease. However, renal
function tests and kidney biopsy reveal some changes. There is evidence of
increased glomerular and tubular basement membrane thickness and
mesangium expansion. Hyperperfusion may be the initiating event with
increased GFR and increased mesangial matrix production in a focal or
diffuse distribution (69). Characteristically, GFR is increased by 20 to 30%,
AER and blood pressure are normal at rest but physical exercise unmasks
changes in albuminuria (56).
2.6.3 Stage III - Incipient DN
The earliest clinical evidence of DN is the appearance of low but abnormal
levels of albumin in the urine (≤ 30 mg/day or 20 μg/min), or MA. A slow, but
gradual increase of albuminuria over the years is a prominent characteristic
of this phase of renal disease when blood pressure is rising. MA and
diabetic renal disease are closely linked (10, 49, 59, 70-75). The presence of
18
MA usually indicates the beginning of DN but it is also often found in
essential hypertension as first described by Parving et al (76).
Persistent MA is involved in early renal and vascular disorders and predicts
the development of overt DN and increased cardiovascular mortality (77).
MA is considered an early sign of damage of the kidney and the
cardiovascular system (75, 78-80).
Diabetic nephropathy prevention strategies may involve the use of early
angiotensin-converting enzyme (ACE) inhibitor treatment and the control of
diabetes to reduce glomerular hypertension and hyperfiltration. It is a
general clinical practice to screen subjects with T1DM for MA. In adults with
diabetes andMA, studies suggest that early blockade of the renin-
angiotensin system prevent the progression to renal disease and the
progression of other microvascular complications (81-84). In the adolescent
T1DM population a large randomized controlled clinical trial is currently
being developed to address the benefits of early intervention witn
angiotensin converting enzyme inhibitors (ACEI) and statins in prevention of
diabetic nephropathy (85).
2.6.4 Stage IV - Overt DN
Without specific interventions, approximately 80% of T1DM subjects who
develop persistent MA have their albumin excretion increase at a rate of 10
to 20% per year to the stage of overt nephropathy or clinical albuminuria (≥
300mg/ day or ≥ 200μg/min) over a period of 10-15 years (1). In this stage,
diffuse and focal glomerulosclerosis develop. Once overt nephropathy
occurs, and without specific interventions, GFR gradually declines over a
period of several years at a rate that is highly variable from individual to
individual (2-20 ml/min/year) and hypertension develops along the way (56).
2.6.5 Stage V - End Stage Renal Disease (ESRD)
The fifth stage is the end stage renal failure with uraemia characterized by
glomerular closure and GFR less than 10ml/min (56). ESRD develops in
50% of T1DM subjects with overt nephropathy within 10 years and in more
19
than 75% by 20 years (1). Subjects with nephropathy had a much poorer
survival than those without proteinuria. Forty years after onset of diabetes,
only 10% of patients who developed nephropathy were alive, whereas
greater than 70% of patients who did not develop nephropathy survived (3).
2.7 Pathogenesis of Diabetic Nephropathy
2.7.1 HYPERGLYCAEMIA AND DN
The true mechanism by which lack of glycaemic control predisposes to
vacular damage is not fully understood. Among the proposed mechanisms
linking hyperglycaemia and vascular disease, two contributing factors are
the advanced glycation end-products (AGEs) and the acceleration of the
aldose reductase or polyol pathway. Other mechanisms may also be
important including the activation of protein kinase C (PKC), enhanced
oxidative stress, altered expression and action of growth factors and
vasoactive mediators in the glomerular tissues (86).
Three of these pathways (Figure 2.4) are further described in the following
sessions:
Figure 2.4 Three main pathways implicated in the link between
hyperglycaemia and diabetic microvascular complications
[Source: The Journal of the American Osteopathic Association, Vol 100, No 10, October
2000]
20
2.7.1.1 Formation of Advanced Glycation End-products (AGEs): The
Glycation Hypothesis Chronic hyperglycaemia and oxidative stress in
diabetes result in the formation and accumulation of advanced glycation
end-products (AGEs). In intracellular hyperglycaemia, these products are
formed primarily through non-enzymatic reactions between protein and
glucose, a process named glycation or non-enzymatic glycation (87).
In diabetes, AGEs accumulates in sites of microvascular injury, including the
kidney, the retina and within vasculature (88). Studies in diabetic populations
have shown that serum and skin AGEs are powerful predictors for the
development of retinopathy, neuropathy and nephropathy (89).
For diabetic nephropathy, the role of AGEs is highly supported by clinical
studies where serum levels of AGEs are significantly increased with the
progression to microalbuminuria and subsequently overt nephropathy (90).
Of note, the proximal tubule is the main site for reabsorption of filtered
AGEs. Glucose uptake in the proximal tubule is not under the effect of
insulin meaning that hyperglycaemia is directly translated into high
intracellular glucose levels which in turn lead to AGEs production and
oxidative stress (91).
AGEs also interact directly with cell surface proteins, activating intracellular
pathways to alter vascular biology. These cell surface proteins, named
RAGEs (scavenger receptor class A) are also involved in the development of
microvascular complications. In the mice model, overexpression of RAGEs
in vascular endothelial cells promote nephromegaly, mesangial expansion,
glomerular hypertrophy and sclerosis (92).
Glycation is not the only mechanism by which vascular damage happens in
diabetes. Nevertheless, AGEs contribute to diabetic pathology both on their
own and in combination with other pathways. Advanced glycation is only one
of the pathways by which renal injury develops in diabetes. An interaction
between metabolic and hemodynamic factors is likely to promote the
deleterious effects of the diabetic milieu in the pathogenesis of diabetes
complications.
21
It seems likely that therapeutic agents that target multiple pathways be more
effective than an individual therapy in preventing diabetes associated renal
injury. In fact in rat models, a synergistic effect toward prevention of diabetic
nephropathy was demonstrated by blockade of the renin-angiotensin system
and inhibition of advanced glycation, This combined therapy was more
effective in preventing glomerulosclerosis and tubulointerstitial damage and
in reducing albuminuria (93). In the clinical setting, it remains to be
determined whether a combination of hemodynamic and metabolic
pathways is more effective than any individual pathway in preventing renal
injury.
2.7.1.2 Activation of Aldose Reductase (Polyol) Pathway This theory
postulates that during hyperglycaemic states, there is activation of the polyol
pathway. The polyol pathway reduces toxic aldehydes generated by reactive
oxygen species to inactive alcohols via aldose reductase (94). In parallel,
sorbitol dehydrogenase reduces glucose to sorbitol, and eventually into
fructose. Elevated intracellular glucose can increase the activity of aldose
reductase. The aldose reductase reaction uses NADPH (nicotinamide
adenine dinucleotide phosphate) as a co-factor, decreasing the availability of
this enzyme for other pathways, which are required to reduce intracellular
oxidative stress. The combination of decreased NADPH and increased
oxidative stress activate other pathways that promote cellular damage,
which in turn causes vasoconstriction and compromises blood supply (95,
96) (Figure 2.5). Therefore, the increased activity of the aldose
reductase/polyol pathway is likely to result in vascular damage secondary to
osmotic changes, induction of oxidative stress and reduced Na+K+-ATPase
activity.
Based on the polyol pathway, one would expect that the use of aldose
reductase inhibition would be an appropriate target for prevention of
microvascular complications. However, initial studies with aldose reductase
inhibitors in the 1980’s ans 1990’s suggested lack of significant effects for
neuropathy, retinopathy and nephropathy (97, 98). More recently, preliminary
22
data on new generations of aldose reductase inhibitorsm is promising in the
management of diabetic peripheral neuropathy (99).
Figure 2.5 Activation of aldose reductase or polyol in diabetes. NADPH =
nicotinamide adenine dinucleotide phosphate
[Source: The Journal of the American Osteopathic Association, Vol 100, No 10, October
2000]
2.7.1.3 Activation of Protein Kinase C (PCK) Theory Protein kinase C is
a family of 12 structurally and functionally related serine/threonine kinases
involved in intracellular signalling related to vascular, cardiac, immunologic
and other systemic functions (94). Pathological activation of PKC can occur
in diabetes.
Some of its isoforms, particularly the β and δ, are expressed in the
vasculature. Abnormalities in PKC activity result in vascular changes in
retinal and renal blood flow, contractility, permeability and cell proliferation
(92).
Activation of PKC in blood vessels of the retina, kidney and nerves can
produce vascular damage tha includes increased permeability, increased
leucocyte adhesion and alterations in blood flow (100, 101).
23
The proposed mechanisms to explain PKC activation in diabetes patients
and its link to diabetes microvascular complications are shown in Figure 2.6.
The use of β-selective PKC inhibitors has been shown to attenuate the
progression of experimental DN in rodents in the setting of continued
hyperglycemia, hypertension, and activation of RAS (102).
Oral Ruboxistaurin treatment, a selective PKC- β inhibitor, has sjown to
reduce vision loss, need for laser treatment, and macular edema
progression in patients with diabetes (103). In type 2 diabetes, treatment
with ruboxistaurin reduced albuminuria and maintained eGFR over 1 year
suggesting some benefit to patients with diabetic nephropathy (104).
Figure 2.6 Activation of diacylglycerol (DAG)-PKC pathway in the
pathogenesis of diabetic microvascular complications. Activation of PKC,
particularly β and δ isoforms, will promote vascular changes and changes in
gene expression, which contribute to the development of microangiopathy
[Source: Endocrinology and Metabolism of North America, Vol 33 (March), 2004)
24
2.7.1.4 Other mechanisms
a) Oxidative stress-induced vascular pathology Hyperglycaemia
generates increased activity of the polyol pathway, AGE formation and
activation of the PKC pathway. All these biochemical changes result in the
production of reactive oxygen species and oxidative stress. Oxidative stress
is implicated in the pathogenesis of microvascular complications by causing
endothelium dysfunction, vascular leakage and altered motor tone (92).
b) Changes in expression and action of growth factors Many growth
factors, which regulate vascular biology and tissue fibrosis, have been
implicated in the pathogenesis of microvascular complications. Vascular
endothelial growth factor (VEGF) has been associated with microvascular
complications in children and adolescents with T1DM (105), and particularly
associated with DR (106). Profibrotic factors, transforming growth factor β1
(TGF-β1) and connective tissue growth factor (CTGF), are increased in
diabetic kidneys and are likely to contribute to the accumulation of
extracellular matrix and mesangium expansion (92).
In addition to the role of hyperglycaemia in DN, haemodynamic disturbances
promote the development of glomerulosclerosis and proteinuria. Among
these factors, systemic and intraglomerular hypertension and in particular
the role of vasoactive hormone such as angiotensin II will be discussed in
further detail.
2.7.2 HAEMODYNAMIC CHANGES AND DN
Both metabolic and haemodynamic insults trigger intracellular signalling
pathways which promote the release of cytokines and growth factors
mediating renal damage.
2.7.2.1 The Role of Systemic Hypertension
The impact of hypertension on DN is independent of other contributing
factors in children, adolescents and adults with T1DM (107).
25
A sustained reduction in blood pressure seems to be the most important
single intervention to slow the progression of nephropathy in type 1 and type
2 diabetes. Diabetic patients with blood pressure < 130/80 mmHg rarely
develop MA and have a decline of GFR similar to age-matched normal
population. On the contrary, diabetic patients with blood pressure between
130/80 and 140/90 mmHg have a greater decline in GFR and 30% of them
develop MA or proteinuria over the subsequent 15 years (108).
Strict blood pressure control is important for preventing progression of
diabetic nephropathy and other complications in patients with type 2
diabetes. In the United Kingdom Prospective Diabetes Study (UKPDS),
each 10 mmHg reduction in systolic pressure was associated with a 12
percent risk reduction in diabetic complications; the lowest risk occurred at a
systolic pressure below 120 mmHg (109). Therefore, normotension is crucial
in the management of diabetes and in preventing DN.
Genetic factors determine a patient’s risk of hypertension and subsequent
DN. There is considerable evidence of familial clustering of long-term
complications of diabetes (110). A higher frequency of hypertension is
observed among subjects with DN and their first-degree relatives suggesting
that susceptibility to develop nephropathy may be influenced by an inherited
predisposition to essential hypertension (111). The susceptibility to DN was
investigated in a subset of 98 young T1DM adults from the Oxford Regional
Prospective Study showing that a higher paternal night to day ratio of ABP
and albumin to creatinine ratio were associated with the presence of
incipient DN (112).
In children with T1DM, parental hypertension is associated with higher 24-h
diastolic blood pressure prior to development of DN and has an independent
effect on longitudinal AER (113).
In microalbuminuric and proteinuric adults with diabetes, several studies
have demonstrated a benefifical effect on microalbuminuria and blood
pressure with the use of agents that block the renin-angiotensin system
(114-119). A more aggressive target for blood pressure control has shown to
reduce the development of incipient and overt nephropathy (120).
26
A meta-analysis based on 698 normotensive adults with T1DM and MA who
received agents that block the renin-angiotensin system (RAS) concluded
that these agents have a clear beneficial effect on AER with a one-third
reduction in the progression to macroalbuminuria and a threefold regression
to normoalbuminuria (121).
Because of the central role of the RAS in the development of DN and the
beneficial effects of agents that interrupt the RAS in this condition, a number
of candidate genes encoding for various components of the RAS may
predict DN. This topic will be explored in more detail in the session
Genetics of Diabetes Nephropathy.
2.7.2.2 The Role of Glomerular Capillary Hypertension and Glomerular
Hyperfiltration in DN
Glomerular hypertension is central to the initiation and progression of DN.
Classical studies performed more than 20 years ago using renal
micropunctures suggested that glomerular hypertension, as observed in
experimental diabetes, has a central role in the initiation and progression of
diabetic nephropathy, even in the setting of normal systemic blood pressure
(122).
Elevations of 25-50% in the whole-renal glomerular filtration rate (GFR),
measured by creatinine clearance or using filtration markers, have been
described in many T1DM patients at diagnosis and during the first years
after diabetes onset preceding the appearance of proteinuria (123).
The mechanisms by which diabetic patients develop glomerular
hyperfiltration are unclear. Animal studies suggest that afferent glomerular
arterioles dilate more than the efferent ones, raising GFR and
intraglomerular pressure. These hemodynamic changes have been
proposed to mediate diabetic glomerulopathy in streptozotocin-induced
diabetic rats (124). Moreover, increased GFR and renal plasma flow have
been reported in newly onset type 1 and type 2 diabetes patients,
suggestive of afferent renal vasodilation. These studies showed elevated
filtration fraction, indicating glomerular hypertension (123, 125-127). Several
27
mechanisms have been proposed as to leading to the afferent glomerular
vasodilation including elevated insulin levels (123), insulin-like growth factor
1 (128), advanced glycation products (129) and a direct effect of
hyperglycaemia (130).
In diabetes, glomerular capillary hypertension happens when the blood
pressure within the glomerulus increases due to impaired autoregulation of
the glomerular microcirculation. Vasodilatation of both afferent and efferent
arteriole occurs, more pronounced on the afferent side, leading to an
increase in the intraglomerular capillary pressure (131). In experimental
diabetes, glomerular hyperfiltration is also a result of increased tubular
reabsorption of glucose and sodium, which causes vasodilation due to
decreased tubuloglomerular feedback (132).
Glomerular hyperfiltration has been associated with the development of
diabetic nephropathy. A meta-analysis of 10 cohort studies involving 780
subjects followed for a median of 11 years suggest an increased risk for
diabetic nephropathy in patients with early glomerular hyperfiltration
compared to those with normal GFR (130). Conversely, a series of 426
T1DM patients followed for 15 years was unable to detect an association
between glomerular hyperfiltration and progression to incipient DN
suggesting that other factors, mainly poor metabolic control, might play a
more important role compared to glomerular hyperfiltration itself (133).
The intra-glomerular hyperfiltration and hypertension in diabetes will lead to
mechanical stretching of all glomerular components, including mesangial
cells and podocytes.
This mechanical injury promotes extracellular matrix accumulation through a
variety of mechanisms summarized in Figure 2.7, including the increased
synthesis of extracellular matrix, decreased activity of degradative enzymes,
induction of gene and protein expression of TGF-β1 (a profibrotic factor),
upregulation of glucose transporter GLUT-1 and angiotensin II (powerful
vasoconstrictor and trophic hormone), production of VEGF and an increased
inflammatory response in the mesangial cells (108).
Moreover, in DN mechanical stretch decreases podocyte proliferation,
increases apoptosis and promotes podocyte detachment from the
28
glomerular basement membrane (108). Mechanical stretching of the the
glomeruli, and stretching-induced podocyte loss will ultimately lead to to
progressive podocyte loss and glomerulosclerosis in diseases associated
with intra-glomerular hypertension, including diabetic nephropathy (108).
Figure 2.7 Mechanisms of extracellular matrix deposition in mesangial cells
caused by mechanical stretch in DN
[Source: Hypertension, Vol 48, 2006]
2.7.2.3 Treatment of Glomerular Hyperfiltration
Diabetic renal injury is mediated by increased renal blood flow, increased
fitration factor, vasodilation of afferent arteriole and increased proximal
tubular sodium absorption which promote glomerular hypertension and
consequent activation of the RAS (134). Therefore, iIncreasd glomerular
pressure could be attenuated by the use of agents that block the
vasoconstrictive effects of angiotensin II on the glomerular efferent arteriole.
In fact, animal data support the beneficial effects of angiotensin 1
converting-enzyme inhibitors (ACEI) or angiotensin II receptor blockers
(ARB) in causing egression in glomerulosclerosis even in advanced phases
of renal disease (135).
29
Several randomized controlled trials in patients with T1DM and T2DM
confirm that ACEI and ARB therapy can prevent the development of ESRD
(136-138), overt nephropathy (114, 139) and microalbuminuria (81, 140).
However, the effect of blocking the activity of the RAS with the use of ACEI,
ARB or even a combination of these therapies is partially limited due to the
angiotensin II and aldosterone breakthrough (141).
2.8 Genetics of Diabetes Nephropathy
Patients with T1DM face a 20-50% risk of developing ESRD requiring
dialysis or renal transplantation (142). As not all individuals with diabetes
develop nephropathy, it is likely that an interaction of environmental factors
and genetic susceptibility play an important role in the development of this
complication. There is evidence of familial clustering of diabetes nephropathy
and a higher incidence of kidney complications among siblings of probands
with DN indicating a strong genetic component (143, 144).
Several groups of genes associated with different metabolic pathways have
been proposed as candidates for influencing the development of DN.
Because the RAS is an important regulator of systemic and local circulation
and is involved in the pathogenesis of arterial hypertension (145), it has been
postulated that genetic polymorphisms of its various components are
important in the pathogenesis of this complication. Systemic and intra-renal
RAS plays an important role in the pathogenesis of diabetic nephropathy
(146). Local production of angiotensin II promotes intra-gomerular
hypertension via constriction of the efferent arterioles contributing to to the
development and progression of glomerulosclerosis. Angiotensin II
stimulates the production of several cytokines, such as TGF-β (147) or
reactive oxygen species (148) mediating accumulation of extra-cellular matrix
proteins and causing cellular dysfunction under diabetic conditions.
Clinical trials have demonstrated that blockage of angiotensin II with either
ACEI or ARB prevent or delay the progression of renal injury associated with
diabetes (136). Therefore, the impoprtance of RAS with respect to the
pathogenesis of diabetic nephropathy is well established.
30
2.8.1 Genes of the Renin-Angiotensin System (RAS)
As accumulating evidence suggests that genetic susceptibility plays an
important role in the development of diabetic nephropathy (149-151), genes
encoding for some components of RAS, such as angiotensin-converting
enzyme, angiotensinogen and angiotensin II receptor type 1, have been
reported to be most probable candidate genes for DN.
The RAS comprises the renin, angiotensinogen (AGT), angiotensin I-
converting enzyme (ACE) and angiotensin II receptor type 1 and 2 (AGTR1,
AGTR2) genes (Figure 2.8)..
The renin gene, located on chromosome 1q32, it is expressed in the
juxtaglomerular cells of the kidney. Circulating renin catalyzes the conversion
of the AGT to angiotensin I.
The AGT gene, located on chromosome 1q42-43, is expressed in the liver.
Angiotensin I is vasoinactive and the conversion of angiotensin I to
angiotensin II is the key reaction of the RAS pathway. This reaction is
catalyzed by the enzyme ACE.
The ACE gene is located on chromosome 17q23. Angiotensin II, the major
bioactive peptide of the RAS, exerts its main effects by binding to two
transmembrane G protein receptors, namely angiotensin II receptors type 1
(AGTR1) and type 2 (AGTR2).
The physiological actions of angiotensin II on vasoconstriction, hyperthrophy
and catecholamine liberation from sympathetic nerve endings (152) are
mostly mediated by the subtype AGTR1 expressed in cardiovascular cells,
such as the vascular smooth muscle cells. The activation of AGTR1 by
angiotensin II triggers a number of cytoplasmatic siganling pathways which
will exert its functional significance in mediating vascular remodelling (153).
Genetic variants of the RAS components, AGT, ACE and AGTR1 genes,
have been implicated in the aetiology of hypertension, coronary artery
disease, myocardial infarction and non-diabetic renal disease. Therefore,
these genes are considered potential candidates involved in the
pathogenesis of diabetic renal complication (152, 154-160).
31
Figure 2.8 The renin angiotensin system (RAS) and the role of ACE
[Source: The Journal of Molecular Diagnostics, Vol 2, August 2000]
2.8.1.1 The angiotensin 1-converting enzyme (ACE) gene and DN
ACE plays a key role in maintaining blood pressure and kidney function
through modulation of RAS and the kinin-kallikrein systems (152). Rigat et al
first described the relationship between the ACE insertion/deletion
polymorphism and its role in controlling ACE levels. In this study, an
insertion/deletion of a 287 base pair Alu sequence in intron 16 of the ACE
gene, the ACE I/D gene, accounted for almost 50% of the variance of serum
ACE and was the major determinant of serum ACE concentration. Subjects
with a DD genotype for the ACE gene had higher serum concentrations while
II individuals had the lower serum concentrations (161).
The D allele has been associated with increased serum ACE activity together
with enhanced conversion of angiotensin I to angiotensin II (162), inactivation
of bradykinin (163) and more rapid progression of renal disease (164).
The possible casual association between the ACE I/D polymorphism and the
development of DN was studied in mice. Diabetes was induced in mice
genetically engineered to have 1, 2, or 3 copies of the gene. After 12 weeks,
the 3-copy diabetic mice developed higher blood pressure and proteinuria,
which also correlated with increased plasma ACE levels (165).
32
In humans, the genetic variation at the ACE gene, mainly the
insertion/deletion (ACE I/D) variant, has been found to be associated with the
development of DN in both type 1 and type 2 diabetes, as demonstrated by a
meta-analysis of almost 15,000 subjects between 1994 and 2004. Subjects
homozygous for the insertion allele (ACE I/I) had a 22% lower risk of DN
when compared to carriers of the D allele (166). More recently, a meta-
analysis on 63 studies from 1994 to 2010 involving 14,108 DN cases and
12,472 controls demonstrated a significant association between the ACE I/D
polymorphism and the risk of DN for all genetic models, particularly for the
development of DN in the Asian group with T2DM (167).
