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L'Épigéné)que et les maladies autoimmunes inflammatoires : En quête du Graal Marie Hudson, MD MPH Rhumatologue Hôpital Général Juif, Institut Lady Davis Université McGill

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L'Épigéné)que  et  les  maladies  auto-­‐immunes  inflammatoires  :  En  quête  du  Graal  

Marie Hudson, MD MPH Rhumatologue Hôpital Général Juif, Institut Lady Davis Université McGill

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Disclosures  

•  Unrestricted  grants  from  Roche,  Janssen,  Grifols,  Baxter,  CSL  Behring  

•  Advisory  board  for  Novar)s,  Sanofi  

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SSc  Mortality  Denmark

UK Sweden 1 Sweden 2

Spain Canada (Montreal, 1980s)

Italy Spain

Canada (Ontario, 1970s)

Pooled SMR = 3.53 (95% CI 3.03, 4.11) Elhai et al. Rheumatology 2012

Canadian Scleroderma Research Group (2005-2011)

SMR = 4.7 (95% CI 3.6, 5.7) Khananian et al. CRA 2014

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Objec)ves  1.  Understand  epigene)c  mechanisms  and  

their  role  in  systemic  autoimmune  inflammatory  rheuma)c  diseases  

2.  Review  preliminary  data  in  SARDs  

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Gene)cs  –  your  DNA  is  your  des)ny    

I am the beneficiary of a lucky break in the genetic sweepstake. Isaac Asimov (1920-1992)

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The  genomics  revolu)on  

•  Human  genome  project  -­‐  2003  •  Over  2000  loci  have  now  been  

iden)fied  to  be  significantly  and  robustly  associated  with  one  or  more  complex  traits.    

•  However,  the  propor)on  of  phenotypic  varia)on  explained  by  GWAS  findings  remains  rela)vely  low  for  most  complex  traits  (typically  less  than  10-­‐15%)  –  suscep)bility  genes  are    

neither  necessary  nor  sufficient      

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Disease  is  not  only  about  DNA    

Brooks et al. J Autoimmunity 2010.

Discordance of A-I phenotype in identical twins

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January    2010  

The  “genomics”  revolu)on    

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Overview  of  the  basics  

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Gene  expression  

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Main  components  of  epigene)c  code  

Methyl marks can repress gene activity

Histone tails can modulate gene activity

Non-coding RNAs can regulate gene expression

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DNA methylation is the addition of a methyl group to the 5’ end of a cytosine in a cytosine-guanine dinucleotide

DNA  methyla)on  

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Cau)on!  

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Agou)  sisters  

Jirtle and Waterland, Duke University

Agouti gene – important in determining colour of coat, propensity for obesity, diabetes, and cancer

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Agou)  gene  

Methylated agouti gene – off

Un-methylated agouti gene - on

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Epigene)cs  and  and  environmental  exposures  

SAME GENOME, DIFFERENT EPIGENOME Variability in CpG methylation determines

phenotype

Molec Cell Biol 2003.

Pregnant agouti mice were fed diets varying in B12 and folate…

Those with more B12 and folate had brown, thin pups with less diabetes. Jirtle and Waterland

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Epigene)cs  and  environmental  exposures  

BPA - a hormone-disrupting chemical found, for instance, in some plastics and the linings of some canned goods. Mice that were exposed to diets high in BPA prenatally were more likely to be yellow, become obese and develop diabetes and cancers compared to genetically identical mice without the exposure (Dolinoy et al. 2007). Offsprings of female

mice exposed to BPA (bisphenol-A) during pregnancy.

Jirtle PNAS 2007.

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It’s  complicated…  

•  Epigene)c  influences  can  cancel  each  other  out    –  Eg.  high  methyl  diet  and  BPA  in  agou)  mice  

–  R.  Jirtle  –  hgp://videocast.nih.gov/summary.asp?live=10520&bhcp=1,  minute  28.04  

•  Mice  are  not  humans  and  these  mice  were  exposed  to  huge  doses.  

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Back  to  humans…  

Yellow shows where the twins have epigenetic tags in the same place. Green and red show where the twins have epigenetic tags in different places.