The prognostic value of the ACE I/D polymorphism for nephropathy in T1DM
was confirmed in 310 patients followed for 6 years. The D allele
independently favoured the development of incipient nephropathy (168).
Supporting these data, the DCCT/EDIC groups followed 1,365 T1DM
subjects and reported that presence of I/I genotype conferred a lower risk for
both persistent MA and severe nephropathy (169).
Most studies in the paediatric population have a cross-sectional design and
include only small numbers. Some have found that in T1DM normotensive
and normoalbuminuria children, the DD genotype was associated with higher
diastolic mean 24-h BP and lower diurnal variation (170) while others found
no correlation between ACE I/D genotype and BP or AER (171).
2.8.1.2 The angiotensinogen (AGT) gene and DN
Angiotensinogen is the only precursor of angiotensin II, a vasoconstrictor and
growth factor implicated in the development of glomerulosclerosis and
mesangial cell hypertrophy (172). Cleavage of angiotensinogen by renin is
the rate-limiting step in activation of the RAS.
A molecular variant involving a methionine-to-threonine transition at
aminoacid position 235 (the AGT M235T polymorphism) has a functional
effect. This polymorphism has been correlated not only with plasma levels,
with highest AGT levels observed in subjects homozygous for the T allele
compared to MT or MM, but also with essential hypertension and
33
cardiovascular disease (173-175).The association between the AGT M235T
variant of the AGT gene has also been recognized among individuals with
early onset of familial hypertension (176).
Examination of the AGT M235T gene polymorphismIn for association with
DN has shown conflicting results. The presence of the TT genotype for AGT
was found to increase the risk for DN by almost 3-fold in a case-control study
involving 95 T1DM patients with nephropathy compared with 100 T1DM
patients without DN (177). An interactive effect between the AGT and ACE
genes was reported in T1DM subjects who developed DN (178). Others have
found that the T allele of the AGT M235T gene is associated with elevated
AER, but only when combined with the D allele of the ACE I/D polymorphism
(179). A gender-specific association of M235T polymorphism has been
described for DN in subjects with T2DM where the M235T variant contributed
to the risk of DN in men but not in women (180). Moreover, the TT genotype
was associated with a faster progression to renal failure in diabetic patients
as described in a large study involving 327 controls and 260 patients with
ESRD (181).
On the other hand, other studies have have failed to report an association
between AGT polymorphisms and DN (182-185) but demonstrated an
association between the TT genotype and elevated blood pressure (183).
Others have found that homozyosity for the M allele of the AGT gene
increased the risk for nephropathy either independently (186, 187) or in a
combinational effect with the D allele of the ACE gene (188).
2.8.1.3 The angiotensin II receptor type 1 (AGTR1) gene and DN
AGTR1 subtype, expressed in the vascular smooth muscle cells, is a
membrane-bound G-protein-coupled receptor that mediates the most
relevant biological properties of angiotensinogen II.
Bonnardeaux et al identified five silent polymorphisms at the AGTR1 gene,
the T573C, A1062G, A1166C, G1517T and A1878G and subsequently
described a significant allelic frequency of the C1166 polymorphism in
hypertensive individuals compared to normotensive controls (189). Since
34
then, an association between the AGTR1 A1166C polymorphism and the
predisposition to hypertension, left ventricular hypertrophy, coronary artery
disease and myocardial infarction has been described (152). A study of 708
adults found a significant associtation between the presence of C1166 and
left ventricular mass (190). A recent meta-analysis of 16,474 subjects from a
total of 22 studies revealed that C1166 allele confered a higher risk of
hypertension (191).
In diabetes, a possible link between A1166C variant of the AGTR1 gene and
the increased risk for microalbuminuria was reported in T2DM patients (192).
More recently, the AGTR1 1166C allele was associated with lower
glomerular filtration rates, kidney dysfunction and with coronary heart
disease in patients with T2DM (193). In addition, the presence of CC at the
AGTR1 gene was more prevalent in T2DM subjects with microalbuminuria
compared to normoalbuminuric ones; CC AGTR1 significantly increased the
incidence of albuminuria after 10 years of diabetes duration (194).
In T1DM, a synergistic effect of the AGTR1 polymorphism and poor
glycaemic control increased the risk of DN in a case-control study of 152
patients, 79 being normoalbuminuric. The risk of nephropathy in the group
with poor glycaemic control during the first decade of diabetes was higher
among the C 1166 carriers compared with A 1166 carriers (195). More
recently, a meta-analysis was performed to estimate the risk of
polymorphisms at the AGT and AGTR1 genes associated with the
development of DN on 4,377 cases and 4,905 controls from 34 published
studies. Overall, a two-fold increased risk of DN was demonstrated for
subjcts with the AGTR1 CC 1166 compared to AA 1166 supporting that
AGTR1 polymorphism may contribute to DN development (196).
2.8.2 Other candidate genes
In addition to genes involved in BP regulation and the RAS, any gene that
could potentially mediate the functional changes observed in the
pathogenesis of DN can be regarded as a potential candidate.
35
Among these genes are those involved with 1) synthesis and degradation of
glomerular basement membrane and mesangial matrix; 2) metabolic
pathways involved in glucose metabolism and transport; 3) cytokines, growth
factors and transcription factors; and 4) advanced glycation among others.
Polymorphisms in the aldose reductase gene have been implicated in DN
indicating a role of the polyol pathway in the pathogenesis of diabetic kidney
disease (197).
Genes involved in lipid oxidation, such as paraoxonase 1 and 2 genes, have
been described in association with increased risk for persistent MA in a large
group of T1DM adolescents (198).
Polymorphisms in the apolipoprotein E gene, a glycoprotein known to play a
key role in lipid metabolism, has also been associated with an increased risk
of DN in T1DM (199).
Genes involved in insulin resistance (ecto-nucleotide pyrophosphatase gene,
ENPP1 gene), glucose transport (GLUT1 gene), and inflammation
(interleukin-6, interleukin-6 receptor, fibrinogen genes) have been linked to
DN and vascular complications, but still need to be closely examined in the
paediatric population (200-202).
A summary of some of the candidate genes in which polymorphisms have
demonstrated in association with T1DM diabetic nephropathy are
summarized in Table 2.1.
36
Table 2.1 Candidate genes in which polymorphisms have demonstrated
association with T1DM diabetic nephropathy
Class Gene Symbol Location
Renin-
angiotensin
system
Angiotensin-converting enzyme
Angiotensinogen
Angiotensin II receptor type 1
ACE
AGT
AGTR1
17q23
1q42-43
3q21-25
Glucose
metabolism
Aldose reductase
Glucose transporter-1
Receptor for advanced glycation end
products
AKR1B1
SCL2A1
RAGE
7q35
1p35
6p21.3
Growth
Factors
Transforming growth factor β1
Transformer growth factor β –
receptors I-III
Vascular endothelial growth factor
TGFB1
TGFBR1/2/3
VEGF
19q13.1
9q22,3p22,1
p33
6p12
Oxidative
stress
Paraoxonase 1 and 2
Superoxide dismutase 1 and 2
Haptoglobin
Catalase
PON1/2
SOD1/2
HP
CAT
7q21-22
21q22,
6q25.3
16q22
11p13
Lipid
metabolism
Apolipoprotein E
Adiponectin
Peroximase proliferator activated
receptor gamma
APOE
ADIPOQ
PPRγ
19q13.2
3q27
3p25
Inflammatory
factors
Interleukin-1
Intercellular adhesion molecule-1
IL1B
ICAM1
2q14
19p13.3
Others Endothelial nitric oxide synthase
Protein kinase C, β1
NOS3
PRKCB1
7q36
16p11.2
[Table adapted from Clinical Practice Nephron (203)].
37
2.9 DN in Children with T1DM
Both genetic and environmental risk factors have been described in
association with DN (Figure 2.9).
Figure 2.9 Potential genetic and environmental risk factors for the
development of long-term diabetes complications
[Source: Pediatric Diabetes, Vol 8 (suppl 6), 2007]
Among the environmental risk factors involved in the appearance of DN in
T1DM children and adolescents are glycaemic control, diabetes duration,
puberty, hypertension, smoking, lipid disorders, family history of vascular
complications and obesity. These factors are commonly associated with the
development of macro and microvascular complications in both adults and
children with T1DM.
2.9.1 Risk factors for DN and microvascular complications in children
with T1DM
Glycaemic control Glycated haemoglobin is presently the best parameter to
predict the risk of developing long-term complications. Several Interventional
studies provide clear evidence in adults and adolescents that better
glycaemic control as measured by lower HbA1c levels is associated with fewr
and delayed microvascular complications (41, 204, 205).
38
The Diabetes Control and Complications Trial (DCCT) was a randomized,
multicenter, prospective study involving 1441 patients with T1DM from 1983
to 1993 (41). In this trial, 195 subjects were pubertal adolescents (age 13-17
years) at recruitment (39). The DCCT demonstrated that intensive diabetes
treatment and lower HbA1c levels conferred a significant reduction risk for
both microvascular and macrovascular complications compared to
conventional treatment. In the adolescent cohort, there was a risk reduction
of background retinopathy of 53%, clinical neuropathy of 60% and MA of
54%. The difference in HbA1c after completion of the DCCT (median 7.4
year of follow-up) in the adolescent group was 8.1% vs. 9.8% (intensive vs.
conventional). The results observed in the adolescent group occurred
despite a higher HbA1c in the adolescent cohort treated by intensified
regimens compared to the total cohort in which the great majority were
adults (8.1% vs. 7.2%).
The Epidemiology of Diabetes Interventions and Complications (EDIC) study
continued to follow the DCCT cohort for another 8 years after the end of the
trial. Despite no differences in HbA1c at 4 years after completion of the trial,
the benefits of the intensive treatment and improved glycaemic control
during the DCCT persited and delayed the progression of microvascular
complications (Figure 2.10 and 2.11). In the former adolescent cohort there
was a 74% reduction in retinopathy, 48% reduction in MA and 85%
reduction in macroalbuminuria in those who received intensive treatment
(206). In addition, the EDIC study also showed a positive effect of intensive
therapy for reduction in of macrovascular disease (207).
39
DCCT indicates Diabetes Control and Complications Trial; EDIC, Epidemiology of Diabetes Interventions and
Complications; HbA1c, glycosylated haemoglobin. Boxes indicate 25th and 75th percentiles of HbA1c level;
whiskers, 5th and 95th percentiles; heavy horizontal lines, medians; thin horizontal lines, means.
Figure 2.10 Distribution of HbA1c Concentration by Randomized Treatment
Group at the end of the DCCT and in Each Year of the EDIC Study
[Source: The Epidemiology of Diabetes Interventions and Complications (EDIC) Study,
JAMA, 2003]
MA defined as AER 28 µg/min, equivalent to 40 mg/24 h. A, Prevalence at the end of the Diabetes Control and
Complications Trial (DCCT) and during the Epidemiology of Diabetes Interventions and Complications (EDIC)
study. The differences between the 2 treatment groups are significant at each time point after DCCT closeout
(P<.001). B, Cumulative incidence of new cases in the EDIC study for those participants in the intensive- and
conventional-treatment groups with normal albuminuria at the beginning and end of the DCCT. The difference in
cumulative incidences is significant by the log-rank test (P<.001).
Figure 2.11 Prevalence and cumulative incidence of MA
[Source: The Epidemiology of Diabetes Interventions and Complications (EDIC) Study,
JAMA, 2003]
40
The sustained effect reported by EDIC study suggests that the influence of
previous glycaemic control can leave an imprint on the cells of the
vasculature and target organs, favouring the future development of diabetes
complications, a phenomenon defined as “metabolic memory” (208). The
term glycaemic exposure, encompassing both the degree of hyperglycaemia
and time, and the concept of “metabolic memory” are supported by the long-
term influence of early metabolic control on clinical outcomes (208).
Although MA is rare before puberty, even in subjects with long diabetes
duration (12, 61, 209), the concept that pre-pubertal glycaemic control does
not affect the development of microvascular complications has changed over
the years. Several groups have demonstrated that glycaemic exposure
during the pre-pubertal years confers additional risk to the development of
MA and retinopathy (210, 211) . Schultz et al showed in a large cohort that
children diagnosed with T1DM before puberty had a latent period of time to
developing MA, which was then followed by a rapid development of MA after
the onset of puberty. In contrast, those diagnosed at or after puberty had a
constant rate of MA over time (210). Early glycaemic exposure, particularly in
the first years of diabetes, seems to accelerate the occurrence of
microvascular complications in childhood onset T1DM (212).
Experts agree that at present, the safest recommendation for improving
glycaemic control in all T1DM children is to achieve the lowest HbA1c that
can be sustained without causing severe hypoglycaemia while avoiding
prolonged periods of significant hyperglycaemia (blood glucose levels > 15-
20 mmol/L) and episodes of diabetes ketoacidosis (213). There is little age-
related scientific evidence for strict, i.e.nearl normal, glucose targets. Each
child should have their targets individually determined aiming at values as
close to normal as possible while avoiding severe hypoglycaemia as weel as
frequent mild to moderate hypoglycaemia. The targets in Table 2.2 are
proposed as guideline by the International Diabetes Federation and
International Society for Pediatric and Adolescent Diabetes (213).
41
Table 2.2 Target indicators of glycaemic control in T1DM children and
adolescents
Level of
control
Ideal
(non-diabetic)
Optimal Suboptimal High Risk
Clinical assessment
Raised blood
glucose (BG)
Not raised No symptoms Polyuria, polydipsia
and enuresis
Blurred vision, poor
weight gain, poor
growth, delayed
puberty, signs of
microvascular
complications
Low BG Not low Mild and no
severe
hypoglycaemias
Severe
hypoglycaemias
(unconscious
and/or convulsions
Biochemical assessment – targets must be adjusted according to individual circumstances
Self monitoring blood glucose levels in mmol/L
AM fasting or
preprandial
plasma
glucose
3.6 – 5.6 5 -8 >8 >9
Postprandial
plasma
glucose
4.5 - 7 5 - 10 10 - 14 >14
Nocturnal
plasma
glucose
3.6 – 5.6 4.5 - 9 < 4.2 or >9 <4.0 or >11
HbA1c% DCCT standardized
DCCT <0.05 <7.5 7.7 – 9.0 >9.0
[Table adapted from Global IDF/ISPAD guideline for Diabetes in Childhood and Adolescence
(213)].
42
Duration of diabetes and the effect of puberty In an incident cohort of
childhood onset T1DM, the effect of diabetes duration could be removed by
examining all patients at a median duration of 6 years (214). Increasing age
and later pubertal staging were associated with increased risk for early
elevation of albumin excretion (AER>7.5 μg/min) (Figure 2.12). In this study,
one year of age increased the risk of borderline AER (AER 7.5 – 20μg/min)
by 27% (OR 1.27, CI 1.12 – 1.45). Pubertal stages 4-5 conferred a five-fold
increased risk for borderline AER (OR 5.3, CI 1.71 – 15.99) over pubertal
stages 1-3 (215).
Cumulative pecentage of borderline AER
0
20
40
60
80
100
5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21
Age (years)
Pe
rce
nta
ge
(%
)
Figure 2.12 Cumulative percentage of borderline AER by age in T1DM with
diabetes duration of 6 years
[Source: Pediatric Diabetes, Vol 8 (suppl 6), 2007]
Postpubertal years of diabetes contribute more heavily to the risk of
developing microvascular complications (8, 210, 211, 216, 217). For the
same number of years of diabetes duration, children in puberty will have
increased risk for incipient DN and for retinopathy in comparison to pre-
pubertal children (36). By comparing adolescents with pre-pubertal and
postpubertal onset of diabetes, retinopathy developed at a shorter period of
diabetes duration among those with pubertal onset of diabetes indicating
that pubertal years have a greater impact in developing complications
compared to prepubertal years (211).
A recent multicentre study involving 105 patients aged 16-40 years
compared the effect of prepubertal duration on the occurrence of
43
complications in T1DM patients after the same number of years of the
disease. The authors found that patients diagnosed in early infancy were
protected from microvascular complications but this effect disappeared if
lifetime metabolic control was poor. Instead, the onset of diabetes in puberty
was itself an independent risk factor for complications which was less
dependent of metabolic control suggesting that other factors such as blood
pressure influence these complications in pubertal years (218). Other have
reported similar findings for both retinopathy (217) and for MA (210).
The duration of glycaemic exposure in pre-pubertal years give a strong
additional risk to the development of MA and retinopathy. The Berlin
Retinopathy Study compared time to onset of retinopathy in children and
adolescents with pre and postpubertal onset of diabetes. The postpubertal
duration until retinopathy was shorter by 3 years in those with prepubertal
diabetes onset (211). In Sweden, a population-based study followed 94
T1DM children (age 0-14 years at diabetes onset) for a median of 12 years.
Inadequate glycaemic control in the first 5 years of diabetes accelerated
time to occurrence of DN (212).
The mechanism by which puberty confers a higher risk for DN is
multifactorial. Glycaemic haemoglobin levels during puberty are higher than
rcommended levels for prevention of complications. In the DCCT,
adolescents showed the same benefits from intensified therapy as adults but
HbA1c levels were generaly 1% higher and weight gain was more frenquent
(39). Children of pubertal age at T1DM onset have poorer glycaemic control
when compared to those diagnosed at a younger age (210). The association
between deterioration in glycaemic control and higher prevalence of MA
observed in puberty is consistent with a decrease in sensitivity to insulin
action observed during the pubertal stages (219).
The relationship between puberty and MA is only partly explained by poor
metabolic control and there is evidence that puberty itself may be an
independent factor (220). A more pronounced progression of albuminuria
occurs during puberty when compared to before or after this period
supporting the concept that other changes in pubertal hormones lead to
kidney damage (221).
44
Growth hormone and IGF-1 have been associated with the pathogenesis of
early DN (222). Derangements in growth hormone and IGF1 are described
in adolescents with T1DM. In comparison to normal controls, diabetic
children excretes more urinary growth hormone at every pubertal stage
(223). Persistent MA in T1DM adolescents occurs more frequently during the
first stages of puberty compared to late pubertal stages (224). Adolescents
girls with MA have lower IGF-I and elevated testorenone levels when
compared to normoalbuminuric controls (225). In addition, girls have been
reported to have an increased risk of MA during puberty in comparison to
boys (210, 224). The observation that hyperandrogenism and low sex
hormone-binding globulin levels in T1DM adolescent girls accompany the
development of MA suggest the role of ovarian hormonal changes as a
contributor to the development of incipient DN and may, at least in part,
account for the sexual dimorphism in MA noticed in puberty (225).
In adolescence, the development of MA has also been associated with
hyperlipidemia (226), elevation of arterial BP (227), decline in renal function
(55) and retinal changes (228). Moreover, MA may represent the first
evidence of a generalized endotheliopathy (229). Markers of endothelial
function, measured by flow mediated dilation, and of early atherosclerosis,
measured by carotid artery intima-media thickness, are abnormal in
adolescents with T1DM (230).
Inflammation is a condition that is common to obesity (231) and T1DM (232),
and systemic inflammation is associated with the development of diabetic
nephropathy (233) and macrovacular complications in T1DM (234).
Increased systemic inflammation, measured by higher levels of hsCRP, IL-6
and fibrinogen, were demonstrated in youth with T1DM compared to non-
diabetic youth regardless of adiposity and glycaemic control (235).
Blood pressure Hypertension contributes more to cardiovascular disease in
diabetic patients than in non-diabetic individuals and is a major factor in the
development of all vascular complications including atherosclerosis,
nephropathy and retinopathy (236). Hypertension has emerged as a risk
45
factor for the appearance and progression of microvascular complications
T1DM adults (43, 237, 238).
In normotensive children with T1DM, elevations in both systolic and diastolic
blood pressure as a continuous variable increase the probability of early
retinopathy (228). Interventional studies with Angiotensin Converting
Enzyme (ACE) inhibitors have shown a reduction in the progression of
retinopathy in adults with T1DM (239). Moreover, intensive blood pressure
control in normotensive T1DM adults slows the progression of nephropathy
(240) and retinopathy (241).
The prevalence of hypertension among patients with T1DM with normal
AER, determined on the basis of causal BP assessment at routine clinical
visits, does not differ from that in the general population (242).
In normotensive individuals, the systolic and diastolic BP variation follows a
circadian pattern in which values are lower at nighttime than during daytime.
In T1DM adults, abnormalities in this rhythm, or non-dipping status, precede
the development of clinical hypertension and have been associated with
increased risk of overt DN and early mortality (243). In addition, the
measurements of ABP give additional information about diurnal variation
during normal activities. Patients with T1DM and MA who are normotensive
on casual blood pressure assessments present with elevated ABP in
comparison to normoalbuminuric individuals (244). In T1DM adolescents,
higher 24-h ABPvalues , still in the normotensive range, have been
associated with persistent MA and subclinical signs of autonomic
neuropathy compared to normoalbuminuric patients and normal controls
(245).
In T1DM normotensive children, the non-dipping pattern has been reported
in association with incipient DN (246, 247). Of note, abnormalities of ABP
were also reported in association with high AER and family history of
hypertension suggesting that this measure may be helpful in detecting
T1DM children prone to develop DN (248).
46
Lipids Lipoproteins contribute to the appearance of microvascular
complications in T1DM subjects. Reports from the DCCT/EDIC studies
confirmed dyslipoproteinaemia to be associated with the development of DN
in individuals with T1DM (32). In a cross-sectional study, lipoproteins from
968 subjects were analysed and renal dysfunction was associated with a
more atherogenic lipoprotein profile: higher total and low density lipoprotein
(LDL) cholesterol and higher triglycerides (32). The severity of retinopathy
was positively associated with triglycerides and negatively associated with
HDL cholesterol implying the involvement of dyslipoproteinaemia in the
pathogenesis of DR (249).
Hyperlipidaemia is commonly reported in adolescents with T1DM (226). A
one-third reduction of major vascular events is observed among T1DM
adults treated with HMG-CoA reductase inhibitors (statins) (250).The role of
statin treatment in children and adolescents with T1DM is unclear as there
have been no studies of HGM-CoA therapy in this population. Short-term
studies in children with familial hypercholesterolaemia show treatment to be
beneficial and safe (251). However, the effects of early statin intervention
on the development of micro and macrovascular complications in T1DM
children need to be addressed through longer-term trials.
Smoking Smoking is correlated with higher AER, MA and borderline
albuminuria in T1DM adolescents (252). Smoking is also associated with
poorer glycaemic control. In addition, an increased prevalence of retinopathy
has been reported in smoking versus non-smoking patients with T1DM
(253).
Family history of vascular complications The DCCT study provided
evidence that familial factors, independent of metabolic control, influence the
presence of DN (110). Despite poor glycaemic control, there are some
T1DM subjects who do not develop microvascular complications (254). This
and the observation of familial clustering of diabetes complications (110)
imply that hereditary factors modify susceptibility to microvascular
complications.
Obesity Higher BMI has been documented as a risk factor for MA (255)
retinopathy, neuropathy (256) as well as associated with for cardiovascular
47
disease (257). In patients with T1DM, correlations among central obesity,
insulin resistance and MA have been reported (258, 259) suggesting a role
of central obesity in the pathogenesis of renal complications in T1DM.
Central obesity was found to be a strong predictor for the development of
MA in the EDIC study (260).
2.10 Screening guidelines for diabetes complications in T1DM children
The current guidelines for screening for diabetes vascular complications
recommended by the International Society for Pediatric and Adolescent
Diabetes (ISPAD) are summarized in Appendix A. ISPAD guidelines are
used by diabetes centres in Australia and New Zealand and are in
agreement with the position statement from the Australasian Paediatric
Endocrinology Group (APEG). The ISPAD Consensus Clinical Practice
Guidelines recommend annually screening from age 11 yrs with 2 yrs of
diabetes duration or from 9 yrs with 5 yrs duration will capture most children
and adolescents developing retinopathy and MA. For macrovascular
disease, the recommended strategy proposes that lipid profiles should be
assessed from age 12 yrs and then be performed every 5 yrs; blood
pressure measurements are recommended to be performed annually (261).
The American Diabetes Association (ADA) Annual screening suggest that
screening for MA should be initiated at age 10 yrs for children who have
diabetes for longer than 5 years; for DR this guidleines suggest the first
ophthalmologic examination once the child is 10 yrs or older and has had
diabetes for 3-5 yrs. For dyslipidaemia, ADA guidelines advise that
prepubertal children older than 2 yrs should have an initial screening at
diagnosis and for this to be repeated every 5 yrs. In pubertal children older
than 12 years, a fasting lipid profile should be performed at diagnosis and
repeated every 5 yrs (262).
The American Academy of Pediatrics recommends an initial eye
examination 3-5 years after diagnosis of diabetes in subjects older than 9
yrs, with annual follow-ups thereafter (263).
48
CCHHAAPPTTEERR TTHHRREEEE
49
CCHHAAPPTTEERR 33 SSTTUUDDYY II
““PPrreevvaalleennccee aanndd rriisskk ffaaccttoorrss ffoorr
mmiiccrrooaallbbuummiinnuurriiaa iinn aa ppooppuullaattiioonn--bbaasseedd
ssaammppllee ooff cchhiillddrreenn aanndd aaddoolleesscceennttss wwiitthh TT11DDMM
iinn WWeesstteerrnn AAuussttrraalliiaa
3.1 PREFACE This chapter was published and the full PDF is presented in
Appendix C
50
3.2 Abstract
Objective. To define the prevalence and describe the natural history of MA
(MA) in a population-based sample of children with T1DM.
Methods. Children with T1DM diagnosed 16 years and screened for MA
were identified through the Western Australia diabetes register created in
1991. The diabetes register provides clinical information of all patients
followed routinely at the service. An audit from all data collected from 1991
and 2003 was used for the analysis. Three-monthly HbA1c was performed
from diagnosis. MA screening (AER in 3 timed overnight samples) was
yearly performed after 10 years of age or after 5 years from diagnosis. Cox
proportional model assessed the risk of different variables on the occurrence
of MA. Kaplan-Meier survival analyses (log-rank test) estimated the
probability of developing MA.
Results. Nine hundred and fifty-five T1DM children (462 male), mean
diabetes duration of 7.6 years, mean age at onset of diabetes of 8.5 years
were selected for the study. MA, mean AER 20 and < 200μg/min,
developed in 128 subjects (13.4%) at mean diabetes duration of 7.6 years.
Cumulative probability for MA was 16% after 10 years. Determinants for MA
were HbA1c (HR 1.21; 95% CI 1.05 -1.38; p=0.007), onset of puberty (HR
8.01; 95% CI 3.18 - 20.16; p<0.001) and age at diagnosis (HR 1.25; 95% CI
1.18 -1.33; P<0.001). Females had a higher probability for MA during
puberty than males (p=0.03). The total incidence of MA (subjects with
MA/100 person-years) was 1.26, 1.85 and 2.44 for those who developed
diabetes at ages < 5 years, 5-11 years and > 11 years, respectively.
Conclusions. Onset of puberty, diabetes duration and metabolic control are
major factors predisposing the development of MA. Children diagnosed with
T1DM at younger ages have a prolonged time for developing MA.
51
3.3 Introduction
In subjects with T1DM, persistent MA (MA) is a predictor of nephropathy and
is associated with an increased risk of cardiovascular disease and early
mortality (3-7). Although a decline in incidence of DN has been reported
(264), between 20 to 80% of adults with T1DM and MA will progress to overt
nephropathy (5-7, 51).
Long-term sub-optimal glycaemic control is an important but not the only risk
factor for development of microvascular complications in T1DM (265, 266).
Other positive predictive factors for the appearance of DN include increasing
age, and duration of diabetes (10, 12, 210, 267), poor metabolic control
within the first five years (10, 268), dyslipidaemia, hypertension (267, 268),
smoking (253) and familial and genetic factors (269-272).
Although persistent MA is predictive for overt nephropathy in adults with
diabetes, its prognostic implications among children and adolescents are
less well defined. Duration of diabetes is a risk factor for MA in children with
T1DM (267, 273, 274), however, MA is uncommon before the onset of
puberty (61, 209, 224, 275). Puberty, characterised by changes both in body
composition, metabolism and hormones, is frequently associated with
deterioration in metabolic control in subjects with T1DM, and all of these
factors may be implicated in the development of incipient nephropathy (9,
222).
Princess Margaret Hospital for Children is the only referral centre for children
diagnosed with T1DM in the state of Western Australia and case
ascertainment levels of 99% are consistently achieved (23, 276). This
prospectively assessed cohort provides a unique opportunity to report the
characteristics and natural history of MA in a population-based sample of
childhood onset T1DM.
52
3.4 Methods
Western Australia is the largest state in Australia with an estimated
population of 1.9 million. Aboriginal people account for 3.5% of the state’s
population and the remainder consists mainly of people of European
descent. This population is mainly distributed in the metropolitan areas with
approximately 25% of people living in the remote/rural areas. The
Endocrinology and Diabetes service at Princess Margaret Hospital for
children provides centralised medical care for all children with diabetes in the
state.
Nine hundred and sixty-nine children aged 0-16 years at onset of T1DM
were initially identified for this study through the Western Australia Children’s
Diabetes database created in 1991. All participants were screened for MA
between 1991 and 2003. Fourteen subjects had only been screened for
AER through one sample of spot urine, and were excluded from the
analysis. The remaining 955 subjects were studied.
As part of our standardised diabetes care program, subjects are seen 3
monthly at clinic with HbA1c being measured at every visit. Height and weight
are measured at each visit and blood pressure at every second visit.
Screening for MA, as by the estimation of AER from three consecutive
overnight urine samples, was performed yearly before puberty when
diabetes duration was more than 5 years or after 10 years of age. The age
of 11 years was used as a definition for the onset of puberty for both sexes
in accordance with other reports in literature (210, 224)
Ethics approval was obtained from the Princess Margaret Hospital Ethics
Committee. Informed consent was obtained from all subjects prior to their
data being stored on the diabetes database.
3.4.1 Definition of microalbuminuria
The classic definition of MA is the presence of AER 20 and 200 μg/min in
2 out of 3 consecutive urine samples. For this study, MA was defined as
mean AER, from three consecutive overnight urine samples, being 20
53
μg/min and < 200 μg/min. A mean of 3.6 2.1 MA screenings/subject
(minimum 1, maximum 12) was performed.
The collection of urine samples was routinely performed at a time interval of
6-12 months and the results were stored in the database. AER collected at
longer intervals (more than 1 year apart) were also included. Urinalysis was
routinely performed to exclude infection and urine collections were not
performed in the presence of any intercurrent illness. Onset of MA was
considered the first occasion when an abnormal AER screening was
observed. Clinically, subjects that present an abnormal screening are
requested a second MA screening performed 6 months apart. In this case,
persistent MA was defined as the presence of a second positive screening
with mean AER 20 μg/min and < 200 μg/min.
All definitions of MA are somewhat arbitrary. By using the classic definition
of AER 20 and 200 μg/min in 2 out of 3 consecutive urine samples
twelve subjects would not be included in our analysis. All twelve subjects
presented with at least one AER in the MA range. The use of the mean AER
as the definition of MA did not affect the final results and therefore this
parameter was chosen to facilitate the analysis.
3.4.2 Laboratory evaluation
HbA1c – The mean HbA1c level for the entire follow-up period was used as a
reflection of metabolic control. HbA1c was followed 3 monthly from diagnosis
to either the first event of MA or during the entire follow-up period. Prior to
1993, glycosylated haemoglobin measurements were performed using an
HPLC (high performance liquid chromatography) assay. The assay was
changed from HPLC to Ames DCA 2000 early in 1993. In this method, HbA1c
is assayed by latex agglutination inhibition using DCA 2000 analyser (Bayer
Ltd, Indianapolis, IN, USA). The inter-assay coefficient of variability (CV) was
4.69% and 2.81% at HbA1c levels of 5% and 11% respectively. On the
changeover, the first 400 samples were analysed by both methods, which
allowed correlation between methods.
54
AER assay - All overnight urine samples were collected and stored at
temperatures between +2 to +8C prior to testing. Urine analysis until 1997
were performed using timed overnight urine AER through Randox
Microalbumin competitive enzyme-linked immunosorbent assay (ELISA)
using rabbit antibodies to human albumin (Cat No MA1410), manufactured
by Randox Labs Ltd, Diamond Rd, Crumlin, County Antrim, N Ireland, UK.
The inter-assay CV was 8.5% and 8.9% for measurements of 9.7 mg/L and
97.6 mg/L respectively. From 1997 to 1999, the method was changed to
nephelometry on the Behring Nephelometer Analyser (BNA). The inter-
assay CV was 3.3% at 10.4 mg/L and 2.7% at 91.2 mg/L. A comparison
between the methods was done using regression equations (Randox ELISA
= 0.9472 Nephelometer + 1.39). From 1999 the AER method was changed
to the Tina-quant Albumin, an immunoturbidimetric assay using
Roche/Hitachi 917. The intra-assay CV was 2.2% at 38.43 mg/L. The inter-
assay CV was 6.4% at 14.15 mg/L and 1.5% at 83.78 mg/L. The latter two
methods were compared and the slopes were virtually identical with a
correlation coefficient close to 1.
3.4.3 Statistical analysis
SPSS 11.5 for Windows was used for statistical analysis, which included
independent two-tailed Student’s t test for differences in mean values
between two groups and Yate’s corrected chi-square for testing differences
in proportions. One-way ANOVA was used for differences in means within
more than two groups. Differences in incidence density were calculated
using the exact binomial probability. Kaplan- Meier survival curves were
used to estimate the probability of developing MA. The log-rank test was
performed to compare survival time. Cox Regression was used for modelling
time-to-event data. It estimated the contribution of each variable to the risk of
developing the outcome, after adjusting for known covariates. Duration of
diabetes was the time variable (unless otherwise stated) and MA was
considered the outcome. Gender, mean HbA1c, puberty and age at diagnosis
were included in the model as covariables. A P value of less than 0.05 was
considered to indicate statistical significance.
55
3.5 Results
3.5.1 Clinical characteristics
For all 955 subjects, the mean diabetes duration at follow-up was 7.6 4.1
years (range 0.9-21.4). The mean age at onset of diabetes was 8.5 3.8
years (range 0.8-15.9) and the mean HbA1c was 9.2 1.4% (range 5.6-
13.9).
One hundred and twenty-eight subjects (13.4%) in the total cohort
developed MA at mean diabetes duration of 7.6 ± 3.8 years (range 1.3 –
17.2).
Forty-four subjects (4.6%) had persistent MA (second positive screening
within 6 months). MA regressed in 61 subjects (47.6% MA cases). In twenty-
three subjects no subsequent AER measurements were yet available until
the end of the study.
Six subjects (mean age of 12.0 ± 1.9 years; mean duration 7.0 ± 4.3 years
(0.6%) presented with macroalbuminuria as the first abnormal screening and
were not included in the analysis for MA. Among the 44 subjects with
persistent MA, three developed macroalbuminuria with a mean follow-up
period of 2.2 ± 0.8 years.
Hereafter, the term MA is used to refer to only the first abnormal values of
AER.
3.5.2 Microalbuminuria, metabolic control, age at diagnosis, gender,
duration of diabetes and puberty
Mean HbA1c was significantly higher among those who developed MA
compared to those who did not (10.1% 1.7 and 9.1% 1.3 respectively,
P<0.001) (Table 3.1).
56
Table 3.1 Gender, HbA1c, incidence density and postpubertal incidence
density of MA for subjects aged < 5, 5-11 and > 11 years at diabetes onset
< 5 yrs 5-11 yrs > 11 yrs Total
n 197 475 277 949
M/F 99/98 212/263 149/128 460/489
Age (years) 15.1 3.5 15.7 2.9 17.7 2.3 16.2 3.1
Age at onset (years) 2.9 1.2 8.2 1.7 12.9 1.3 8.5 3.8
Duration (years) 12.1 3.4 7.5 3.4 4.7 2.5 7.6 4.1
MA subjects (M/F) 14/16 30/36 16/16 60/68
HbA1c (%) Non-MA
subjects
9.4 1.1 9.1 1.2 8.9 1.5 9.1 1.3
HbA1c (%) MA subjects 10.7 1.5 a
10.3 1.6 b
9.3 1.6
10.1 1.7 c
Total person-years (from
diabetes onset to the last
follow-up)
2386.5 3560.2 1306.2 7251.9
Postpubertal years 829.2
2261.2 1306.2 4396.6
Total incidence density of
MA
1.26
1.85 2.44 d
1.77
Postpubertal incidence
density of MA
3.25 2.78 2.44 2.77
HbA1c, glycated haemoglobin; MA, MA. Data are presented as mean SD or n unless
otherwise stated.
a P < 0.001 versus < 5 years non-MA group.
b P < 0.001 versus 5-11 years non-MA group.
c P < 0.001 versus whole non-MA group.
d P = 0.009 versus < 5 years total incidence density of MA.
57
Mean HbA1c was higher among those who developed MA when age at
diagnosis was less than 5 years or between 5 - 11 years (10.7% 1.5 vs
9.4% 1.1 and 10.3 % 1.6 vs 9.1 % 1.2 respectively, P<0.001). There
was no difference in mean HbA1c between children with and without MA
aged > 11 years at diabetes onset.
Considering MA as the outcome and duration of diabetes as the time
variable, the probability for developing MA was 16% after 10 years and 37%
after 15 years of diabetes duration.
Girls represented 51.5% of the total cohort and no difference in gender was
seen among those with and without MA.
Similar age, duration of diabetes and mean HbA1c were observed between
boys and girls who developed MA. The Kaplan-Meier curve for the
appearance of MA was similar between males and females either using
duration of diabetes or age attained as the survival time.
Girls were more likely to develop MA during pubertal years (11 – 15 years)
(n=269) when age attained was used as the time variable (log-rank test,
P=0.03) (Figure 3.1).
58
Figure 3.1 Cumulative probability (Kaplan-Meier survival curves, log-rank
test, P=0.03) for the development of MA for boys and girls during puberty (○
females, □ males).
Using 11 years of age as the defined age for onset of puberty, only 6 (4.7%)
of 128 individuals developed MA before puberty (mean age SD of 9.8 1.1
years) and three of them developed diabetes before 5 years of age.
Dividing the subjects into three groups: those who were aged < 5 years
(n=197), 5 - 11 years (n=475) and > 11 years at diagnosis (n=277) enabled
the evaluation of the effect of diabetes duration and puberty on the
development of MA. Kaplan-Meier survival curves as a function of age at
onset showed a highly statistical difference in the cumulative probability for
the appearance of MA across the 3 groups (log-rank test, P<0.001) (Figure
3.2).
59
Figure 3.2 Cumulative probability (Kaplan-Meier survival curves, log-rank
test, P<0.001) for the development of MA for each year since diabetes onset
in three groups divided by age at diagnosis (+ < 5 years, □ 5 to 11 years and
○> 11 years)
Among those aged < 5 years at diabetes onset the probability for MA was
5% after 10 years of diabetes duration. This same probability was achieved
after only 2.5 years among those who were diagnosed with diabetes > 11
years of age. In addition, the increase in the probability of developing MA
remained constant over time among the oldest age-at-onset group while in
the youngest age-at-onset group, the cumulative probability for MA started
to increase after a period of 8 years of diabetes.
The total incidence density of MA, defined as the number of subjects who
developed MA per 100 person-years of follow-up, was highest among those
who were > 11 years of age at diagnosis of diabetes when compared to
those diagnosed < 5 years of age (P = 0.009). There was a trend in the
incidence rates of MA to be higher in the 5-11 group compared to those
60
diagnosed < 5 years (P = 0.07) but no difference in the incidence rate of MA
was observed between the 5-11 and > 11 years groups at diagnosis. The
two groups who were prepubertal at diagnosis demonstrated a higher
incidence rate of MA after puberty (Table 3.1).
3.5.3 Contribution of the different risk factors for developing of MA
The proportional contribution of gender, puberty, age at diagnosis and mean
HbA1c (glycaemic exposure) for the development of incipient nephropathy
was measured using the Cox proportional hazard model. Modelling MA as a
function of glycaemic control up to the onset of MA or during the entire
follow-up and adjusting the model for gender, age at diabetes onset and
onset of puberty, an increase in hazard ratio (HR) of 21% per one
percentage unit increase in mean HbA1c was observed (HR 1.21; 95% CI
1.05 – 1.38, P=0.007). The probability of developing MA was higher after the
onset of puberty by a factor of 8. Also, an increase in HR of 25% was
noticed per one-year increase in the age of diabetes onset for a given
duration of diabetes (HR 1.25; 95% CI 1.18 -1.33; P<0.001) (Table 3.2).
Table 3.2 Proportional contribution of gender, puberty, age at diabetes onset
and HbA1c as risk factors for the development of MA with duration of diabetes
as the time variable (n= 949)
Variable Baseline
value
P value Hazard Ratio
Exp ()
95% CI for HR
Gender Female 0.72 1.07 0.74 – 1.53
Puberty Prepubertal 0.000 8.01 3.18 – 20.16
Age at diagnosis 0.000 1.25 a
1.18 – 1.33
Mean HbA1c (%) 0.007 1.21 b 1.05 – 1.38
HbA1c, glycated haemoglobin; HZ, hazard ratio; MA, micro albuminuria.
For gender and puberty, the probability for developing MA is expressed as a ratio relative to
the baseline values, female and prepubertal years.
a Hazard ratio per one year increase in age of diabetes onset.
b Hazard ratio per one percentage unit increase in HbA1c.
61
3.6 Discussion
We report the association of MA with gender, duration of diabetes, age at
onset, metabolic control and puberty in a population-based cohort of children
with T1DM followed from diagnosis to a mean age of 16 years and a mean
duration of 8 years. In this cohort, the prevalence of MA of 13 percent was
similar to prevalence rates of 8- 18% that have been reported in cross-
sectional studies (8, 277-279)
As one of the main determinants for the development of microvascular
complications, our results confirmed that an increase in the mean HbA1c
increased the risk for developing MA over time for the total cohort. Poor
metabolic control directly correlates with hyperfiltration and renal
hyperperfusion in early stages of T1DM (280) and it has been reported as a
major risk factor for MA even among young subjects with diabetes (281). In
our cross sectional analysis between those with and without MA, subjects
diagnosed > 11 years presented no differences in the mean HbA1c. This
group had a shorter duration of follow-up and consequently a shorter
duration of exposure to high glucose levels, which could partially explain
similar mean HbA1c between those with and without MA. These results do
not exclude the effect of higher HbA1c as a risk factor over time in the
development of MA. For the total group a difference in mean HbA1c was
observed between those with and without MA. When adjustments for other
variables related to MA were performed, including duration of diabetes and
onset of puberty, mean HbA1c was still a remarkable risk factor in the
appearance of MA in this cohort.
In addition, the effect of diabetes duration on the risk of MA was not constant
over time. Subjects who developed diabetes at younger ages presented a
latent period of time with little risk for MA followed by an abrupt increase in
this risk, which coincided with the onset of puberty. By contrast, in subjects
developing diabetes after puberty, an increased risk for MA occurred at
earlier time after the onset of diabetes and at a constant rate.
Epidemiological data suggests that postpubertal years of diabetes contribute
more heavily to the risk of developing DN (8, 9, 278, 282) compared to the
prepubertal ones and persistent MA has been reported in T1DM adolescents
62
during the early stages of puberty (224). Our findings suggest that children
developing diabetes at younger ages have a prolonged time to the
development of renal complication and may be relatively protected during
their early years of diabetes. However, once puberty is achieved, the
prepubertal years of diabetes contribute as an additional risk for MA. The
relative protection of development of MA in prepubertal years seems to be
overcome by a longer duration of diabetes and longer glycaemic exposure,
which give additional risk for MA after puberty. A higher incidence rate of MA
in postpubertal years among those diagnosed with T1DM earlier in life
suggests that a similar cumulative probability for MA across the age groups
might occur with a longer duration of diabetes, but longer follow-up is
needed to confirm these observations in our cohort. Similar findings were
reported by Donaghue et al who described an increasing delay in the onset
of retinopathy and MA in subjects with T1DM with a longer prepubertal
duration (217). A study by the Danish group revealed that prepubertal and
postpubertal duration of diabetes are contributors for the development of
retinopathy. Similar results were not observed for the development of
increased AER or MA. Our study involves a population-based cohort with a
different study design and different age for puberty onset which may have
contributed for the discrepancies in findings (283). Other factors other than
glycaemic control and duration of diabetes play a role in the development of
DN. The DCCT/EDIC and Pittsburgh epidemiology of diabetes studies have
demonstrated that multiple genetic susceptibilities, insulin resistance,
atherogenic lipoprotein profiles and inflammatory markers are associated
with increased risk of DN (258, 284, 285). The concept of microhypertension
or incipient hypertension has also been associated with the development of
MA. Early disturbances of blood pressure in normotensive subjects with
T1DM have been reported and increments of blood pressure occur in
parallel to AER even within the normal range (246, 286).
The mechanisms by which puberty increases the risk of the development
and progression of MA are not completely understood. Both the increase in
insulin requirements and insulin resistance observed in puberty might result
in poor glycaemic control (287) a well established risk factor for
63
microvascular complication (265). Our data showed that the total incidence
of MA was higher among those who started with diabetes after puberty and
a rise in postpubertal incidence of MA was observed among those with
prepubertal age at diabetes onset, as described in the Oxford Regional
Prospective Study (210). As the group diagnosed with T1DM after puberty
who developed MA differed from the prepubertal one by having a better
glycaemic control, the proportional hazard model was applied and the
estimate probability for puberty was corrected for mean HbA1c. Still, puberty
was associated with an 8-fold increase in the likelihood of developing MA,
representing a strong independent risk factor for the development of MA.