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Epigene)cs  –  where  genes  meet  the  environment  

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Epigene)cs  in  health  

•  Epigene)c  signals  help  to  organize  genomic  informa)on  in  a  cell.  

•  Epigene)c  processes  are  fundamental  to  normal  development  and  cell  differen)a)on.  – Responsible  for  regula)ng  gene  expression  and  in  controlling  specific  cellular  func)ons.  

– All  cells  have  the  same  DNA  but  can  differen)ate  into  cell  types  via  epigene)c  signals.  

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Epigene)cs  in  disease  •  Epigene)c  marks  sensi)ve  to  the  environment  •  Epigene)c  abnormali)es  increasingly  recognized  in  human  disease  

–  Cancer  -­‐  Epigene)c  abnormali)es  might  explain  80-­‐90%  of  cancers  •  Eg.  Tumour  suppressor  genes  are  inac)vated  by  smoking  

•  Importantly,  epigene)c  marks  are  poten)ally  reversible  by  drug  treatments.    

–  Several  inhibitors  of  chroma)n-­‐modifying  enzymes,  including  histone  deacetylase  (HDAC)  inhibitors  and  DNA  methyltransferase  (DNMT)  inhibitors,  have  now  been  FDA  and  EU  approved  and  are  being  used  in  clinical  prac)ce  with  good  prognosis  for  tumor  regression.    

–  Eg.  VIDAZA  (azaci)dine;  DNA  demethyla)on)  for  MDS  

–  Drug  development  targe)ng  epigene)c  marks  is  in  now  in  full  swing.  

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Epigene)cs  in  autoimmune  diseases  

•  Autoimmune  diseases  are  thought  to  arise  from  an  interplay  of  “gene)c  predisposi)on”  and  “environmental  triggers”  

•  Epigene)cs  could  be  the  link  between  these  two  elements  

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Drug-­‐induced  lupus  •  Procainamide  and  

hydralazine    –  Both  drugs  shown  to  be  

associated  with  DNA  hypomethyla)on  

–  T  cell  methyla)on  defect  traced  to  low  DNMT1  levels  resul)ng  from  abnormal  ERK  pathway  signaling.  

–  Gene)c  predisposi)on  may  explain  why  some  but  not  all  pa)ents  exposed  to  these  drugs  develop  lupus-­‐like  disease  

Cornacchia E, Golbus J, Maybaum J, Strahler J, Hanash S, Richardson B. Hydralazine and procainamide inhibit T cell DNA methylation and induce autoreactivity. J Immunol. 1988;140:2197–2200.

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Other  poten)al  environmental  triggers  

Somers, Richardson. Lupus 2014.

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The  SARD  Hypothesis  

South  African  daisies  (Gorteria  diffusa)  are  unique  flowers  that  appear  in  16  different  shapes  and  colours  (ie.  genotype-­‐phenotype  discordance).  

Ellis,  Stephens.  Am  J  Botany  2008.    

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The  SARD  Hypothesis  

Familial poly-autoimmunity supports shared SARD signature.

Hudson et al. J Autoimmunity 2008.

Kuo et al. JAMA Int Med 2015.

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Addi)onal  evidence  for  SARD  hypothesis  

•  Clinical  -­‐  share  demographic  (women  >  men)  and  clinical  (inflammatory  arthri)s,  Raynaud’s  phenomenon,  inters))al  lung  disease)  manifesta)ons    

•  Immunological  -­‐  share  complex  abnormali)es  in  CD4+  T  lymphocyte  func)on,  in  par)cular  Treg  cell  subset  

•  Gene.c  –  share  HLA  and  non-­‐HLA  gene.c  suscep.bili.es    –  Cotsapas  et  al.  PLOS  gene)cs  2011  –  Cho  and  Gregersen.  NEJM  2011  

•  Environment  –  eg.  smoking  is  common  risk  factor  

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The  SARD  Hypothesis  

We hypothesize that the DNA methylomes of SARD patients have common and unique ‘SARD specific’ DNA methylation signatures. Environmental exposures modulate the risk of having those signatures.

Ellis,  Stephens.  Am  J  Botany  2008.    