Additional hormonal changes may contribute to kidney damage during
puberty other than deterioration in metabolic control. Experimental models of
DN have implicated sex steroids in its pathogenesis (288, 289). This study
did not show any differences in gender regarding the total number of
subjects who developed MA. When age was used as the time for the
development of MA, our results demonstrated that girls are at increased risk
of developing MA during puberty. A possible explanation for this finding is
the high androgen and low sex hormone-binding globulin levels that have
been associated with increased risk of MA during puberty, particularly in
females (225, 290). The development of hyperandrogenism and insulin
resistance secondary to polycystic ovarian syndrome is more common
among female adolescents with T1DM and could also explain the gender
discrepancies of MA during puberty. Other factors including changes in
growth hormone release and low IGF-I levels, more commonly reported in
girls with T1DM (222, 225, 278, 291-293), and glomerular hypertrophy and
hypertension (10, 61, 268, 279, 294) may also be involved in the
pathogenesis of MA during the pubertal years. In addition, as onset of
puberty at the age of 11 years was arbitrarily chosen, the discrepancies in
gender during pubertal years might reflect the fact that girls start puberty
earlier and have it for a longer period of time compared to boys. No
differences in gender were observed in the cumulative probability for MA
after puberty.
64
In summary, the cumulative probability of MA in this cohort of children and
adolescents is strongly associated to the onset of puberty. Poorer metabolic
control, age at diagnosis and diabetes duration are also determinants for
MA. Children diagnosed at younger ages have a prolonged time to the
appearance of MA but once puberty is achieved, prepubertal years increase
the risk for renal complication. Although MA seems to regress in
approximately 50% during childhood, there is need for longitudinal follow-up
particularly of this high risk group for the development of overt DN and
cardiovascular complications later in life.
3.7 Acknowledgements
This study was supported by grants from the Diabetes Research
Foundation, Perth, Western Australia. We wish to thank Maree Grant,
endocrine nurse and clinical data manager at the Department of
Endocrinology and Diabetes, Princess Margaret Hospital for Children,
Western Australia for her invaluable advice.
65
CCHHAAPPTTEERR FFOOUURR
66
CCHHAAPPTTEERR 44 SSTTUUDDYY IIII
““Early changes in 24-hour ambulatory blood
pressure are associated with high normal
albumin excretion rate in children with type 1
diabetes”
4.1 PREFACE This chapter was published and the full PDF is presented in
Appendix C
67
4.2 Abstract
Objective. The relationship between urinary AER and elevated blood
pressure (BP) is unclear as a cause-effect phenomenon in the development
of DN. The aim of this study was to examine the association between AER,
HbA1c and BP in children with normoalbuminuria.
Methods. 24-hour ambulatory BP assessment was performed in 78 children
with T1DM, mean age ± SD of 13.4 ± 2.7 yrs, range 7.3-18.3 yrs, mean
diabetes duration ± SD of 6.6 ± 2.9 yrs, range 2.1-11.9 yrs. Using
generalised linear mixed models with systolic (SBP) and diastolic (DBP)
blood pressure as dependent variables, the effects of AER and HbA1c were
examined, adjusting for age, gender, diabetes duration and insulin dose.
Results. Subjects with high normal AER (7-20 mcg/min) had higher SBP
during daytime and nighttime compared to the low normal AER ( 7
mcg/min) (mean SD of 118.20 7.98 and 110.33 7.08 mmHg, P= 0.02;
mean SD of 108.76 9.21 and 100.20 7.75 mmHg, P= 0.03,
respectively). DBP was also higher both during day and nighttime when
compared to the 7 mcg/min group (mean SD of 73.40 6.50 and 64.86
5.67 mmHg, P= 0.002; mean SD of 62.50 6.75 and 56.30 5.56 mmHg,
P=0.03 day and nighttime respectively).
Conclusion. A rise in SBP and DBP is associated with increased levels of
AER even within the normal range.
68
4.3 Introduction
Nephropathy and hypertension remain major complications of T1DM mellitus
(T1DM). Persistent MA in diabetic patients is a risk factor not only for renal
disease but also for cardiovascular morbidity and mortality (4, 28, 295). The
cumulative incidence of DN in patients with T1DM is approximately 25-30%,
although a decline has been reported probably as a result of improved
glycaemic control (3, 296, 297). Several risk factors have been described
associated with the onset and progression of MA in children and adolescents
with T1DM including gender, HbA1c, duration of diabetes, pubertal status
(11, 61, 210, 268), as well as elevated BP and increased levels of AER (268,
298).
The prevalence of hypertension among patients with T1DM with normal
urinary AER, determined on the basis of blood pressure (BP) readings at
clinic visits, is similar to that in the general population (242).
Measurements of ABP (ABP) give additional information about the
differences between daytime and nighttime BP and about the diurnal
variation during normal activities. Patients with T1DM and MA often present
with elevated BP (detected using ABP monitoring) but it is unclear whether
the elevation precedes the appearance of MA or is concomitant with its
development (245, 299-301). Systolic and diastolic blood pressures follow a
circadian pattern in normotensive individuals with values being lower at night
than during the day. The loss of diurnal rhythm has been shown to correlate
with kidney disease (246, 247, 302), with a higher incidence of
cardiovascular disease and as an early sign of DN (247, 303, 304). The non-
dipping status (loss of the normal BP circadian pattern) has been related to
renal morphologic changes and to long-term hyperfiltration in
normoalbuminuric subjects with T1DM independent of duration of diabetes
(305).
In this study, we examined the relationship between blood pressure and
albumin excretion in a cohort of normoalbuminuric children with T1DM.
69
4.4 Research design and methods
A total of 78 children with T1DM were randomly selected from the Children’s
Diabetic Clinic at Princess Margaret Hospital for Children, Perth, Western
Australia. All children with T1DM in the State are currently followed in this
service. None of the patients had evidence of other chronic illness nor had
received anti-hypertensive treatment. All study participants were
normoalbuminuric (urine AER <20 mcg/min in at least 2 out of three timed
overnight collections) and had no evidence of other microvascular
complications of T1DM.
Height, weight and pubertal status were assessed in all patients by the
clinician at the time of the visit. Pre-pubertal subjects were classified as
stage 1, early pubertal as stage 2, mid-pubertal as stage 3 and finally, when
puberty was complete as stage 4-5 according to Tanner (306).
4.4.1 Urinary AER assay
Three overnight urine samples were collected and stored at temperatures
between +2 and +8C prior to testing and were analysed within one week of
arrival at the laboratory. Urinary albumin concentrations were measured by a
Randox Microalbumin competitive enzyme-linked immunosorbent assay
using rabbit antibodies to human albumin (Cat No MA1410), manufactured
by Randox Labs Ltd, Diamond Rd, Crumlin, County Antrim, N Ireland, UK.
The interassay coefficient of variation was 8.5% and 8.9% for measurements
of 9.7 mg/L and 97.6 mg/L respectively. The AER method is sensitive
enough to detect levels as low as 1 mcg/min. The values less than 1 are still
detectable, but results are described as < 1 mcg/min. For the analyses
where the mean AER was used, AER’s reported as < 1 mcg/min were
considered 1 mcg/min.
4.4.2 Mean HbA1c levels
HbA1c is measured 3 monthly in all subjects and the mean HbA1c was
calculated from the onset of diabetes. HbA1c was assayed by latex
agglutination inhibition using DCA 2000 analyser (Bayer Ltd). Inter-assay
70
coefficient of variation was 4.69 and 2.81% at HbA1c measurements of 5
and 11.5% respectively. The non-diabetic reference range is < 6.2%.
4.4.3 Assessment of BP
The 24-h ABP was monitored using an oscillometric portable automatic
monitor, the Suntech Accutracker® II (Suntech Medical Instruments,
Raleigh, North Caroline USA). The monitor was programmed to perform
systolic BP (SBP) and diastolic BP (DBP) measurements at 30-min intervals.
Patients followed their usual insulin regimen, avoided excessive physical
activity and none reported symptoms of hypoglycaemia. The use of the
monitor was explained to each participant and the appropriate cuff was
chosen and attached to the non-dominant arm. Subjects were instructed to
relax the arm during the blood pressure measurement.
For the purpose of ABP monitoring, two different periods were defined:
daytime which included all readings obtained from the time the subject woke
up to the time he went to bed and nighttime which included all readings from
the time he went to bed until the time he woke up.
The 24-h ABP measurements were statistically examined for mean systolic
and diastolic BP and respective standard deviations.
In this study, normal circadian variation was defined as a difference of 10/5
mmHg or more between mean daytime and nighttime blood pressure.
Patients were classified into “dippers” or “non-dippers” based on the
presence or absence of nocturnal dip (304).
4.4.4 Statistical analysis
Using the SPSS software package (version 11.5 for Windows), the
independent Student’s t test was used to compare means between the low
normal AER and the high normal AER groups.
Logistic regression analysis was used to examine the association between
several variables when considering dippers or non-dippers as the final
outcome.
71
In order to use all repeated measurements, a generalised linear mixed
model with SBP and DBP as dependent variables was applied. The effects
of AER and HbA1c were examined adjusting for age, gender, duration of
diabetes, body mass index (BMI) and insulin/kg/day (SAS software
package). A P value of less than 0.05 was considered to indicate statistical
significance.
72
4.5 Results
4.5.1 Characteristics of the subjects at the time of enrolment
Among the 78 subjects (40 males, 38 females) the mean ± SD age was 13.4
± 2.7 years (range, 7.4-18.3 years) and the mean ± SD duration of diabetes
of 6.6 ± 2.9 years (range, 2.1-11.9 years). Fourteen patients were pre-
pubertal, 27 were in early puberty (Tanner stage 2 and 3) and 37 were in
late puberty (Tanner stage 4). AER was performed in 75 subjects. Mean
AER, based on the mean of the 3 overnight urine samples, was within the
normal range in all of them (mean SD 3.58 2.88; range 1.00 – 18.57
mcg/min).
ABP was completely assessed in 65 subjects with measurements during
daytime and nighttime. The remaining subjects had some BP readings either
during daytime or nighttime and all measurements were included in the
mixed model.
The mean values for the 24-h ABP for each individual was in the normal
range. The 24-h BP mean ± SD for the SBP was 106.92 ± 12.08 and for the
DBP was 62.07 ± 11.12 mmHg. Mean ± SD daytime SBP and DBP were
110.92 7.39 and 65.49 6.12 mmHg, respectively. Mean ± SD nighttime
SBP and DBP were 100.72 8.03 and 56.68 5.78 mmHg, respectively
(307).
4.5.2 Subgroup analysis according to AER
Seventy-five subjects had a complete assessment of AER based on 3
overnight urine samples. Subjects were classified into 2 subgroups based on
the mean AER from the 3 samples. Mean AER less or equal to 7.0 mcg/min
were considered low normal albuminuria and mean AER above 7.0 mcg/min
but lower than 20 mcg/min were considered high normal albuminuria. The
cut off value of 7.0 mcg/min was used as this value corresponded to the 95th
percentile of normal for this cohort.
73
The clinical characteristics of the 2 groups are shown on Table 4.1. Seven
patients presented with a “high normal” AER (4 males; 3 females) and all
were in puberty (Tanner stage 3 and 4).
Table 4.1 Characteristics of children and adolescents with T1DM with low
and high normal AER
Low Normal AER
(n=68)
High Normal AER
(n=7)
t test
Age (yrs) 13.4 2.7 15.2 1.6 NS
Duration (yrs) 6.6 2.7 7.5 4.3 NS
AER (mcg / min) 2.8 1.4 10.7 3.1 P = 0.002
Mean HbA1c (%) 8.6 0.8 8.9 1.0 NS
24-h SBP (mmHg) 106.7 ± 12.0 111.1 ± 12.6 P < 0.001
24-h DBP (mmHg) 61.7 ± 11.0 69.0 ± 12.4 P = 0.006
SBP –daytime (mmHg) 110.3 7.1 118.2 8.0 P = 0.02
DBP – daytime (mmHg) 64.8 5.7 73.4 6.5 P = 0.002
SBP-nighttime (mmHg) 100.2 7.7 108.7 9.2 P = 0.03
DBP–nighttime (mmHg) 56.3 5.6 62.5 6.7 P = 0.03
Results are expressed in mean ± SD. SBP, systolic blood pressure; DBP, diastolic blood
pressure
Mean AER was higher in the high normal AER group, as expected (mean
SD of 10.66 4.14 and 2.85 1.37 mcg/min respectively, P=0.002). No
differences were observed between the 2 groups regarding age, duration of
diabetes, gender, mean HbA1c or BMI.
The 24-h SBP and DBP were higher among those with high normal AER
levels compared to those with low normal AER (mean ± SD of 111.07 ±
74
12.59 and 106.72 ± 12.02 for SBP, P=0.006 and 68.99 ± 12.43 and 61.74 ±
10.95 for DPB, P<0.001)
Daytime SBP was higher among those with high normal AER (mean SD of
118.20 7.98 and 110.33 7.08 mmHg, P= 0.02) and so was nighttime
SBP (mean SD of 108.76 9.21 and 100.20 7.75 mmHg, P= 0.03).
Diastolic BP was also higher among subjects with high normal AER (mean
SD of 73.40 6.50 and 64.86 5.67 mmHg at daytime, P= 0.002; mean
SD of 62.50 6.75 and 56.30 5.56 mmHg at night-time, P=0.03).
In addition, a significant increase in both SBP (P=0.02) and DBP (P=0.01)
was observed comparing the high normal AER group to the low normal AER,
adjusting for age, gender, mean HbA1c, duration of diabetes, body mass
index (BMI) and insulin/kg/day.
In order to analyse in depth the effect of increasing AER on SBP and DBP,
subjects were further stratified in 3 categories of AER: < 2.0 mcg/min (n=10),
2–7 mic/min (n=58) and 7–20 mic/min (n=7). The effect of increasing AER
was not present on SBP comparing the 7-20 mcg/min group to the 2-7
mcg/min during daytime but it was still significant at nighttime (daytime
P=0.09 and nighttime P=0.03). The effect of increasing AER both at daytime
and nighttime DBP was still observed between the 7-20 and the 2-7 group
(daytime P=0.01 and nighttime P=0.03). There was no significant effect of
increased AER on either SBP or DBP during daytime or nighttime between
the < 2 and 2-7 groups (Figures 4.1 and 4.2).
75
AER (mcg/min)
7-202-7< 2
SB
P (
mm
Hg
)
130
120
110
100
90
Nighttime
Daytime
*
**
**
*
Figure 4.1 Effect of increments of AER on systolic blood pressure (SBP)
during daytime (■) and nighttime (●). Results are expressed as means and
95% CIs. P values represent the differences between the 2-7 and 7-20
mcg/min groups (* P=0.03; ** P=0.09).
AER (mcg/min)
7-202-7< 2
DB
P (
mm
Hg
)
90
80
70
60
50
Nighttime
Daytime
*
** *
**
Figure 4.2 Effect of increments of AER on diastolic blood pressure (DBP)
during daytime (■) and nighttime (●).Results are expressed as means and
95% CIs. P values represent the differences between the 2-7 and 7-20
mcg/min groups (* P<0.01; ** P <0.03).
76
4.5.3 Subgroup analysis according to glycosylated hemoglobin level
Subjects were grouped according to their metabolic control based on the
mean HbA1c in 4 categories: HbA1c < 7.5%, between 7.5 and 8.3%,
between 8.3 and 9% and finally >9.0%. There was no effect of increasing
the mean HbA1c and changes in SBP. A significant effect was observed on
DBP, but only when comparing the group with mean HbA1c >9% with the
others groups (P=0.02).
4.5.4 Subgroup analysis on dippers and non-dippers
Among 65 subjects (36 males, 29 females) whose ABP was completely
assessed, 29 (44.63%) had non- SBP dipping and 18 (27.6%) had non-
diastolic dipping. Non-dipping in both systolic and diastolic blood pressure
was observed in 15 (23.1%) subjects.
Non-dipping for systolic and diastolic BP was more common among males
than females (P=0.05 and P=0.03, respectively) adjusting for age, duration
of diabetes, mean HbA1c and mean AER. Neither long-term glycaemic
control nor mean AER at the time of the study increased the risk for non-
dipping BP.
77
4.6 Discussion
The relationship between elevated BP and incipient DN is important not only
to understanding the natural history of diabetic kidney disease but also when
considering intervention strategies that might prevent and delay the
development of overt nephropathy.
In this study, we found an increase in SBP and DBP both during daytime
and nighttime, detected by 24-h ABP monitoring, among normoalbuminuric
children with T1DM with higher AER levels. Even though borderline AER has
been defined differently by different authors, its development is associated
with a higher risk for developing incipient nephropathy (53, 54). In the Oxford
regional Prospective Study for Childhood Diabetes, higher tertiles of the
albumin excretion phenotype in children aged 11-15 years were predictive of
subsequent risk for the development of MA. Tracking the AER phenotypes in
a second independent cohort from Perth, Australia showed similar results.
All subjects who developed proteinuria had an AER in the upper tertile or
levels of HbA1c above 9%. (308).
Our findings are in accordance with studies that showed that higher 24-h BP
is present before the development of persistent MA among children and
young adults with T1DM (245, 247, 300, 301). Lafferty et al demonstrated an
incremental increase in all parameters of the 24-h BP from nondiabetic
controls through diabetic subjects with normoalbuminuria, intermittent and
persistent MA (245). Although our observations come from a cross-sectional
analysis of normoalbuminuric T1DM children who had never developed MA
(the classification of intermittent or persistent MA can not be applied in our
case) we still observed a simultaneous rise in BP and AER even in the
normal range. In spite of the lack a healthy matched control group in this
study, our data suggest that there is an early association between increased
AER and BP, which precedes MA in subjects with T1DM. These findings are
consistent with the observations of Garg et al who studied teenagers with
T1DM and concluded that 24-h ABP parameters were significantly higher
among those with borderline AER. In the same study, all BP parameters on
the 24-h ABP were similar for subjects with diabetes having AER’s less than
78
7.6 mic/min when compared to matched healthy controls (301). Of note, in
our study, there was no significant effect of increasing AER on the ABP
when < 2 and 2-7 mcg/min groups were compared suggesting that BP rises
only when borderline AER levels are achieved.
Giving credence to the observations described by Schultz et al (227), our
findings are not consistent with the hypothesis that elevations in systemic BP
are the initiating factor for DN but support the idea of a simultaneous rise of
both BP and AER. However, it is clear that longitudinal evaluation is needed
to clarify if the changes in BP precede those in AER.
The loss of circadian rhythm of BP has been related to albuminuria (305,
309) and it has been associated with an increase in mortality rate of adults
with diabetes and overt nephropathy (243). Diabetes duration, long-term
metabolic control, BMI and mean AER were not associated with abnormal
systolic or diastolic dipping in this study. These subjects will need
prospective assessment to investigate the persistence of abnormal BP
dipping and its real impact on the development of DN.
We conclude that early changes in both systolic and diastolic BP occur
concomitantly with a rise in AER prior to the development of MA. Early
structural changes have been described in borderline MA and these subjects
require further attention to minimise associated factors such as higher blood
pressure in the development of nephropathy. The use of 24-h ABP is a
sensitive method that should be used to identify T1DM subjects at risk of
developing nephropathy.
79
CCHHAAPPTTEERR FFIIVVEE
80
CCHHAAPPTTEERR 55 SSTTUUDDYY IIIIII
““Declining Trends of Albumin Excretion Rate in
Children and Adolescents with Type 1 Diabetes
Mellitus”
5.1 PREFACE This chapter has not been published. It is presented in full in
the following pages.
81
5.2 Abstract
Aim. The aim of this study is to examine the changes in prevalence of MA in
a population-based cohort of adolescents with T1DM between 1993 and
2004.
Methods. T1DM subjects (n=620, median age 14.8 years, median duration
6.6 years) matched by diabetes duration were selected for a cross-sectional
study of MA in three study periods (P1= 1993-1996; P2= 1997-2000 and
P3= 2001-2004). MA was defined as AER 20g/min and < 200g/min (2
out of 3 consecutive timed overnight urine samples). High AER was defined
as mean AER 7.5 g/min.
Results. High AER (P1 26%; P2 20% and P3 10%; P<0.001) and MA
prevalence (P1 5%; P2 6% and P3 2%; P=0.06; P2 6% vs. P3 2%; P=0.03)
declined over time. Metabolic control improved (mean HbA1c SD, P1 10.6
1.1; P2 9.4 1.1 and P3 8.4 0.8, P<0.001). Systolic and diastolic BP Z
scores decreased (mean SBP Z score SD, P1 0.46 1.13, P2 0.43 0.93,
P3 0.08 1.00, P<0.001 and mean DBP Z score SD, P1 0.16 0.73, P2 -
0.08 0.70 and P3 0.02 0.70; P=0.004) over time. More patients were
treated using intensive insulin management (P1 7%, P2 26% and P3 53%,
P<0.001) over time.
Conclusion. Prevalence of high AER and MA decreased in this cohort. Over
a 12-year period, intensified management and better metabolic control are
likely to have influenced changes in AER.
82
5.3 Introduction
Diabetes management has been strongly influenced by the Diabetes Control
and Complications Trial (DCCT), which confirmed a relationship between
optimal metabolic control achieved by intense diabetes management and
reduced microvascular complications both in adults and adolescents with
T1DM (265, 266, 310). Although a secular decline in the incidence of DN
has been reported among T1DM adults over the past years in some western
countries (264, 311), others have found no trend toward a decrease in DN
despite evidence of better glycaemic control (312, 313)
In adults with T1DM, MA is a marker for incipient nephropathy and is
considered a risk factor for renal disease, proliferative retinopathy, and
cardiovascular morbidity and mortality (295, 314).
Persistent MA is rare before the onset of puberty (209, 210, 224). The
prevalence rates vary between 4 and 21% in childhood (12, 61, 278, 279,
294). Reports suggest that the presence of MA in the first decade of disease
will persist or progress into the second decade in approximately two thirds of
children with T1DM (315). Even those with borderline increases in
albuminuria have a relatively high rate of progression to persistent MA, and
at higher risk of developing incipient DN (54).
We have reported an overall prevalence of MA of 13% in our population and
a cumulative probability for MA of 16% after 10 years of diabetes duration .
Risk factors involved in the appearance of MA during childhood included
poor metabolic control, onset of puberty, duration of diabetes, age at
diagnosis and gender discrepancies, among others (210, 212, 279, 316,
317).
We hypothesised that improvements in glycaemic control and modifications
in diabetes management have reduced the prevalence of MA over time. The
aim of this study was to assess the changes in AER in a population-based
cohort of adolescents with T1DM screened for DN from 1993 to 2004.
83
5.4 Patients and methods
5.4.1 Study design and patients
The Endocrinology and Diabetes service at Princess Margaret Hospital for
Children is the only referral centre for subjects diagnosed with T1DM under
the age of 16 years in the state of Western Australia with a case
ascertainment of over 99% (23). Clinical information has been collected from
all subjects since diabetes onset and data have been stored in the Western
Australia Children’s Diabetes database since 1987. All cases of T1DM have
been confirmed by auto-antibody testing.
Information on clinical features, on the results of blood tests and urine
protein of the patients was obtained from the diabetes database. All
individuals were seen three monthly in clinic. Records of glycosylated
haemoglobin (HbA1c), height, weight, body mass index (BMI), systolic (SBP)
and diastolic blood pressures (DBP) were collected at each visit. Information
on number of injections, total daily insulin doses and number of
hypoglycaemic episodes in the previous 3 months was also collected.
The estimation of AER was obtained from three consecutive overnight urine
samples following ISPAD guidelines. For children with prepubertal onset of
diabetes the AER screening was performed annually after 5 years of
diabetes or from the age of 11 years (whichever came first). For those
children diagnosed during or after puberty the AER screening was
performed annually after 2 years of diabetes onset (318).
For this study, adolescents aged above 11 years diagnosed with T1DM
between the years of 1986 and 2000 (n=1058) were initially identified. Those
with T1DM for at least 5 years were selected for this cross-sectional study
(n=620).
All participants were matched by diabetes duration. Participants were
randomly selected without replacement in three study periods based on the
year of AER screening: 1993-1996 (P1, n=169), 1997-2000 (P2, n=238) and
84
2001-2004 (P3, n=213). Hence, subjects allocated in the first period were
not included in the second period or third one; patients allocated to the
second period were not included in the third one. One random AER
screening consisting of three consecutive overnight urine samples was
selected for each participant.
The mean of all HbA1c levels for each subject since diabetes onset was
used to measure long-term metabolic control. Persistent MA was defined as
a minimum of two out of three consecutive urine specimens with AER >= 20
and < 200 g/min. High AER was defined as the mean AER 7.5 g/min
and < 20 g/min. This cut-off was used based on findings that 95th centime
of urinary AER in healthy non-diabetic adolescents have been shown to be
less than 7.5 g/min (53, 252). The mean AER of the three timed overnight
urine collection for each subject was used as a continuous variable for all
statistical analysis.
The number of subjects with severe hypoglycaemic events in the 12 months
preceding the AER screening was used for analysis. Severe hypoglycaemia
was defined as an event in which the child was found semi-conscious or
unconscious (coma/convulsions).
Intense insulin management was defined as 3 insulin injections per day or
pump therapy. Conventional insulin management was defined as 1-2 insulin
injections per day.
Patients and their parents gave informed consent prior to their data being
stored on the diabetes database. Ethics approval for this study was obtained
from the Princess Margaret Hospital Ethics Committee.
5.4.2 Laboratory tests
AER Urine samples were stored at temperatures between + 2 to + 8C. Until
1997, AER was analysed through Randox Microalbumin competitive
enzyme-linked immunosorbent assay (ELISA) using rabbit antibodies to
human albumin (Cat N MA1410), manufactured by Randox Labs Ltd,
Diamond Rd, Crumlin, County Antrim, UK. The inter-assay coefficient of
85
variability (CV) was 8.5% and 8.9% for measurements of 9.7 mg/L and 97.6
mg/L respectively. From 1997 to 1999, the method was changed to
nephelometry on the Boehring Nephelometer Analyser (BNA). The inter-
assay CV was 3.3% and 2.7% at 10.4 mg/L and 91.2 mg/L respectively. In
the changeover, 80 urine samples were analysed by the two assays with
measurements being virtually the same (Randox ELISA = 0.9472
Nephelometer + 1.39, r2=0.9727).
From 1999 the AER method was changed to the Tina-quant Albumin, an
immunoturbidimetric assay using Roche/Hitachi 917. The intra-assay CV
was 2.2% at 38.43 mg/L. The inter-assay CV was 6.4% at 14.15 mg/L and
1.5% at 83.78 mg/L. Sixty-two urine samples with measurements between 0
and 3030 mg/L were analysed by the two assays and highly correlated
(BNA=0.989 x Hitachi 917 – 1.20, r2=0.999).
HbA1c Prior to 1993, HbA1c measurements were performed using a high-
performance liquid chromatography (HPLC) assay. The assay was changed
to Ames DCA 2000 early in 1993, in which HbA1c is assayed by latex
agglutination inhibition using DCA 2000 analyser (Bayer Ltd, Indianapolis,
IN, USA). The inter-assay CV was 4.69% and 2.81% at HbA1c levels of 5%
and 11 % respectively. On the changeover, the first 400 samples were
analysed by both methods and the correlation coefficient was close to 1.
Total cholesterol Non-fasting cholesterol levels were assayed using a
colorimetric assay at 540nm using cholesterol esterase and oxidase as
adapted to the dry slide technology used in the Vitros 500 and 250 chemistry
analysers.
Anthropometric data and blood pressure Height (Harpenden stadiometer)
and weight (electronic weighing scales) were assessed and BMI was
calculated in kg/m2. Height, weight and BMI were transformed in to Z scores
for age and gender based on published standards (319). Measurements of
blood pressure were performed by auscultation with a sphygmomanometer.
Appropriate cuff sizes were chosen ensuring that the cuff bladder length
86
would cover 80% of the circumference of the arm. Blood pressures Z scores
for gender, age and height were computed using published standards (320).
5.4.3 Statistical analysis
Summary statistics are expressed as median [interquartile range (IQR)],
number (%) and mean standard deviation (SD). SPSS version 13.0 (SPSS
for Windows, Rel. 11.0.1.2001. Chicago: SPSS Inc.) was used for statistical
analysis. Kruskal-Wallis test was used to compare continuous variables not
normally distributed across the three study groups (P1, P2 and P3).
One-way ANOVA was used for analysis of continuous variables with normal
distribution. For categorical variables, a chi-square (2) test was performed
to establish the association with the three time periods. Where statistically
significant results were achieved, the difference between individual groups
was assessed using the Student’s t-test or Mann-Whitney test.
Univariate analysis for predictors of high AER and MA was performed using
simple logistic regression. The variables studied were gender, age, age at
diagnosis, diabetes duration, mean HbA1c, total cholesterol, SBP and DBP
Z scores, BMI Z scores, insulin dose (U/kg), insulin management (intense
vs. conventional) and study period.
Multiple logistic regressions was performed to assess the combined effect of
different predictors of the development of MA and high AER. A strong
multicolinearity effect between mean HbA1c and the 3-study periods was
noticed (Pearson correlation –0.64, P<0.001). Therefore, two models were
used to assess the association of multiple variables and the outcome. In the
first model, mean HbA1c was included and the variable study-period was
removed from analysis. In the second model, study-period was included
instead of mean HbA1c, as stated in footnotes of Tables 5.4 and 5.5. A P-
value of <0.05 was considered statistically significant.
87
5.5 Results
5.5.1 Patients’ characteristics
A total of 620 subjects (M=292; F=328) were studied. The overall median
(IQR) age and duration of diabetes were 14.8 years (12.9-17.1) and 6.6
years (5.7-8.2). The median (IQR) age at diagnosis was 8.3 years (5.7-10.7).
Mean HbA1c% SD was 9.4 1.4 and the median (IQR) AER was 3.0
g/min (1.5-5.7).
Duration of diabetes was similar across the three study groups. Group P3
was younger when compared to P1 and P2 and had an earlier onset of
diabetes when compared to P1 but not to P2. The clinical characteristics of
the subjects are summarised in Table 5.1.
88
Table 5.1 Characteristics of T1DM adolescents the three study periods
P1 (93 – 96)
n=169
P2 (97 – 00)
n=238
P3 (01 – 04)
n=213
P value
Gender (M/F) 68/101 a
111/127 113/100 a
Year of Diagnosis 1986 - 1989
1990 - 1994
1995 - 2000
125
44
_
34
194
10
_
57
156
CSII subjects 0 2 (1%) 27 (13%)
Age (years) b 15.5 2.7
15.4 2.9
b 14.6 2.4 0.002
Duration (years) 6.7 (5.8 – 8.0) 6.7 (5.7 – 8.3) 6.6 (5.6 – 8.5) 0.428
Age at onset (years) c 8.5 2.9
8.1 3.6
c 7.6 3.5
0.01
Last HbA1c (%) 9.6 1.7 8.9 1.5 8.4 1.2 <0.001
Mean HbA1c (%) * 10.7 1.1 9.4 1.1 8.5 0.8 <0.001
AER (g/min) 4.2 (2.8 – 7.8) 3.5 (2.4 – 6.5) 2.0 (1.0 – 3.5) <0.001
Total cholesterol
(mmol/L)
4.64 1.04 4.54 1.03 4.38 0.79 0.05
BMI Z score 0.59 0.67 0.64 0.76 0.74 0.79 0.157
Weight Z score 0.55 ± 0.78 0.59 ± 0.82 0.74 ± 0.89 0.06
SBP Z score 0.46 1.13 0.41 0.93 0.07 1.01 <0.001
DBP Z score 0.16 0.74 0.13 0.73 0.00 0.72 0.001
N injections/day 1-2
3-5
157(93%)
12 (7%)
176 (74%)
62 (26%)
100 (47%)
113 (53%)
<0.001
Non-MA
MA
161 (95.3%)
8 (4.7%)
223 (93.7%)
15 (6.3%)
209 (98.1%)
4 (1.9%)
0.06
Low AER
High AER
125 (74%)
44 (26%)
190 (80%)
48 (20%)
191 (90%)
22 (10%)
<0.001
Number (%) subjects with severe
hypoglycaemia (12 months)
9 (5%) 32 (13%) 25 (12%) 0.03
Results are expressed in n (%), mean SD or median (IQR). * Mean of all HbA1c
measurements since the onset of diabetes. CSII, subjects on continuous subcutaneous
89
insulin infusion. a
P1 vs. P3, -square test, P=0.01. b P1 vs. P3, Student’s t test, P=0.001.
c
P1 vs. P3, Student’s t test, P=0.002.
5.5.2 Albumin excretion rate and MA
The proportion of subjects with high AER decreased across the three
periods (Figure 5.1a). There was a declining trend in MA over the three time
points, mainly observed between P2 and P3 (Figure 5.1b).
01 - 0497 - 0093 - 96
STUDY PERIOD
30
25
20
15
10
5
0
% H
IGH
AE
R
01 - 0497 - 0093 - 96
STUDY PERIOD
7
6
5
4
3
2
1
0
% M
ICR
OC
AS
ES
Figure 5.1 Percentage of subjects with high AER (1a) and MA (1b) over the three
study periods
90
To minimise the effect of age differences, subjects were grouped by age in
two-year intervals. The median AER was consistently lower in the third study
period compared to the first two study groups (p<0.01) (Figure 5.2).
>2018-2016-1814-1612-14< 12
Age (years)
5.00
4.00
3.00
2.00
1.00
0.00
Med
ian
AE
R (
mic
/min
)
2001-2004
1993-2000
Study period
Figure 5.2 Median AER by age, comparing P1+ P2 (1993-2000) vs. P3
(2001-2004)
5.5.3 Metabolic control, insulin management and hypoglycaemic
events
Improvements in long-term glycaemic control and glycaemic control on the
day of assessment were noticed across the three groups.
A higher proportion of subjects were intensively treated across the three
periods. The difference was significant both when P2 was compared to P1
(P<0.001) and when P3 was compared to P2 (P<0.001). There was a
parallel increase in the percentage of subjects on continuous subcutaneous
insulin infusion.
A higher number of subjects presented severe hypoglycaemia events across
the three time points but no difference was noticed in the number of subjects
with severe hypoglycaemia between the last two study periods (p=0.35)
(Table 5.1).
91
5.5.4 Blood pressure, cholesterol levels and anthropometric data
There was an overall decrease in SBP and DBP Z scores and total
cholesterol across the three study-groups (Table 1). SBP Z score was lower
in P3 when compared to P1 (mean SD 0.07 1.01 vs. 0.46 1.13,
P=0.001) and to P2 (mean SD 0.07 1.01 vs 0.41 0.93, P<0.001). DBP
Z score was lower in P2 compared to P1 (mean SD -0.13 0.74 vs 0.16
0.74, P<0.001). No differences were observed between P2 and P3.
Total cholesterol was lower when P3 was compared to P2 (mean SD 4.38
0.79 vs 4.64 1.04, P=0.02) and compared to P1 (mean SD 4.38 0.79
vs 4.54 1.02, P=0.01).
No differences were noticed in height, weight and BMI Z scores over the
three periods.
5.5.5 Univariate and multiple logistic regression
The associated risk factors for high AER and persistent MA in the univariate
analysis are shown in Tables 5.2 and 5.3.
Table 5.2 Univariate logistic regression analysis for high AER
Outcome Variable Odd ratio
(95% CI)
P value
High AER
(AER 7.5 g/min
Age (years) 1.19 (1.11 – 1.28) < 0.001
Age at onset (years) 1.13 (1.06 – 1.20) <0.001
Mean HbA1c % 1.44 (1.24 – 1.68) <0.001
SBP Z score 1.24 (1.01 – 1.52) 0.04
Total cholesterol (mmol/L) 1.39 (1.10 – 1.76) 0.005
Study period
1993-1996 vs. 2001-2004
1997-2000 vs. 2001-2001
3.05 (1.75 – 5.35)
2.19 (1.27 – 3.77)
<0.001
0.005
92
Table 5.3 Univariate logistic regression analysis for MA
Outcome Variable Odd ratio
(95% CI)
P value
Microalbuminuria Age (years) 1.27 (1.12 – 1.46) <0.001
Duration (years) 1.24 (1.02 – 1.49) 0.03
Mean HbA1c % 1.43 (1.08 – 1.89) 0.01
SBP Z score 1.46 (1.01 – 2.13) 0.04
DBP Z score 1.77 (1.01 – 3.10) 0.05
Total cholesterol (mmol/L) 1.62 (1.12 – 2.34) 0.01
Study period
1997-2000 vs. 2001-2001
3.51 (1.14 – 10.76)
0.03
In the multivariate analysis for risk factors associated with high/low AER,
older age at diagnosis and mean HbA1c was associated with high AER in
the first model. In the second model when study period was included and
mean HbA1c removed, the most recent study period was an independent
risk factor associated with high AER (Table 5.4).
Table 5.4 Multiple logistic regression analysis for high AER
Outcome Variable Odds Ratio (95% CI) P value
High AER *
(AER 7.5 g/min)
Age at diagnosis (years) 1.13 (1.01 – 1.28) 0.03
Mean HbA1c % 1.42 (1.17 – 1.73) <0.001
High AER **
(AER 7.5 g/min)
Study period
1993 -1996 vs. 2001-
2004
1997-2000 vs. 2001-2004
3.23 (1.66 – 6.23)
2.04 (1.07 – 3.91)
0.001
0.03
* Adjusting for: gender, age at diagnosis, diabetes duration, total cholesterol, SBP and DBP
Z scores and mean HbA1c. **Adjusting for: gender, age at diagnosis, diabetes duration, total
cholesterol, SBP and DBP Z scores and study period.
93
The predictors for MA were older age at diagnosis and longer diabetes
duration both when the first and the second model were applied (Table 5.5).
Table 5.5 Multiple logistic regression analysis for MA
Outcome Variable Odds Ratio (95% CI) P value
Microalbuminuria * Age at diagnosis (years) 1.34 (1.11 – 1.62) 0.002
Duration (years) 1.74 (1.23 – 2.47) 0.002
Microalbuminuria ** Age at diagnosis (years) 1.35 (1.12 – 1.62) 0.002
Duration (years) 1.76 (1.25 – 2.49) 0.001
* Adjusting for gender, age at diagnosis, diabetes duration, SBP and DBP Z scores and
mean HbA1c.** Adjusting for gender, age at diagnosis, diabetes duration, SBP and DBP Z
scores and study period.
94
5.6 Discussion
In this population-based cohort of adolescents with T1DM, we observed a
decline in the median AER in parallel to improvements in metabolic control
between 1993 and 2004. A trend towards a lower prevalence of MA was
noticed across the three study periods, particularly after the year 2000.
In view of the relative small number of MA cases, we analysed the
prevalence of high AER, which has been shown to confer a higher risk of
progression to diabetes nephropathy and to share the same risk
associations as MA (53, 54). A lower prevalence of high AER was seen
across the three periods supporting the finding of a decrease in AER over
time.
We have recently reported a prevalence of 13% of persistent MA in our
population of T1DM children followed prospectively from diagnosis (20). The
present study shows a lower prevalence of MA. However, this analysis
includes a smaller number of participants selected from the whole
population. In addition, it had a cross-sectional design and included one
AER screening (3 overnight samples) randomly selected for each subject
reflecting one single instant in time. As a cross-sectional study, it was less
likely to reflect the true prevalence of MA for the whole population.
Nevertheless, it clearly demonstrated declining trends of AER over time.
Different risk factors have been associated with the development of
microavascular complications among subjects with T1DM. Improvements in
metabolic control have been reported as contributing to the decline in
incidence of severe retinopathy and nephropathy in longitudinal follow-up
studies (35, 264, 311). A close relationship between glycaemic control and
early glomerular morphological changes is observed among young T1DM
subjects (321, 322). Better glycaemic control, as reflected by lower mean
HbA1c, was shown in this cohort across the three periods. Despite the fact
that the observed mean HbA1c was still above the target HbA1c level of
7.0% recommended by the DCCT (310), the decrease in the prevalence of
both high AER and MA suggests that minor changes in glycaemic control
95
may affect AER. In addition, an increase in mean HbA1c was an
independent risk factor associated with high AER adjusting for different
covariates.
All participants were matched by diabetes duration but subjects in the last
study period were younger and had an earlier onset of diabetes. These
factors could be confounders for the lower prevalence of high AER and MA
observed in the last study period. However, the observation of a significant
decrease in median AER between the first two study periods and the last
one, when subjects were grouped by age in two-year intervals, gives support
to our findings of a decreased prevalence of high AER and MA specially
after the year 2000.
In spite of carefully matching the three study groups by diabetes duration
and selecting only adolescents for this study, our data showed that older age
at diagnosis and longer duration of diabetes were still independently
associated with MA. Others have also reported that children that develop
diabetes at younger ages have an increased time to the development of
incipient nephropathy compared to those diagnosed in pubertal years.
Postpubertal years of diabetes contribute more heavily to the risk of
developing DN (8, 9, 210, 317). The lack of detailed information on puberty
status for the whole study group did not allow us to analyse closely the effect
of different stages of puberty as risk factors associated with the development
of high AER and MA. The endocrine changes associated with puberty,
particularly in its later stages, lead to an accelerated process of early kidney
damage in diabetes and have been associated with deterioration in
glycaemic control during the pubertal years (221, 225, 323, 324).
Changes in the AER assays occurred three times over the study period of 12
years, which might have interfered with the MA screening. However, at each
changeover, methods were carefully validated with correlation coefficients
close to 1 and therefore were virtually identical in measuring AER.
Consequently, the declining trends observed in this study are unlikely to
reflect eventual fluctuations of AER secondary to changes in AER assays.
96
Concomitantly to the decrease in mean HbA1c and median AER, insulin
therapy was intensified over time with a higher proportion of adolescents
intensively managed. Intensified insulin regimens have not always been
described as having an impact on metabolic control among adolescents with
diabetes and have been associated with increments in insulin dosage and
greater weight gain particularly in girls (325). Mohzin et al showed a decline
in the prevalence of retinopathy and MA among T1DM adolescents over
time in parallel to an increase in intensified insulin management but the
authors were not able to show changes in metabolic control (326).
Of note, our study was able to show improvements in metabolic control but
there was no evidence of increase either in weight Z scores or in BMI Z
scores across the three study periods. Insulin dosage only increased
between the first and second study-groups but not between the last two
periods.
Hypoglycaemia is the major obstacle to tight metabolic control in T1DM
children and adolescents (327). An increasing number of subjects with
severe hypoglycaemic events were seen between the first and second study
periods but no changes were observed between the second and third
periods despite improvements in metabolic control. These findings are in
accordance to previous reports in our population showing an increased
incidence of severe hypoglycaemia over the last decade but with a plateau
in the incidence rates after 1997 (328). This plateau may have been
achieved as a result of improved skills of the diabetes carers in preventing
hypoglycaemia and the introduction of better systems of insulin delivery such
as the use of continuous subcutaneous insulin infusion which is known to
reduce the risk of hypoglycaemic events (329).
Elevated BP and increased levels of AER have previously been described
being associated with the onset and progression of MA in children and
adolescents with T1DM (268, 298). A decrease in both SBP and DBP Z
scores was seen in parallel to the decrease in AER rates over time. This
finding gives credit to the hypothesis that changes in SBP and DBP occur
simultaneously with changes in AER and illustrates that improvements in
97
metabolic control may have an impact not only on AER but also on BP levels
early in the course of diabetes (227, 286). It also supports the finding of a
true decline on AER over time because of changes in diabetes management
and unlikely to be an artefact of modifications on AER assays.
In conclusion, our results suggest a decline in the prevalence of high AER
and MA in a population-based cohort of adolescents with T1DM over time.
This decline appears to be directly related to improvements in metabolic
control and changes in diabetes management in the last decade but further
longitudinal evaluation is recommended.
98
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6.1 PREFACE This chapter was published and the full PDF version is
presented in Appendix C
100
6.2 Abstract
Aim. We examined genetic polymorphisms in the renin-angiotensin system
(RAS) coding for angiotensin-converting enzyme (ACE) insertion/deletion
(I/D), for angiotensinogen (AGT) M235T and for angiotensin II receptor type
1(AGTR1) A1166C as predictors for the development of MA (MA) in children
with T1DM.
Methods. 453 T1DM children (215 M, 238 F), median (IQR) age 16.7 yrs
(13.9 – 18.3), diabetes duration 6.9 yrs (3.3 – 10.8) and age at diagnosis 9.1
yrs (5.8 – 11.8) were followed prospectively from diagnosis until the
development of MA (2 out of 3 consecutive overnight urine samples with
AER 20 and < 200 g/min). Kaplan-Meier survival curves and Cox
proportional multivariate model estimated the probability of developing MA
and the relative risk for MA among different variables.
Results. MA developed in 41 (9.1%) subjects. The frequencies of the
genotypes were ACE-II 112 (25%), ACE-ID 221 (49%) and ACE-DD 117
(26%) (n=450); AGT-MM 144 (32%), AGT-MT 231 (51%) and AGT-TT 77
(17%) (n=452); AGTR1-AA 211 (47%), AGTR1-AC 204 (45%) and AGTR1-
CC 37 (8%) (n=452). The cumulative risk for the development of MA was
higher in ACE-DD vs. ACE-ID/II groups (log rank test, P=0.05) and a trend
was noticed when AGT-TT was compared to AGT-MT/MM groups (log rank
test, P=0.08). The AGT-TT polymorphism conferred a 4-fold increased risk
for MA compared to AGT-MM/MT (HR 3.8, 95% CI 1.43 – 10.3, P= 0.008).
Interpretation. Our findings suggest that RAS gene polymorphism at AGT
M235T is a strong predictor for early MA in young T1DM subjects.
101
6.3 I Introduction
DN is a common complication in T1DM and is characterised by the
development of proteinuria, hypertension and decline in renal function.
Persistent MA is a predictor of overt nephropathy and an independent risk
factor for cardiovascular disease and early mortality in subjects with T1DM
(4, 5). In T1DM children the presence of MA in the first decade of disease
persists and progresses in approximately two thirds of T1DM subjects (330).
We have recently observed a cumulative risk for MA of 16% after 10 years of
diabetes duration in our paediatric population of T1DM. The main predictors
in this study were poor metabolic control, onset of puberty, duration of
diabetes and age at diagnosis (317).
Improvements in glycaemic control achieved through intensive management
reduce the development and progression of microvascular complications in
young T1DM subjects (39). However long-term follow-up studies show that
despite poor glycaemic control some subjects do not develop DN (254). In
addition to familial clustering, these findings imply hereditary factors may be
relevant in the aetiology of DN (144).