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Genome-­‐wide  DNA  methyla)on  in  SARD  

Main limitations

– confounding by cell type, established disease, medication exposures

- low resolution approaches

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Epi-­‐SARD  study  -­‐  Methods  •  Incident,  treatment  naïve  subjects  •  Isolated  CD4  +  T  cells  •  Genome-­‐wide  DNA  methyla)on  of  CD4+  T  cells  was  assessed  using  the  Illumina  Infinium  HumanMethyla)on450  BeadChip  array  

•  Genome-­‐wide  gene  expression  was  carried  out  using  Illumina  TruSeq  stranded  RNA-­‐seq  

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CLiPP 01/2013-01/2015

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Cell  isola)on  

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Integra)ve  analysis  • First,  iden)fied  significantly  differen)ally  methylated  (DM)  sites  between  SARD  cases  and  controls  (ie.  no  significant  differences  between  disease  (p-­‐value  >0.2)  but  differen)ally  methylated  between  SARD  and  controls).    • Second,  iden)fied  significantly  differen)ally  expressed  (DE)  RNAseq  transcripts  between  SARD  cases  and  controls.  • Third,  iden)fied  genes  that  were  both  significantly  DM  and  DE.  • Adjusted  for  mul)ple  tes)ng.  

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SARD  signature  

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Log fold-change Ave. expression t P value Adjusted p B CD1C 1.878176186 -1.571708727 3.480974367 0.001103574 0.009594854 -0.875142348 AIPL1 1.180516781 -3.71637427 3.472447414 0.001131673 0.009774192 -0.921683609 CD36 1.071191215 -0.390132877 2.716164032 0.009265551 0.047078545 -2.687077009 CALHM2 0.896048994 0.74309745 2.787199521 0.0076947 0.040897653 -2.637585631 SYNPO2 0.891739201 -0.795858834 2.831603948 0.006841965 0.037306678 -2.41327067 DPYSL2 0.841284915 3.497565036 4.320155386 8.22E-05 0.00144616 1.256675619 SCD 0.839306682 0.750065481 3.668618319 0.000630144 0.006457008 -0.413870911 SLFN12L 0.80749901 4.102152265 5.385864606 2.37E-06 0.00010394 4.610626079 LIMA1 0.693959117 2.92256851 4.637757041 2.92E-05 0.000672132 2.276814437 CEP97 0.667110577 3.619971987 5.179085323 4.78E-06 0.00017278 3.956808949 TNRC6B 0.638464317 7.313600826 6.322637212 9.39E-08 1.03E-05 7.630432549 BCL2 0.621165505 7.31856972 3.989997394 0.000234452 0.003130261 0.042201908 ACTR3 0.513120975 6.982132479 5.054392222 7.28E-06 0.000235728 3.396416081 PCCA 0.43961969 2.018788673 3.948954273 0.000266507 0.003409277 0.255757429 MRPL48 0.434716098 2.259246861 3.373764885 0.001510666 0.012197772 -1.378318591 ZNF407 0.426504893 5.225624043 3.596960434 0.000781727 0.007521222 -1.013604888 TFDP1 0.343909917 3.558235673 3.377760897 0.001493214 0.012101897 -1.507046395 EIF2C1 0.337982277 4.361111941 3.874960676 0.00033532 0.004028302 -0.166530369 KIF13B 0.317276523 4.463419278 3.745123833 0.000499576 0.005408581 -0.551064288 NPEPPS 0.303402848 4.455457817 4.36023599 7.22E-05 0.001323894 1.287257248 ZMYM4 0.261843777 5.209462487 3.033239699 0.003964164 0.02497668 -2.533809017 CUL4A 0.245138862 4.993450196 3.490056435 0.001074379 0.009433317 -1.306978327 YWHAG -0.313231679 5.098025859 -3.274939384 0.002009299 0.014985822 -1.916324232 WIPI2 -0.314485056 4.580701632 -2.787930555 0.007679899 0.040849003 -3.124779224 ZNF552 -0.3269609 2.470099055 -3.342544169 0.001653851 0.013010132 -1.537143507 ATP5G2 -0.431385337 5.217949044 -4.029482884 0.000207157 0.00287371 0.219288047 RNMTL1 -0.462209923 3.28863435 -4.587305332 3.44E-05 0.000766109 2.039352774 CCDC40 -1.21616542 -1.930467602 -4.596073798 3.35E-05 0.000750982 2.203933966

Top  “28”  

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Gene  by  gene  analysis  •  CD1C  

–  cluster  of  differen)a)on  1C  –  over-­‐expressed  >  6-­‐fold  –  gene  expresses  an  MHC-­‐I  –like  

molecule  that  presents  lipid  an)gens  to  T  cells  and  helps  bridge  the  temporal  gap  between  the  onset  of  innate  immunity  and  the  adap)ve  responses  of  MHC-­‐restricted  T  cells.    