The renin-angiotensin system (RAS) is important in blood pressure
homeostasis and involved in the pathogenesis of arterial hypertension (145).
Genetic variants of its major components, angiotensinogen (AGT),
angiotensin I-converting enzyme (ACE) and angiotensin II receptor type 1
(AGTR1) have been implicated in the aetiology of hypertension, coronary
artery disease, myocardial infarction and non-diabetic renal disease and
therefore could be considered candidate genes involved in the pathogenesis
of diabetic renal complication (152, 154-160). An insertion/deletion of a 287
base pair Alu sequence in intron 16 of the ACE gene on chromosome 17q23
(ACE I/D) accounts for approximately 50% of the variability of serum ACE
levels between individuals. Subjects homozygous for the D allele exhibit fifty
per cent higher ACE levels than those homozygous for the I allele (161).
Associations between AGT gene polymorphism, plasma AGT levels and
essential hypertension have been described (174, 331). The AGTR1 is a
membrane-bound, G protein-coupled receptor that mediates the
102
vasoconstrictive effects of angiotensin II. The AGTR1 A1166C polymorphism
has been associated with essential hypertension, increased left ventricular
mass and myocardial infarction (152) and is reported as a predictor for renal
injury in the presence of inadequate glucose control in adults with T1DM
(195, 332).
We hypothesized that genetic variations in the RAS contribute to the
development of persistent MA in children with T1DM. We examined specific
gene polymorphisms coding for ACE insertion/deletion (I/D), for AGT M235T
(rs5186) and for AGTR1 A1166C (rs11568053) in children with T1DM
followed from diagnosis.
6.4 Patients and methods
The Endocrinology and Diabetes service at Princess Margaret Hospital for
Children is the referral centre for subjects diagnosed with T1DM under the
age of 16 years in the state of Western Australia. Cases of T1DM have been
confirmed by autoantibody testing. Clinical information has been collected
prospectively from all subjects since diabetes onset and data has been
stored in the Western Australia Children’s Diabetes database since 1987.
Four hundred and fifty-three Caucasian children with T1DM (215 males, 238
females) with median age of 16.8 years (IQR 13.9 – 18.4) and median
duration of diabetes of 6.9 years (IQR 3.3 – 10.8) were randomly selected
from subjects regularly attending the diabetes outpatient clinic at our
institute. Case ascertainment for T1DM children diagnosed under the age of
16 years is 99% (23). Children with secondary diabetes, T2DM and with
other causes of nephropathy were excluded from this study. None of the
selected participants has had any previous treatment with ACE inhibitors.
Informed consent was obtained from parents prior to the child’s data being
stored on the diabetes database. Ethical approval for this study was
obtained from the Princess Margaret Hospital Ethics Committee.
103
6.4.1 Design and procedures
Participants were seen once every three months in clinic. Records of
glycated haemoglobin (HbA1c), height, weight, systolic (SBP) and diastolic
blood pressures (DBP) and insulin regimen were collected at each visit.
In children with prepubertal onset of diabetes, the estimation of AER was
obtained from three consecutive overnight urine samples performed
annually after 5 years of diabetes onset or at the age of 11 years. In those
children with pubertal onset of diabetes, AER screening was performed
annually after 2 years of diabetes onset as recommended by the
International Society for Pediatric and Adolescent Diabetes guidelines
(ISPAD). Persistent MA was defined as the presence of a minimum of two
out of three consecutive urine specimens with AER >= 20 and < 200 g/min
(333).
All subjects were followed from diagnosis until the development of persistent
MA or until the end of the study in July 2005. The mean HbA1c since
diabetes onset until the end of the study was used as an indication of long-
term metabolic control. Information on anthropometric data, BP, lipids and
insulin dose from the last visit were used for statistical analysis. All
participants were screened for the ACE I/D, AGT M235T and AGTR1
A1166C polymorphisms.
6.4.2 Laboratory tests
Urine samples were stored at temperatures between +2 to +8C. Until 1997,
AER was analysed through Randox Microalbumin competitive enzyme-
linked immunosorbent assay (ELISA) using rabbit antibodies to human
albumin (Cat N MA1410), manufactured by Randox Labs Ltd, Diamond Rd,
Crumlin, County Antrim, UK. The inter-assay coefficient of variability (CV)
was 8.5% and 8.9% for measurements of 9.7 mg/L and 97.6 mg/L
respectively. From 1997 to 1999, the method was changed to nephelometry
on the Boehring Nephelometer Analyser (BNA). The inter-assay CV was
3.3% and 2.7% at 10.4 mg/L and 91.2 mg/L respectively. During the
transition period, measurements were made on the same samples by the
two assays and the two methods were compared and validated (ELISA=
104
0.9472 x BNA +1.39, r2=0.9727). From 1999 the AER method was changed
to the Tina-quant Albumin, an immunoturbidimetric assay using
Roche/Hitachi 917. The intra-assay CV was 2.2% at 38.43 mg/L. The inter-
assay CV was 6.4% at 14.15 mg/L and 1.5% at 83.78 mg/L. Comparison
between the two methods was made and validated (BNA= 0.989 x Hitachi
917 - 1.20, r2=0.999).
Prior to 1993, HbA1c measurements were performed using a high-
performance liquid chromatography (HPLC) assay. The assay was changed
to Ames DCA 2000 early in 1993 in which HbA1c is assayed by latex
agglutination inhibition using DCA 2000 analyser (Bayer Ltd, Indianapolis,
IN, USA). The inter-assay CV was 4.69% and 2.81% at HbA1c levels of 5%
and 11%. Both methods have been DCCT standardised.
Cholesterol levels were assayed using a colorimetric assay at 540nm using
cholesterol esterase and oxidase as adapted to the dry slide technology
used in the Vitros 500 and 250 chemistry analysers.
Height (Harpenden stadiometer), weight (electronic weighing scales) and
BMI (kg/m2) were transformed to age and gender adjusted Z scores (319).
Blood pressure, measured after 5 minutes rest through auscultation with a
sphygmomanometer, was transformed to gender, age and height adjusted Z
scores (334).
6.4.3 Genotyping
Blood was collected into EDTA blood tubes and DNA was extracted from the
buffy coats using a salting out method (335). The 287bp Alu insertion in ACE
was genotyped directly by polymerase chain reaction (PCR) amplification,
followed by separation on a 2% agarose gel. The insertion allele was
identified by the presence of a 480bp band, the deletion allele by a 193bp
band (154). Samples that were identified as being DD homozygous were
confirmed using an insertion specific forward primer (5’–
TTTGAGACGGAGTCTCGCTC–3’). The DD genotype was confirmed by the
absence of PCR product.
The M235T AGT polymorphism was genotyped using a tetra-primer ARMS
assay (336) with forward outer primer 5’–
AGTCCTAGGGCCAGAGCCAGCAGAGAGG–3’, reverse outer primer 5’–
105
CCGTTTGTGCAGGGCCTGGCTCTCTATA–3’, forward inner primer 5’–
CAGGGTGCTGTCCACACTGGCTCCGA–3’, reverse inner primer 5’-
GACAGGATGGAAGACTGGCTGCTCCCTTAC–3’. The T allele was
identified by the presence of a 166bp band, the C allele by a 121bp band.
PCR products were separated on a 2% agarose gel.
The A1166C polymorphism in AGTR1 was identified using mutagenically
separated-PCR, with A allele specific forward primer 5’–
TCTGCAGCACTTCACTACCAAATGAGTA–3’, C allele specific forward
primer 5’-
AAGGAGCAAGAGAACATTCCCTTGCAGCACTTCACTACCAAATGAACC–
3’, reverse primer 5’–TCAGAGCTTTAGAAAAGTCGG–3’. A 3% agarose gel
was used to separate the PCR products. The A allele specific product was
indicated by the presence of a 97bp band, the C allele specific product by a
117bp band.
6.4.4 Statistical analysis
SPSS version 13.0 (SPSS for Windows, Rel. 11.0.1.2001. Chicago: SPSS
Inc.) and SimHaP (337) version Beta 2.1 were used for statistical analysis.
Results were reported as mean standard deviation (SD); or median and
interquartile ranges (IQR) when distributions were skewed. Mean AER was
log-transformed. Groups were compared by the use of the chi-square (2)
test for categorical variables. Differences in continuous variables were
evaluated using ANOVA or Student’s t tests if normally distributed, or using
Kruskal-Wallis or Mann-Whitney U tests if distributions were skewed.
Kaplan-Meier survival curves estimated the probability for the development
of persistent MA. Duration of diabetes was used as the time variable.
Comparisons between the curves were performed using the log-rank test.
Genotypes at each locus were tested for deviations from Hardy-Weinberg
equilibrium separately in individuals with and without MA. A Cox regression
method was used to calculate the hazard ratios and 95% confidence
intervals for genotypes at the ACE, AGT and AGTR1 loci under additive,
dominant and recessive models adjusting for gender, age at diagnosis,
mean HbA1c, total cholesterol, insulin dose (U/kg), BMI Z score, SBP Z
score and DBP Z score.
106
Genotypic models were tested by recoding genotypes with the most
common genotype coded as zero for the baseline. Under additive models,
heterozygous were coded as 1 and homozygous for the rarer allele as 2.
Under dominant models, both the heterozygous and homozygous for the
rarer allele were coded as 1 whilst under recessive models heterozygous
were also coded as zero and homozygous for the rarer allele were coded as
1. The threshold for declaring statistical significance was set at alpha=0.05.
107
6.5 Results
Forty-one subjects developed persistent MA (9.1%). The overall cumulative
probability for persistent MA in this cohort was 11% after 10 years of
diabetes duration.(data not showed) Subjects in the MA group were younger
at diagnosis, had poorer metabolic control, required higher insulin doses and
had higher SBP and DBP Z scores and higher total cholesterol levels. There
was a trend for subjects with MA to have a longer duration of diabetes
(Table 6.1).
Table 6.1 Clinical characteristics of participants
Results expressed as median ± SD and median (Interquartie range).
The distribution of ACE, AGT and AGTR1 genotypes in this cohort of T1DM
children with and without MA was consistent with Hardy-Weinberg
equilibrium (Table 2). There were no significant differences in the genotype
frequencies between subjects with and without MA under additive, dominant
or recessive models. The allele frequencies of ACE, AGT and AGTR1
genotype were similar to previous data reported in other studies both in non-
diabetic and diabetic subjects (Table 6.2) (195, 338, 339). The distribution
of the three genotypes studied was similar between genders.
108
Table 6.2 ACE, AGT and AGTR1 genotype distribution of participants
There was no difference among the ACE genotypes in terms of age at
diagnosis, duration of diabetes, mean HbA1c, log mean AER, SBP and DBP
Z scores or insulin dose (U/kg) in any of the models. Subjects identified as
ACE-DD had higher total cholesterol levels compared to ACE-II (mean SD
4.6 1.1 vs. 4.2 0.9 mmol/L, P=0.03) and higher BMI Z scores (mean
SD 0.84 0.67 vs. 0.55 0.90, P=0.02) but no differences between ACE-
DD and ACE-ID groups in the additive model suggesting a recessive effect.
However when ACE-DD and ACE-ID+II were compared, no differences were
observed in total cholesterol and BMI Z scores between the two groups.
Similarly, we found no differences in age at diagnosis, duration of diabetes,
mean HbA1c, log mean AER, SBP and DBP Z scores, BMI Z scores, insulin
dose (U/kg) and total cholesterol across the three AGT and AGTR1
genotypes under additive, dominant and recessive models. For the ACE
genotype, the Kaplan-Meier survival curves for duration of diabetes to the
development of MA showed a higher cumulative probability for persistent MA
for subjects ACE-DD in comparison to ACE-ID/II implying a recessive model
of action (log-rank test, P=0.05) (Figure 6.1). Under the recessive model,
thirty per cent of subjects homozygous for the ACE-D allele developed MA
after 12 years of diabetes while only 15% of those genotyped as ACE-ID/II
109
developed MA after the same duration of follow-up. There was no difference
in the cumulative risk for persistent MA between the ACE genotypes under
the additive or dominant models.
Figure 6.1 Kaplan-Meier estimation for the development of persistent MA
according to ACE genotype in the recessive model (DD versus ID/II
There was a trend towards statistical significance of higher risk for MA for
subjects homozygous for the T allele of the AGT M235T polymorphism
under a recessive model (log-rank test, P=0.08) (Figure 6.2). Dominant and
additive models for AGT M235T showed no significant effect in the
cumulative probability for the appearance of MA. None of the models applied
to the AGTR1 genotype showed a significant effect on the cumulative risk for
MA.
110
Figure 6.2 Kaplan-Meier estimation for the development of persistent MA
according to AGT genotype in the recessive model (TT versus MT/MM).
The multivariate Cox regression showed that subjects carrying two risk
alleles for the AGT polymorphism (AGT-TT) had a 4-fold increase risk for
persistent MA (Table 6.3). Epistatic interactions between loci were
investigated but no significant interactions were found. There was no
interaction between ACE, AGT or AGTR1 polymorphisms and gender or
long-term glycaemic control. In addition, we have analysed the interaction
between different genotypes, which lacked statistical significance in this
study. There was a positive correlation between insulin dose (U/kg) and
mean HbA1c (Pearson’s correlation, P<0.001) but no significant effect was
found between the interaction of these variables and persistent MA.
111
Table 6.3 Cox regression multivariate analysis on the risk of persistent MA
in T1DM children
112
6.6 Discussion
We identified an association between AGT M235T polymorphism and the
development of persistent MA in children with T1DM. This is the first
longitudinal study in an ethnically large and homogenous population-based
sample of T1DM children followed prospectively from diagnosis that has
demonstrated an increase risk for persistent MA, an early sign of DN and a
marker for cardiovascular disease, among subjects that are homozygous for
AGT T235. Although the relatively small number of subjects who developed
persistent MA (41/453) and the short follow-up time (median 6.9 years) need
to be carefully considered when these findings are interpreted, the 4-fold
increased risk for MA with the AGT-TT genotype strongly indicates an
association between polymorphisms in the RAS and the development of
incipient nephropathy in young T1DM. Subjects that developed MA had a
poorer glycaemic control and were older at diagnosis. There was a trend
towards a longer duration of diabetes among subjects with MA. Of note, in
this cohort, glycaemic control was not a predictor for MA in the multivariate
analysis. However, a strong correlation between mean HbA1c and insulin
dose was observed and a higher insulin dose increased by almost 3 times
the risk for MA. In addition, the overall glycaemic control for the total cohort
was above the recommendations from the DCCT (DCCT 1994) guidelines.
Doria et al have reported a synergistic effect of genetic polymorphisms at the
RAS and poor glycaemic control on risk of nephropathy in IDDM (195) and it
is likely that specific DNA sequence differences at the RAS genes may
modify the already existent noxious effects of hyperglycaemia on the kidney.
AGT is the only precursor of angiotensin II, a vasoconstrictor and growth
factor implicated in the development of glomerulosclerosis and mesangial
cell hypertrophy (172). Systemic and glomerular hypertension play a role in
the pathogenesis of DN (340-342). Cleavage of angiotensinogen by renin is
the rate-limiting step in the activation of the RAS and molecular variants of
the AGT gene, M235T in particular, have been shown to correlate with
higher plasma angiotensinogen levels and to be associated with essential
hypertension and cardiovascular disease (173, 174, 343). Some have found
that differences between genders in the genotype frequency confer different
113
risk to DN for males and females (180), our study could not replicate these
findings and similar genotype distribution was observed between genders.
It seems unlikely that the 4-fold increase risk for persistent MA conferred by
the AGT-TT genotype is exclusively mediated by systemic hypertension as
the multivariate analysis showed that AGT T235 was an independent
predictor for incipient nephropathy, adjusting for systolic and diastolic blood
pressures. Although there was a trend in SBP Z score to be an independent
predictor for MA, there was no significant difference in SBP or DBP Z scores
across the three AGT genotypes for the whole group or for the MA and non-
MA groups, individually. However, changes in 24-hour blood pressure have
been associated with high levels of AER (286) and with different ACE
genotypes (170). Thus it is possible that minor blood pressure abnormalities
not detected as a clinical BP measurement could at least in part mediate the
relationship between AGT T235M polymorphism and the development of
persistent MA.
In adults with T1DM, reports on the association of AGT gene polymorphisms
and the development of nephropathy show discrepant results mainly due to
differences in study design, study population and measured outcomes.
Some have found the TT genotype of the AGT M235T polymorphism to be
more common among subjects with overt nephropathy and persistent MA
(177, 344) while others have failed to reproduce the same results (183, 184)
but described an association between higher blood pressure among AGT-TT
subjects with DN (183). More recently, a Dutch group found the T allele to be
associated with an increased risk of elevated AER but only when interaction
with the D allele of the ACE I/D polymorphism was considered (179). A
family-based study involving diabetic subjects and their parents found that
the T allele of the M235T polymorphism was transmitted preferentially to
those with the most severe manifestation of nephropathy, end-stage renal
disease (345).
In T1DM children, there is little information on the association of AGT
polymorphism and persistent MA. Most studies in the paediatric population
have a cross-sectional design and focus on the association between ACE
genotype, nephropathy and BP abnormalities (170, 171, 338). Barkai et al
found the DD genotype to be associated with higher diastolic BP in
114
normoalbuminuric children with T1DM (170) while Pavlovic at al described
nocturnal BP abnormalities in children homozygous for the ACE-I allele
(338) but reported no association between I/D polymorphism and
nephropathy (171).
The higher cumulative risk for persistent MA found in ACE-DD subjects is in
agreement with most reports in the literature in which a causal relationship
between ACE gene function and DN in both type 1 and type 2 diabetes
mellitus is described (166, 169). In our study, there was no difference in SBP
or DBP across the three ACE genotypes neither for the whole group nor for
the MA and non-MA groups. Nevertheless we found an increase in total
cholesterol and BMI Z scores among those homozygous for the ACE-D
allele suggesting an association between the ACE polymorphism and lipid
profiles as probable contributors to cardiovascular disease in children with
T1DM(346, 347).
Finally, there was no significant association between the AGTR1 gene
A1166C polymorphism and the development of persistent MA. Although
some have reported a synergistic effect of AGTR1 genotype and poor
glycaemic control on the risk of DN (195) others failed to reproduce these
results in subjects with T1DM (348, 349).
In conclusion, our data gives evidence that genetic variability at the RAS, in
particular the AGT 235T allele, is a predictor for persistent MA in the T1DM
paediatric population. These findings provide a potential tool for identifying a
subgroup of children who may benefit from strategies targeted to early
prevention of DN.
6.7 Acknowledgement
This study was funded by the School of Paediatrics and Child Health, the
University of Western Australia, 2004 Channel Seven Telethon Grant
awarded to Professor CSY Choong.
115
CCHHAAPPTTEERR SSEEVVEENN
116
CCHHAAPPTTEERR 77 GGEENNEERRAALL DDIISSCCUUSSSSIIOONN
77..11 SSUUMMMMAARRYY &&CCOONNCCLLUUSSIIOONNSS
Although improvements in glycaemic control in T1DM adolescents reduce
the risk of appearance and progression of DN (350), MA remains the best
predictive marker for future development of overt nephropathy (351) and is
an independent risk factor for the development of cardiovascular disease
and early mortality in T1DM (3, 4).
Identifying children and adolescents at greatest risk for developing MA,
provides a unique opportunity for selecting individuals for early intervention.
The studies comprising this thesis have identified relevant clinical and
genetic predictors for the development of MA in a large population-based
cohort of children and adolescents with T1DM. These markers allow
selection of an at-risk group of children in whom intervention strategies
aimed at reducing the rate of micro and macrovascular long-term
complications can be trialled.
In the first study, outlined in Chapter 3, the natural history of MA was
examined in almost a thousand T1DM children followed longitudinally for a
mean duration of diabetes of 7.6 years. The overall prevalence of MA was
13%, similar to previous rates reported in the paediatric population (8, 210).
The cumulative incidence after 10 years of diabetes duration was 16%. The
major determinants for the development of MA were the onset of puberty,
older age at diagnosis and higher mean HbA1c levels since diagnosis. We
demonstrated that the effect of diabetes duration on the risk of MA was not
constant over time. Children diagnosed with T1DM after puberty had a
shorter time until the appearance of MA, shown as higher total incidence
density of MA, compared to the younger age-at-onset groups. These
findings are consistent with the hypothesis that the effect diabetes duration
117
before and after puberty is non-linear in relation to the appearance of MA.
Similarly, Donaghue et al found a delay in the onset of MA and retinopathy
in children with longer prepubertal duration (217). However, it is important to
highlight that in the current study, the post-pubertal incidence of MA among
the young age-at-onset group was higher when compared with the older
age-onset groups. Our results indicate that the relative protection from MA
observed in subjects with pre-pubertal onset of diabetes is overcome by a
prolonged duration of diabetes and glycaemic exposure once puberty starts.
These findings are in agreement with the Berlin Retinopathy Study in which,
for the outcome of incipient retinopathy, the median post-pubertal duration
was shorter by 3 years in those with pre-pubertal onset of diabetes (211);
and with the Oxford Regional Prospective Study (ORPS) group, which
reported a strong contribution of prepubertal duration of diabetes and
hyperglycaemia to the appearance of postpubertal MA (210).
The effect of BP on the development of MA was studied in Chapter 4.
Elevated BP has been reported in patients with T1DM monitored with 24-
hour ABP but it is unclear whether this elevation precedes the appearance
of MA or is concomitant to its development (245, 299, 300). We addressed
this question by analysing the relationship between changes in AER and 24-
hour ABP in a cohort of almost 80 normoalbuminuric and normotensive
T1DM children. We were able to demonstrate that changes in 24-hour ABP
preceded the onset of MA. Children with borderline AER (AER 7.0-20
μg/min) had higher 24-hour ABP when compared to those with
normoalbuminuria. After adjusting for age, duration of diabetes, BMI,
gender and glycaemic control, subjects with borderline AER had higher
systolic and diastolic BP when compared with the normoalbuminuric group.
Our results support the hypothesis that the elevation in systemic BP parallels
the rise in AER and that these changes are detectable prior to development
of persistent MA. The ORPS group also found that the onset of MA was
associated with elevations in systolic and diastolic BP, measured in a clinical
setting, in a large cohort of T1DM children followed longitudinally (227).
Hence, we concluded from Chapter 4 that early changes in SBP and DBP
118
occur prior to the development of MA; and that assessing 24-hour ABP is a
sensitive screening tool that could be used to identify T1DM children that
would benefit from intervention with antihypertensive agents.