–  Role  for  CD1c  in  M.  Tb  and  other  microbial  infec)ons    

–  Very  ligle  known  for  role  of  CD1c  in  autoimmune  diseases.  

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Gene  ontology  •  GO  is  a  bioinforma)cs  approach  used  to  describe  gene  products  in  terms  of  their  biological  processes,  cellular  components  and  molecular  func)ons.  

•  Eg.  Ingenuity  Pathway  Analysis  

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Canonical pathways P value Mitochondrial L-carnitine shuttle pathway 3.24E-03

Signaling by Rho family GTPases 6.56E-03

Virus entry via endocytic pathways 1.02E-02

Mitochondrial dysfunction 1.09E-02

RhoGDI signaling 1.13E-02

IPA  analysis  

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Canonical pathways P value Mitochondrial L-carnitine shuttle pathway 3.24E-03

Signaling by Rho family GTPases 6.56E-03

Virus entry via endocytic pathways 1.02E-02

Mitochondrial dysfunction 1.09E-02

RhoGDI signaling 1.13E-02

IPA  analysis  

Jan 2016

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Canonical pathways P value Mitochondrial L-carnitine shuttle pathway 3.24E-03

Signaling by Rho family GTPases 6.56E-03

Virus entry via endocytic pathways 1.02E-02

Mitochondrial dysfunction 1.09E-02

RhoGDI signaling 1.13E-02

IPA  analysis  

Jan 2016

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Of  course,  all  of  this  needs  to  be  reproduced!!!  

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La  quête  du  Graal?  

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Conclusion  •  Epigenomics  offers  great  opportuni)es  for  understanding  auto-­‐immune  diseases  (and  iden)fying  novel  biomarkers)  

•  Success  predicated  on  high-­‐quality  data  

•  Cri)cal  need  for  collabora)ons  because  of  rela)ve  rarity  of  diseases  and  complexity  of  science   Gourley M, Miller FW. Nat Clin Pract Rheumatol (2007).

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Acknowledgements  JGH  Murray  Baron  

LDI  Celia  Greenwood  Kathleen  Klein  Greg  Voisin  Aurélie  Labbe  

MUHC  Ines  Colmegna  Sasha  Bernatsky  

McGill  GQIC  Tomi  Pas)nen  

McGill  MDTC    Joaquim  Madrenas  Corinne  Maurice      

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Poten)al  for  discovery  

•  Many  genes  and  pathways  iden)fied  were  related  to  other  biological  func)ons    –  cellular  cytoskeleton,  including  SYNOP2,  LIMA1,  KIF13B  and  ZMYM4    –  cell  trafficking,  including  CEP97  (over-­‐expressed)  and  CCDC40  (under-­‐

expressed).  

•  This  is  in  contrast  to  GWAS  studies  that  have  iden)fied  genes  of  relevance  predominantly  for  immune  func)on  only  and  provides  novel  cellular  targets  of  interest.  

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Human trait variation.(A) Differences in a human trait (such as height) are partly due to the combined effects of genetic variants that alter the expression of multiple genes.

Terrence S. Furey, and Praveen Sethupathy Science 2013;342:705-706

Published by AAAS

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C57BL/6 mice – lupus resistant

C57BL/6 x SJL mice – lupus susceptible

Inbred ERK signalling defect

Methyl-supplemented diet

Slight Increase in dsDNA

Significant increase in dsDNA

Kidney disease on standard and MR but not MS diet

Standard diet Kidney disease only on MR but not standard and MS diet

Methyl-restricted diet

DNA  methyla)on  and  diet  

Strickland, Richardson. A and R 2013.

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