In Chapter 5, we explored the changes over time in the prevalence of MA
and of borderline AER in a population-based cohort of 620 T1DM
adolescents screened for DN between the years of 1993 and 2004. Although
a secular decline in the incidence of DN has been reported among T1DM
patients over the past years in some western countries (264, 311), results
are controversial and others have found no trend toward a decrease in DN
despite evidence of better glycaemic control (312, 313). In a report from
Amin et al, the prevalence of MA was unchanged in a UK based incipient
cohort of T1DM children diagnosed from 1986 to 1996 despite
improvements in glycaemic control (352). In our study, we showed a decline
in the prevalence of incipient DN and borderline AER, which appeared to be
directly related to a decrease in mean HbA1c and to a more intensified
insulin therapy regimen. In addition, we noticed a similar decline in both
systolic and diastolic BP along with the changes in AER over time. Others
have described a decline in the prevalence of retinopathy and MA among
T1DM children over time in parallel to a more intensified diabetes
management but were not able to show improvements in glycaemic control
(326). Intensified insulin regimens have been reported in association with
greater weight gain (325) and hypoglycaemia is still a major obstacle in
achieving a better glycaemic control among T1DM children and adolescents
(327). In our study, despite improvements in glycaemic control, there was
no increase in BMI Z scores across the study periods. In addition, although
the prevalence of individuals with severe hypoglycaemia was increased
between the first and second study-periods, a plateau was observed after
1997 as previously shown by our group (328). In summary, the decline in the
prevalence of incipient DN occurred concomitantly with improvements in
metabolic control, to a decline BP Z scores and to a more intensified
diabetes management.
119
In Chapter 6, we studied the relationship between specific genetic variants
in the RAS and the development of incipient DN. We investigated three gene
polymorphisms coding for ACE I/D, AGT M235T and AGTR1 A1166C in 465
T1DM children followed from diagnosis for a median of 6.9 years. The
cumulative risk for persistent MA was higher for subjects ACE-DD in
comparison to ACE-ID/II. After 12 years of diabetes duration 30% of subjects
genotyped ACE-DD developed persistent MA compared to only 15% of
those ACE-ID/II. Our findings support a casual relationship between ACE
gene function and the development of DN which has also been confirmed by
a meta-analysis of several studies comprising almost 15,000 T1DM and
T2DM subjects between 1994 and 2004 (166). In adults with T1DM,
discrepant results in relation to the association between AGT gene
polymorphisms and the risk for DN have been reported (184, 344). In T1DM
children, there is limited available information on the effect of AGT
polymorphism and the development of MA. Some have reported its
relationship with 24-hour BP changes in the T1DM paediatric population
(338) but most studies in the paediatric group focus on the association
between ACE genotype and DN in T1DM children (170, 171). We were able
to demonstrate that T1DM children homozygous for the T allele at the AGT
M235T gene have a four-fold increased risk for persistent MA; and that this
effect was independent of changes in systolic or diastolic BP Z scores.
Hence, our data give evidence to the hypothesis that genetic variants at the
RAS, particularly the presence of the AGT 235T allele, are predictors for
persistent MA and can be identifiable early in the course of diabetes.
77..22 LLIIMMIITTAATTIIOONNSS
Although this thesis has contributed to a better understanding of the natural
history of MA, and of the clinical and genetic predictors for the development
of incipient DN in T1DM children, a number of limitations must be
acknowledged.
120
Firstly, identifying children at-risk of incipient DN based on the outcome of
the first MA event is not fully accurate as MA will regress in around 50% of
adolescents by the end of puberty; and a smaller proportion of these
subjects will progress to overt nephropathy (330). In Study I, we reported
that almost 50% of our MA cases regressed and approximately 35% of those
with one episode of MA had a second episode detected at least 6 months
later. However, the finding of increasing rates of AER identified as early as
one year from diagnosis, has been associated with increased risk of DN in
childhood T1DM (298). Moreover, recent evidence suggests that higher AER
in the upper tertile of the normal range strongly predicts those children who
go on to develop persistent MA (353).
In addition, although puberty was clearly a strong predictor for MA, the lack
of detailed information on puberty status for all participants did not allow an
analysis of the effect of different pubertal stages in the development of MA.
By using the chronologic age of 11 years as cut off for definition of onset of
puberty likely overestimated the effect of onset of puberty as an independent
predictor for MA. Neverhtless, the auhors have analysed the data using
older ages of 12 and 13 years for onset of puberty and the effect was
maintained (data not showed).
Although involving a complete cohort in Study I, we were unable to
document accurately information on other potential predictors for the
development of MA such as the effect of the lipoprotein profile or the
presence of inflammatory markers as predictors for the development of MA.
Hyperlipidaemia has been reported among adolescents with T1DM (226,
354). There is emerging data supporting the use of lowering lipid agents in
T1DM adults with MA in preventing cardiovascular events (250).
Inflammation appears to be involved in the pathogenesis of both macro and
microvascular complications. Inflammation occurs in the vasculature as a
response to lipid oxidation. Various others risk factors such as hypertension
and diabetes are amplified by the effects of oxidized low-density-lipoprotein
cholesterol initiating a chronic inflammatory reaction, which is associated
with increased risk of cardiovascular disease (355). Elevated CRP
concentrations have been found in association with increasing HbA1c
121
suggesting a link between glycaemic control and systemic inflammation in
people with established diabetes (356). Low-grade inflammatory markers are
associated with DN in T1DM patients (357) and serum inflammatory markers
are elevated in subjects with severe DR (358). Therefore, the assessment of
inflammatory state would have provided a more complete picture of the
relative contribution of various factors to MA.
Due to constraints of a cross-sectional study design and a relatively small
group of children with T1DM involved in Study II, interpretation of results
should be done with caution. We were able to identify an effect of increasing
AER on both systolic and diastolic BP by stratifying the patients according to
AER in three normal categories. However, although our findings indicate a
simultaneous rise of BP and AER, blood pressure assessment of these
patients was measured in mmHg and are not reported as Z
scores/percentieles after appropriate adjustments for height and gender
which has been recommended in the pediatric population (359).
Abnormal SBP and DBP dipping has been previously reported in association
with albuminuria in adolescents (305). In our study, the lack of association
between abnormal BP dipping status and mean AER or glycaemic control
may be due to limited number of studied children. The study also have
limitations as power calculation indicated that a minimum of 80 paticipants
should have been recruited for detecting 50% of changes between dippers
and non-dippers.. In addition, from the studied participants, only 9% (7/75
participants) presented with high AER. Only a longitudinal evaluation of
these participants in would clarify whether these changes in BP precede
those in AER.
As discussed in Study III, in spite of carefully matching subjects of the three
study–periods by diabetes duration and selecting only adolescents,
participants in the last study period were younger and had earlier onset of
diabetes, factors that could be confounders for the lower prevalence of MA
or borderline AER observed in the last study-period. Similar to the
discussion in Study I, the lack of information on different stages of puberty
122
did not allow us to assess the risk of each pubertal stage in the development
of MA or borderline MA.
Study IV, which addressed the effect of genetic variants in the RAS as
predictors for the development of MA, has a number of limitations and these
were detailed in Chapter 6. Only a small proportion of adolescents (41 of
453) developed MA over a short period of follow-up time (median 6.9 years).
We were unable to measure serum angiotensinogen levels in order to
correlate it to the variants at the AGT gene. Higher serum levels of
angiotensinogen are associated with polymorphisms at the AGT gene,
particularly with M235T, and are also associated with the development of
essential hypertension and cardiovascular disease (173). Additionally, we
failed to demonstrate the effects conferred by the AGT-TT genotype in the
development of MA being exclusively mediated by systemic hypertension as
no changes in systolic or diastolic BP were observed across the three AGT
genotypes, when measured in the clinical setting. The possibility of minor BP
abnormalities detected through more sensitive methods such as the use of
24-hour ABP could not be excluded from this study.
Similar to the lack of angiotensinogen serum measurements, we were
unable to correlate the ACE I/D genotype with ACE serum enzymatic
activity. Finally, a more prolonged follow-up and a larger study group would
probably have shown a stronger effect of the studied ACE and AGT
genotypes in the cumulative risk for MA.
77..33 IIMMPPLLIICCAATTIIOONNSS AANNDD FFUUTTUURREE DDIIRREECCTTIIOONNSS
The studies comprising this thesis have provided further insights into the
natural history of MA in children and adolescents with T1DM. The knowledge
gained from these studies contributes largely to identifying children at risk for
this complication. A combination of clinical and genetic factors is involved in
the pathogenesis of DN. Despite the decline in the prevalence of DN,
123
improvements in glycaemic control do not eliminate the risk of this
complication.
Our studies highlight the importance of having discussions on prevention of
complications in T1DM, mainly DN, earlier in the clinical practice. Although
DN is rarely seen during childhood, poor glycaemic control since diabetes
onset contributes to an increased risk for MA and the child with diabetes
who receives limited care is more likely to develop diabetes long-term
complications at an earlier age.
Although screening programs for diabetes complications are costly to set up,
attention to risk factors and the impact of improved glycaemic control should
reduce long-term morbidity and mortality from diabetes complications.
Nevertheless, the development of screening programs for subclinical
complications is only appropriate if treatment intervention is available. There
is need for the development of intervention therapies in T1DM children and
adolescents with the ultimate goal of reducing the rates of DN and other
complications.
77..33..11 IInntteerrvveennttiioonn DDiirreecctteedd ttoo TT11DDMM CChhiillddrreenn aanndd AAddoolleesscceennttss
77..33..11..11 GGllyyccaaeemmiicc CCoonnttrrooll
Glycaemic control remains the most important risk factor for DN and
glycosilated heamglobin levels during puberty are invariably higher than
those levels recommended for prevention of complications (325).
Although the adolescent subgroup of the DCCT provided unquestionable
evidence for the superiority of an intensified insulin regimen in reducing the
risk for DN, excess weight gain and hypoglycaemia were more frequent
compared to adults (39). In addition, the beneficial effects of intensified
insulin therapy during puberty seem to be less evident than in younger
children and older individuals with T1DM (360).
Achieving near-normal glycaemia without increasing the risk of severe
hypoglycaemia in young T1DM children and adolescents require a great
124
deal of effort on the part of both patients and those who care for them.
Nevertheless, based on our findings, one should recognize the effect of
prepubertal glycaemic exposure in increasing the risk for the future
development of MA and consider the concept of “metabolic memory”, in
which there is an imprinting phenomenon related to previous levels of
exposure to hyperglycaemia in determining the future development of DN
(206).
Therefore, in providing good quality diabetes care, every effort should go
into targeting a near-normal glycaemic control since the onset of diabetes,
with benefits and risks balanced and treatment individually tailored.
From our findings, we concluded that early signs of DN occur in puberty but
the relationship between incipient DN and puberty is partly mediated by poor
glycaemic control. Puberty itself exerts an independent effect in the
development of MA. Intervention on other modifiable factors in addition to
poor glycaemic control should be targeted in children and adolescents with
T1DM, particularly BP and lipid control.
77..33..11..22.. TThhee uussee ooff aannttiihhyyppeerrtteennssiivvee ttrreeaattmmeenntt
It is now over 30 years since Mogensen showed that the use of
antihypertensive treatment attenuates the rate of decline in renal function in
T1DM (361). In adults with T1DM and MA with or without hypertension, there
is a universal agreement in the usage of ACEI or ARB as these have been
shown to reduce the risk of progression of MA to overt DN and of mortality
from CVD (362).
In the paediatric population, although screening guidelines for MA are
routinely recommended (261, 262), recommendations on who should
receive treatment with renoprotective agents and when are not consistent.
There are still some concerns regarding the use of ACEI in protecting long-
term renal function in young people without hypertension. Some clinicians
treat only if retinopathy and hypertension coincide, others will treat patients
with a familial history of hypertension or CVD, and still others who will treat
all patients that develop MA (363).
125
There is no consensus as to the use of either ACEI or ARB during
adolescence.
ACE Inhibitors (ACEI)
As mentioned previously, our findings showed a strong association between
ACE I/D and AGT M235T variants with increased risk for DN as well as
changes of ambulatory BP preceding the appearance of MA. Due to the
known renoprotective effect associated with antihypertensive action, drugs
that affect the RAS are potentially the first choice in preventing DN.
In a meta-analysis of 12 studies involving 698 adults with T1DM, patients
receiving ACEI had a reduction in AER of 50% compared to those receiving
placebo. In the normotensive T1DM patients with MA, ACEI reduced
progression to overt nephropathy (121).
In the paediatric group, only a small number of studies have been performed
suggesting the potential benefits of ACEI in the adolescents T1DM group
(364, 365) However, most of these studies have included small number of
subjects followed for a short period of time. There is an urgent call for long-
term randomized control trials involving the use of ACEI the paediatric
population. Since the elaboration of this thesis and publication of our results,
a large multicentric trial aiming for prevention of long-term complications in
T1DM adolescents, the Adolescent T1DM Cardio-Renal Intervention Trial
(AdDIT) is under development coordinated primarily by Prof Dunger in the
United Kingdom (Cambridge). This study involved several groups from
United Kingdom, Australia and Canada. In Australia, Western Australia has
become the National Coordinator Centre. In this study, a large cohort of
adolescents at high-risk for DN, based on AER in the upper tertile, will
receive intervention with ACEI, statins or a combination of both and will be
compared with the use of placebo.
Angiotenisn II receptor blocker (ARB)
The ARBs are selective inhibitors of the angiotensin II type I receptor. These
drugs have not been used widely until now. However, studies from in adults
126
with T1DM and T2DM suggest that this may be a valuable new drug in
reducing the risk for DN and other diabetes complications (366, 367).
Up to now, there has been no clinical trial in the paediatric population in
order to exploit the pharmacological profile of this drug in this age group.
77..33..11..33.. TThhee uussee ooff lliippiidd aaggeennttss
Although hyperlipidaemia is commonly reported in the paediatric T1DM
population (226) there is no longitudinal study using lipid lowering agents in
this population. Based on a 10-year incidence data, the Pittsburgh
Epidemiology of Diabetes Complications Study suggests a vigorous control
of lipids and BP in terms of reducing mortality and CVD (226). Treatment
with lipid lowering agents, statins, has been increasingly used in adults in
order to reduce vascular events (250).
The AdDit study, as previously mentioned, is the first long-term randomized
control trial in the paediatric population addressing the effects of statins in
preventing microvascular complications, mainly DN, in the adolescents
group.
77..33..22 GGeenneettiicc SSccrreeeenniinngg ffoorr DDNN
The pathogenesis of DN involves an interplay between environmental
factors and an individual genetic predisposition (mono or polygenic factors),
which determines a phenotypic expression. No particular mutation has been
identified, which could explain the development of DN in the majority of
patients; the use of genetic markers as a population screening in assessing
the risk of DN is somehow limited.
However, the discovery of susceptibility genes for DN identifiable at early
stages in the course of the disease in childhood implicates on the
development of novel modalities of prevention and treatment of this
complication. For example, several studies have reported that genetic
variants at the ACE gene seem to modulate the response to the use of ACEI
127
in DN (166). By having a better understanding of the genetic profile in
relation to the development of DN may be useful in selecting different
antihypertensive agents for patients with different genetic profile.
In addition, the future development of better technologies, such as the
genomic and proteinomic approaches, will possibly unravel the genetics of
DN, identify new mechanisms of renal disease and generate target
molecules for prevention and treatment of DN.
In summary, we have studied clinical and genetic markers for DN in children
and adolescents with T1DM. Based on these findings and other studies,
future protocols could be developed to prevent incipient DN including:
Longitudinal Intervention trials comparing the use of ACEI and ARB in
the progression of DN in childhood;
Longitudinal studies assessing the long-term effects of ACEI and the
use of lipid agents in the development of DN (currently under
development, the AdDIT study);
The use of genetic markers of RAS in assessing not only the risk for
DN but also the response to different antihypertensive agents used in
the adolescent group.
128
RReeffeerreenncceess
129
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342. Yip JW, Jones SL, Wiseman MJ, Hill C, Viberti G. Glomerular hyperfiltration in the prediction of nephropathy in IDDM: a 10-year follow-up study. Diabetes. 1996;45(12):1729-33.
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344. Doria A, Onuma T, Gearin G, Freire MB, Warram JH, Krolewski AS. Angiotensinogen polymorphism M235T, hypertension, and nephropathy in insulin-dependent diabetes. Hypertension. 1996;27(5):1134-9.
345. Rogus JJ, Moczulski D, Freire MB, Yang Y, Warram JH, Krolewski AS. Diabetic nephropathy is associated with AGT polymorphism T235: results of a family-based study. Hypertension. 1998;31(2):627-31.
346. Alsaeid M, Moussa MA, Haider MZ, Refai TM, Abdella N, Al-Sheikh N, et al. Angiotensin-converting enzyme gene polymorphism and lipid profiles in Kuwaiti children with type 1 diabetes. Pediatric Diabetes. 2004;5(2):87-94.
347. Kobayashi K, Amemiya S, Mochizuki M, Matsushita K, Sawanobori E, Ishihara T, et al. Association of angiotensin-converting enzyme gene polymorphism with lipid profiles in children and adolescents with insulin-dependent diabetes mellitus. Hormone Research. 1999;51(4):201-4.
348. Tarnow L, Cambien F, Rossing P, Nielsen FS, Hansen BV, Ricard S, et al. Angiotensin-II type 1 receptor gene polymorphism and diabetic microangiopathy. Nephrology Dialysis Transplantation. 1996;11(6):1019-23.
349. Tarnow L, Kjeld T, Knudsen E, Major-Pedersen A, Parving HH. Lack of synergism between long-term poor glycaemic control and three gene polymorphisms of the renin angiotensin system on risk of developing diabetic nephropathy in type I diabetic patients. Diabetologia. 2000 Jun;43(6):794-9.
350. White NH, Cleary PA, Dahms W, Goldstein D, Malone J, Tamborlane WV, et al. Beneficial effects of intensive therapy of diabetes during adolescence: outcomes after the conclusion of the Diabetes Control and Complications Trial (DCCT). Journal of Pediatrics. 2001;139(6):804-12.
351. Hovind P, Tarnow L, Rossing P, Graae M, Torp I, Binder C, et al. Predictors for the development of microalbuminuria and macroalbuminuria in patients with type 1 diabetes: inception cohort study. Bmj. 2004 May 8, 2004;328(7448):1105.
352. Amin R, Widmer B, Dalton RN, Dunger DB. Unchanged incidence of microalbuminuria in children with type 1 diabetes since 1986: a UK based inception cohort. Archives of Disease in Childhood. 2009 April 1, 2009;94(4):258-62.
353. Dunger DB, Schwarze CP, Cooper JD, Widmer B, Neil HAW, Shield J, et al. Can we identify adolescents at high risk for nephropathy before the development of microalbuminuria? Diabetic Medicine. 2007;24(2):131-6.
354. Abraha A, Schultz C, Konopelska-Bahu T, James T, Watts A, Stratton IM, et al. Glycaemic control and familial factors determine hyperlipidaemia in early childhood diabetes. Oxford Regional Prospective Study of Childhood Diabetes. Diabetic Medicine. 1999;16(7):598-604.
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359. Soergel M, Kirschstein M, Busch C, Danne T, Gellermann J, Holl R, et al. Oscillometric twenty-four-hour ambulatory blood pressure values in healthy children and adolescents: a multicenter trial including 1141 subjects. Journal of Pediatrics. 1997;130(2):178-84.
360. Danne T, Mortensen HB, Hougaard P, Lynggaard H, Aanstoot HJ, Chiarelli F, et al. Persistent differences among centers over 3 years in glycemic control and hypoglycemia in a study of 3,805 children and adolescents with type 1 diabetes from the Hvidore Study Group. Diabetes Care. 2001;24(8):1342-7.
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365. Rudberg S, Aperia A, Freyschuss U, Persson B. Enalapril reduces microalbuminuria in young normotensive type 1 diabetic patients irrespective of its hypotensive effect. Diabetologia. 1990;33(8):470-6.
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157
Appendix A
Information Sheet and Consent Forms
158
MICROALBUMINURIA STUDY: PREVALENCE, CLINICAL CHARACTERISTICS AND
GENETIC MARKERS OF NEPHROPATHY IN CHILDREN AND ADOLESCENTS WITH
TYPE 1 DIABETES IN WESTERN AUSTRALIA.
Introduction: Among subjects with diabetes, the risk of developing complications from the
disease is greatly reduced by an improvement in the control of blood glucose. However, some
children and adolescents still develop problems with their kidneys as adults despite good control of
their blood glucose levels. As well as being related to glycaemic control, the risk of complications
may be partly inherited. Some genes may also influence the development of kidney complications.
Small leaks of protein in the urine of children and adolescents with diabetes (microalbuminuria) may
be the first marker of a later risk of developing complications. We plan to investigate the relationship
between the amount of protein in the urine, microalbuminuria, in adolescents with Type 1 diabetes
and the blood pressure.
What does the study involve? This study aims to find a relationship between blood pressure
and the amount of protein in the urine.
Your child will also be asked to provide three overnight urine samples for measurements of protein in
the urine and a blood test for assessing the genes and lipids. Blood pressure assessment will be
performed by using a 24-hour blood pressure machine.
What will happen to the data and the samples? Blood and urine samples will be
analysed at the laboratories in Princess Margaret Hospital for Children. Results will be kept
confidential and only available to the investigators involved in the study.
How will I find out the results of the tests? We will inform you and your child about all
the test results so that any necessary therapeutic adjustments can be performed. In the unlikely event
that the results are outside the normal range, we will advise you so that the necessary steps can be
taken.
If I agree to join the study: We will arrange dates for your child’s assessments. We will also
organise a convenient time to review your test results. Your involvement is entirely voluntary and
you are free to withdraw at any stage without affecting your child’s care at our department in any
way.
Confidentiality: Of note, we remind you that all the information will be kept under
confidentiality. A number will codify the data sheets. Only the principal investigators and supervisor
of the study will have access to the data.
Whom should I contact if I have any questions or concerns about the study? If you have any questions regarding this study, do not hesitate to contact:
Dr Timothy W Jones
Head of Department Endocrinology and Diabetes
Princess Margaret Hospital for Children
Roberts Road, Subiaco, WA 6008
Phone: (08) 9340-8090; FAX: (08) 9340 8605
E-mail: [email protected]
Dr Patricia Herold Gallego
Paediatric Endocrinologist Fellow
Department of Endocrinology and Diabetes
Princess Margaret Hospital for Children
Roberts Road, Subiaco
WA 6008
Phone: (08) 9340-8744/ 9340-8671
FAX: (08) 9340-8605
Email: [email protected]
159
FORM OF CONSENT - PARTICIPANT
PLEASE NOTE THAT PARTICIPATION IN RESEARCH STUDIES IS
VOLUNTARY AND SUBJECTS CAN WITHDRAW AT ANY TIME WITH
NO IMPACT ON CURRENT OR FUTURE CARE.
I
....................................................................................................................................
have read and understood the information explaining the study entitled
“Microalbuminuria: Prevalence, Clinical Characteristics and Genetic Markers
of Nephropathy in Children and Adolescents with Type 1 Diabetes Mellitus in
Western Australia”
I agree to participate and I understand that I may withdraw from the study at
any stage and withdrawal will not interfere with routine care.
I agree that research data gathered from the results of this study may be
published, provided that names are not used.
Dated ................................. day of ............................................................ 20 ..........
Participant’s Signature ..................................................………………………………..
I,……............................................... …………………………………………………...
(investigator’s name)
have explained the above to the signatories who stated that he/she understood the
same.
Signature:.......................................................................................…………………….
160
FORM OF CONSENT TO PARENTS AND CHILD
PLEASE NOTE THAT PARTICIPATION IN RESEARCH STUDIES IS
VOLUNTARY AND SUBJECTS CAN WITHDRAW AT ANY TIME WITH
NO IMPACT ON CURRENT OR FUTURE CARE.
I
....................................................................................................................................
have read and understood the information explaining the study “ Microalbuminuria:
Prevalence, Clinical Characteristics and Genetic Markers of Nephropathy in
Children and Adolescents with Type 1 Diabetes Mellitus in Western Australia”
Any questions I have asked have been answered to my satisfaction. I agree to
participate in this study and I understand my child may withdraw from the study at
any stage and withdrawal will not interfere with routine care.
I agree that research data gathered from the results of this study may be
published, provided that names are not used.
Dated.................... day of........................................................ 20 ........…………………
Child’s Signature ...................................………………………………………………..
Parent or Guardian’s
Signatures…………………………………………………………
I, ....................................................... …………………..have explained the above to
the (Investigator’s full name)
signatory who stated that he/she understood the same.
Signature
.............................................................................................................................
161
DNA CONSENT FORM FOR GENE STUDIES
I consent to the collection from my child of (blood – via venepuncture, thumb
prick; cells - mouthwash) from which DNA will be extracted and stored for the gene
studies that have been explained to me as part of the study: “Microalbuminuria:
Prevalence, Clinical Characteristics and Genetic Markers of Nephropathy in
Children and Adolescents with Type 1 Diabetes Mellitus in Western Australia”
I consent to my child’s DNA being used for gene research into ……………………..
(condition)
I understand that the DNA will not be used for purposes other than that specified
above and will not be used for diagnostic purposes.
Name of child: ………………………. …………………………………………….
Name of Parent / Guardian: ………………………………………………………...
Signature: …………………………………………….Date: ……………………..
Witness: ……………………………………………....Date: ……………………..
162
DNA CONSENT FORM FOR GENE STUDIES
I consent to the collection of my (blood – via venepuncture, thumb prick; cells -
mouthwash) from which DNA will be extracted and stored for the gene studies that
have been explained to me as part of the study “Microalbuminuria: Prevalence,
Clinical Characteristics and Genetic Markers of Nephropathy in Children and
Adolescents with Type 1 Diabetes Mellitus in Western Australia”
I consent to my DNA being used for gene research into ……………………..
(condition)
I understand that the DNA will not be used for purposes other than that specified
above and will not be used for diagnostic purposes.
Name of Participant: ……………………………………………………………….
Signature: ……………………………………………….Date: ……………………
Witness: ………………………………………………..Date: …………………...
[Type text]
163
Appendix B
Classification and characteristic features of T1DM in children
Screening guidelines for vascular complications in the
paediatric and adolescent T1DM group
Association Between p.Leu54MetPolymorphism at the Paraoxonase-1 Geneand Plantar Fascia Thickness in YoungSubjects With Type 1 DiabetesPATRICIA H. GALLEGO, MD, MSC
1
MARIA E. CRAIG, MBBS, PHD, FRACP1,2,3
ANTHONY C. DUFFIN, PHD1
BRUCE BENNETTS, PHD, FHGSA4
ALICIA J. JENKINS, MBBS, MD, FRACP, FRCP5
SABINE HOFER, MD6
ALBERT LAM, MD, FRACR7
KIM C. DONAGHUE, MBBS, PHD, FRACP1,2
OBJECTIVE — In type 1 diabetes, plantar fascia, a collagen-rich tissue, is susceptible toglycation and oxidation. Paraoxonase-1 (PON1) is an HDL-bound antioxidant enzyme. PON1polymorphisms have been associated with susceptibility to macro- and microvascular compli-cations. We investigated the relationship between plantar fascia thickness (PFT) and PON1 genevariants, p.Leu54Met, p.Gln192Arg, and c.-107C�T, in type 1 diabetes.
RESEARCH DESIGN AND METHODS — This was a cross-sectional study of 331adolescents with type 1 diabetes (162 male and 169 female). PFT was assessed by ultrasound,PON1 was assessed by genotyping with PCR and restriction fragment–length polymorphism,and serum PON1 activity was assessed by rates of hydrolysis of paraoxon and phenylacetate.
RESULTS — Median (interquartile range) age was 15.4 (13.5–17.3) years, and diabetes du-ration was 7.6 (4.9–10.6) years. The distribution of p.Leu54Met genotypes was LL 135 (40.8%),ML 149 (45%), and MM 47 (14.2%). PFT was abnormal (�1.7 mm) in 159 adolescents (48%).In multivariate analysis, predictors of abnormal PFT were ML/LL versus MM p.Leu54Met poly-morphism (odds ratio 3.84 [95% CI 1.49–9.82], P � 0.005); BMI (percentile) (1.02 [1.01–1.03], P � 0.007); systolic blood pressure (percentile) (1.01 [1.00–1.02], P � 0.03); and malesex (3.29 [1.98–5.46], P � 0.001).
CONCLUSIONS — Thickening of the plantar aponeurosis occurs predominantly in over-weight and male adolescents with type 1 diabetes. The MM genotype at PON1 p.Leu54Met isassociated with a reduced risk of abnormal PFT.
Diabetes Care 31:1585–1589, 2008
P araoxonase-1 (PON1) is a calcium-dependent HDL-associated enzymethat protects LDLs from oxidation.
In type 1 diabetic patients, the serumparaoxonase concentration is lower andHDL is a less efficient antioxidant than inhealthy individuals (1). Oxidized LDL isimplicated in the pathogenesis of athero-
sclerosis, diabetic retinopathy, and ne-phropathy (2). Variations in lipoprotein-related enzymes and genotypes may alsopromote diabetic microvascular damage(3).
Soft-tissue thickening is associatedwith chronic hyperglycemia and is hy-pothesized to be due to collagen glycation
(4). With use of ultrasound techniques tomeasure plantar aponeurosis, a collagen-rich tissue, researchers demonstrated pre-viously that people with diabetes haveincreased plantar fascia thickness (PFT)(5). Recently, this group reported that in-creased PFT predicted the developmentof microvascular complications in adoles-cents with type 1 diabetes and proposedabnormal PFT as a putative marker ofsoft-tissue glycation (6).
The PON gene cluster maps to chro-mosome 7q21-22 and influences gene ex-pression and serum activity. There is anestablished link between PON1 and mac-rovascular disease (7) and emerging evi-dence linking PON1 to microvascularcomplications (8,9). In this study we in-vestigated whether the variants c.-107C�T at the promoter region andp.Leu54Met and p.Gln192Arg at thecoding regions of PON1 are associatedwith PFT in type 1 diabetes.
RESEARCH AND METHODS —The cohort consisted of 331 Caucasianadolescents and young adults (162 maleand 169 female) with a median (inter-quartile range) age of 15.4 (13.5–17.3)years and type 1 diabetes duration of 7.6(4.9–10.6) years, who presented for rou-tine complications assessment at the Chil-dren’s Hospital at Westmead (Sydney,Australia) between 1998 and 2004. Thestudy was approved by the hospital’s eth-ics committee, and written informed con-sent was obtained.
PFT measurementA single investigator (A.D.) measured PFTusing ultrasound (Acuson 128 gray scaleimager; Acuson, Mountain View, CA).For aponeurosis measurements, a linear-array, 7-MHz high-resolution transducerwas placed longitudinally over the centerof the arch at least 3 cm from the calcanealinsertion. To assess test-retest variability,four individuals were assessed 10 times inthe same session. The assessor wasmasked to the measurements until theywere completed and stored. The intra-class coefficient was 0.89. Abnormal PFT
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From the 1Institute of Endocrinology and Diabetes, The Children’s Hospital at Westmead, Sydney, NewSouth Wales, Australia; the 2Discipline of Paediatrics and Child Health, University of Sydney, Sydney,New South Wales, Australia; the 3School of Women’s and Children’s Health, University of New SouthWales, Sydney, New South Wales, Australia; the 4Department of Molecular Genetics, The Children’sHospital at Westmead, Sydney, New South Wales, Australia; the 5Department of Medicine (St. Vincent’s),University of Melbourne, Melbourne, Victoria, Australia; the 6Department of Paediatrics, Medical Uni-versity of Innsbruck, Innsbruck, Austria; and the 7Department of Radiology, The Children’s Hospital atWestmead, Sydney, New South Wales, Australia.
Corresponding author: Patricia H. Gallego, [email protected] 25 November 2007 and accepted 2 May 2008.Published ahead of print at http://care.diabetesjournals.org on 9 May 2008. DOI: 10.2337/dc07-2236.© 2008 by the American Diabetes Association. Readers may use this article as long as the work is properly
cited, the use is educational and not for profit, and the work is not altered. See http://creativecommons.org/licenses/by-nc-nd/3.0/ for details.
The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be herebymarked “advertisement” in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
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(�1.7 mm) was defined as 2 SDs abovethe mean measurement of 57 age-matched unrelated nondiabetic controlsubjects (27 male, median age 15.6 years)(5).
PON1 genotypingDNA was extracted from peripheral whiteblood cells collected in lithium-heparintubes using a modified salting out proto-col. Polymorphisms were analyzed byPCR-restriction fragment–length poly-morphism using a slightly modified ver-sion of the procedure described byHumbert et al. (10). DNA (100 ng) wasdenatured (94°C, 12 min) and then am-plified for 35 cycles using PCR primers.Each cycle consisted of denaturation(94°C, 30 s), annealing (55°C, 30 s), andextension (72°C, 30 s) with a final exten-sion of 5 min. For p.Leu54Met geno-typing, the 171-bp PCR product wasdigested (37°C, 2 h) with Hsp92II (Pro-mega, Madison, WI), and products wereseparated by PAGE (10%) and stained byethidium bromide. The leucine allele cor-responded to the presence of a non-digested fragment of 171 bp; themethionine allele corresponded to twodigestion fragments of 127 and 44 bp.
For p.Gln192Arg genotyping, the99-bp PCR product was digested withDpnII, and products were separated byPAGE (10%). The arginine allele corre-sponded to the presence of three diges-tion fragments (40, 31, and 28 bp); theglutamine allele corresponded to two di-gestion fragments of 59 and 40 bp.
For c.-107C�T genotyping, the240-bp PCR product was digested withBsrBI, and products were separated byPAGE (10%). The TT genotype corre-sponded to a nondigested 240-bp frag-
ment, the CC genotype corresponded totwo digestion fragments of 212 and 28bp, and the CT genotype corresponded tothree digestion fragments of 240, 212,and 28 bp.
PON1 activityIn a representative subgroup of subjects(n � 144), PON1 activity of lithium-heparin plasma was measured by the ratesof hydrolysis of paraoxon and phenylace-tate as described previously (9).
Other variablesA1C was measured by a Bio-Rad Diamatanalyzer (nondiabetic range of 4 – 6%;Bio-Rad Laboratories, Hercules, CA).Nonfasting plasma cholesterol was mea-sured by Cobas Mira. Systolic blood pres-sure (SBP), diastolic blood pressure(DBP), and BMI percentiles were deter-mined using age- and sex-related refer-ence standards.
Statistical analysisDescriptive statistics are reported asmeans � SD or median (interquartilerange) for skewed distributions. Groupswere compared by �2 test for categoricalvariables. Differences between indepen-dent samples were evaluated using Stu-dent’s t test and one-way ANOVA fornormally distributed data or the Mann-Whitney U test for skewed data.
Multiple logistic regression was usedto evaluate the association between ab-normal PFT and biological and geneticvariables. Explanatory variables were sex,age, diabetes duration, A1C, BMI, SBP,cholesterol, and PON1 genotypes (MMvs. ML/LL for p.Leu54Met; QQ vs. RQ/RRfor p.Gln192Arg, and TT vs. CT/CC forc.-107C�T). Results are expressed as
odds ratios and 95% CI. P � 0.05 indi-cated statistical significance.
RESULTS — Clinical characteristicsare summarized in Table 1. Patients withabnormal PFT had higher SBP and BMIpercentiles and were more likely to bemale. PON1 activity was not significantlydifferent between those with or withoutabnormal PFT for any substrate.
Table 2 shows genotype distributionsand allele frequencies (all mutations werein Hardy-Weinberg equilibrium). Activi-ties for phenylacetate and paraoxon sub-strates were higher for patients carryingLL alleles at PON1 p.Leu54Met versusthose with the MM genotype. Similarly,those with CC alleles at c.-107C�T hadhigher enzyme activity for both substratesversus those with the TT genotype. Atp.Gln192Arg, enzyme activity for hydro-lysis of paraoxon was higher in those withthe RR versus the QQ genotype, but phe-nylacetate activities did not differ.
The p.Leu54Met genotype distribu-tion differed between the two PFT groups.The MM genotype was less frequentamong those with thickened aponeurosis(normal PFT 20% vs. abnormal PFT 8%,�2, P � 0.01). There was no difference infrequency of p.Gln192Arg or c.-107C�Tgenotype distribution by PFT (Table 3).
In the multiple regression, LL/ML atp.Leu54Met, male sex, and BMI and SBPpercentiles were associated with in-creased PFT (Table 4). There was no in-teraction between sex and BMI, sex andPON1 variants, or BMI and PON1 vari-ants. There was strong linkage disequilib-r ium be tween p .Leu54Met andp.Gln192Arg and between p.Leu54Metand c.-107C�T genotypes (not shown).
Table 1—Clinical characteristics of young subjects with type 1 diabetes with and without abnormal PFT
Normal PFT Abnormal PFT Total P value
n 172 159 331Age (years) 15.7 (13.5–17.3) 15.1 (13.5–17.3) 15.4 (13.5–17.3) 0.46Sex (male/female) 62/110 100/59 172/159 �0.001Diabetes duration (years) 7.6 (5.0–10.3) 7.9 (4.3–11.0) 7.6 (4.9–10.6) 0.77A1C (%) 8.6 � 1.3 8.5 � 1.1 8.6 � 1.3 0.69Total cholesterol (mmol/l) 4.3 (3.9–5.0) 4.3 (3.8–4.8) 4.3 (3.8–4.9) 0.42SBP (percentile) 54 (27–82) 71 (38–85) 59 (32–82) 0.004DBP (percentile) 73 (48–83) 73 (48–87) 73 (48–84) 0.49BMI (percentile) 74 (56–87) 78 (63–91) 76 (61–88) 0.02PON1 activity*
Paraoxon (units/ml) 39.6 (28.3–79.3) 45.4 (28.1–85.4) 41.4 (28.4–79.9) 0.41Phenylacetate (units/ml) 64.9 (44.6–81.6) 70.6 (56.7–80.4) 66.7 (52.8–80.5) 0.26
Data are means � SD or median (interquartile range). *PON1 activity was measured in 144 subjects.
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CONCLUSIONS — This is the firstreport demonstrating an association be-tween PFT, a marker of tissue glycationand/or oxidation, and PON1 gene poly-morphisms in type 1 diabetes. In thiscross-sectional study, the L allele at thep.Leu54Met gene was associated with ab-normal PFT, or, conversely, the M allelehad a protective effect. These results sup-port the association between PON1 genepolymorphisms and plantar fasciachanges. Previously, our group showedthat the LL genotype was closely associ-ated with microvascular complications(9,11).
After a relatively short median diabe-tes duration of 7 years, approximately halfof the cohort had abnormal plantar fasciameasurements. The early appearance ofabnormal PFT, although unrelated toA1C measured at the time of the assess-ment, does not exclude the possibilitythat early glycemic variability could leavean imprinting in target organs, includingchanges in collagen, predisposing theseorgans to the future development of com-plications. In support of this possibility,we have recently demonstrated that PFTpredicts retinopathy, early elevation of al-bumin excretion rate, and nerve abnor-malities in young people with type 1diabetes (6).
Oxidative stress and abnormalities oflipoprotein quantity and quality are im-plicated in the pathogenesis of microvas-cular complications (3). We hypothesizethat genetic variants at the PON1 gene, foran antioxidant enzyme, could also predis-pose to collagen abnormalities via ad-vanced glycation end product (AGE)
formation, which involves glycation andoxidation. Tissue glycation and/or oxida-tion via intra- and extracellular generationof AGEs may promote diabetes complica-tions. The Diabetes Control and Compli-cations Trial/Epidemiology of DiabetesInterventions and Complications (DCCT/EDIC) demonstrated in skin biopsies thatcollagen AGEs predict microvascular dis-ease (12). Skin collagen methionine sul-foxide, a marker of oxidative damage
independent of glycemia, has also beenassociated with type 1 diabetes complica-tions (13).
There are divergent reports of PON1activity and genotype and their relation-ship to microvascular complications. Ourgroup described a higher allelic frequencyof leucine 54 among type 1 diabetic sub-jects with versus without retinopathy(14). Similar findings were subsequentlyconfirmed in a larger cohort of 372 type 1
Table 2—Allele frequencies and enzyme activity of PON1 genotypes for hydrolysis of paraoxon and phenylacetate as substrates
Polymorphism Genotype (n)Frequency
(Hardy-Weinberg)Paraoxon(units/ml) Phenylacetate (units/ml)
n 331 144 144p.Leu53Met LL (135) 0.40 (0.39) 77.8 (46.2–106.5) 73.4 (64.9–87.7)
ML (149) 0.45 (0.46) 39.1 (28.4–64.7) 66.2 (53.0–80.9)MM (47) 0.14 (0.13) 21.0 (16.7–30.4) 56.0 (39.5–63.0)
P value �0.001 �0.001p.Gln191Arg RR (29) 0.09 (0.08) 99.8 (73.0–185.0) 68.2 (32.2–85.8)
RQ (127) 0.38 (0.39) 80.3 (63.4–106.1) 68.7 (54.6–80.1)QQ (175) 0.53 (0.52) 30.5 (24.5–39.8) 66.7 (53.1–81.7)
P value �0.001 0.81c.-107C�T* CC (90) 0.27 (0.26) 61.4 (37.9–90.3) 77.4 (68.4–90.2)
CT (154) 0.49 (0.49) 40.3 (28.7–82.3) 70.3 (59.4–81.6)TT (75) 0.24 (0.24) 34.6 (20.8–73.6) 54.0 (39.7–63.2)
P value 0.017 �0.001
Data are median (interquartile range) unless otherwise indicated. *For c.-107C�T, genotyping was performed in 319 individuals and PON1 activity measured in139 subjects.
Table 3—Distribution of PON1 genotype in subjects with type 1 diabetes with and withoutabnormal PFT
Normal PFT Abnormal PFT P value
p.Leu54MetLL 66 (38) 69 (43)ML 72 (42) 77 (49) 0.01MM 34 (20) 13 (8)
p.Leu54MetMM 34 (20) 13 (8)ML/LL 138 (80) 146 (92) 0.003
p.Gln192ArgRR 14 (8) 15 (9)RQ 64 (37) 63 (40) 0.81QQ 94 (55) 81 (51)
p.Gln192ArgQQ 94 (55) 81 (51)RQ/RR 78 (45) 78 (49) 0.58
c.-107C�TTT 41 (25) 34 (22)CT 76 (46) 78 (51) 0.65CC 49 (29) 41 (27)
c.-107C�TTT 41 (25) 34 (22)CT/CC 125 (75) 119 (78) 0.69
Data are n (%).
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diabetic adolescents in whom the LL ge-notype increased risk for early retinopa-thy by almost threefold (8). The presenceof the LL genotype and two other PON1polymorphisms was found to influenceurinary albumin excretion in 156 Cauca-sian type 1 diabetic adolescents (9). Incontrast, others found no correlation be-tween microvascular complications andPON1 polymorphisms in adults with type1 diabetes (15). Divergent results may beexplained by differences in ethnicity, age,sample size, smoking, diet, concomitantmedications (16), PON1 assays, and dif-fering relationships between PON activityor genotype for initiation and progressionof complications.
Conversely, there is strong evidenceshowing that “high-expressor” PON1 al-leles influence macrovascular disease.Homozygosity for the L allele doubledcardiovascular disease risk after adjust-ment for other risk factors in diabetes(17).
If PON1 protects lipids from oxida-tion, one might expect a higher expressorallele and a higher enzymatic activity to beprotective against oxidative stress, AGEformation, and diabetes complications.However, the artificial nature of the sub-strates in this study is recognized and maynot represent physiological substrates. Arecent report demonstrated that the pri-mary activity of the paraoxonases is thatof a lactonase (18). As yet, there are nostudies relating lactonase activity to dia-betes complications.
Although PON1 activity was mea-sured in a subgroup of subjects, PON1polymorphisms influenced at least one ofthe two measured activities, in agreementwith published data (19). PON1 activitywas higher in the abnormal PFT groupbut did not achieve statistical significance.There is a large interindividual variationin PON activity that mostly depends onfunctional and promoter variations at thePON gene. Lower PON activity has beenreported in type 1 diabetic subjects versuscontrol subjects regardless of differences
in PON1 phenotype (20). Hyperglycemiamay influence the in vivo concentrationand in vitro activity of PON1. Kordonouriet al. (11) showed that higher PON1 ac-tivity was associated with high glucoselevels but not with A1C. With adjustmentfor blood glucose and diabetes duration,PON1 activity was higher in subjects withdifferent stages of retinopathy versusthose without retinopathy.
Our findings suggest that high-expressor alleles and a higher enzymaticactivity are associated with increased sus-ceptibility to microvascular complica-tions (8,9,11). One explanation could bethat although paraoxonase hydrolyzesharmful lysolipids produced by peroxida-tion, it might also increase their produc-tion from phospholipid peroxidationproducts and create a more harmful li-poprotein profile. The LL genotype hasbeen shown to be least protective againstoxidation (21). Another possibility is thatrelatively reduced enzyme activity ratherthan increased absolute PON1 activitypromotes vascular complications. Somehave reported that a higher LDL choles-terol–to-PON concentration ratio may in-dicate a reduced capacity of the enzyme tolimit LDL oxidation (22). The low-activityallele at the PON1 gene has also been as-sociated with a less harmful lipoproteinprofile (23). Data on the LDL cholesterol–to-PON concentration ratio or levels ofLDL cholesterol, triglycerides, and apoli-poprotein B were not available for thisstudy.
Male sex presented a threefold in-creased risk for thickened aponeurosis in-dependent of other risk factors. Thereasons for this are unclear, but men havea greater risk of lower limb diabetes com-plications (24). Hormonal variation anddifferent recreational activities may becontributors. Although level of physicalactivity was not measured, it is unlikelythat plantar fasciitis, a common conditionamong athletes, is the cause of fasciathickness. Fasciitis is associated with heelpain, and its ultrasonographic changes
are limited to the proximal insertion ofthe aponeurosis (25).
Higher BMI and SBP were associatedwith abnormal PFT. Although BMI mayincrease mechanical load on the plantaraponeurosis, overweight is associatedwith microvascular complications in dia-betes, insulin resistance, hypertension,and an atherogenic profile.
In summary, this study underlinesthe association between p.Leu54Met vari-ants and PFT, implicating PON1 in thepathogenesis of diabetes-related collagenchanges. Although relationships betweenPON1 genes and collagen abnormalitiesmerit further investigation, these initialfindings support the concept of PON1 ge-netic variants as a link predisposing to de-velopment of complications in type 1diabetes.
Acknowledgments— This study was sup-ported by a Diabetes Australia Research TrustNew Millennium Grant.
We thank Connie Karschimkus and CheeLee for PON1 activity measurements.
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