Régulation homéostatique du sommeil Synthèse circadien-homéostatique

Christelle Monaca-Charley

DIU Veille-Sommeil 2013

Absence de conflit d’intérêt sur le thème du cours

0

500

1000

1500

2000

10:00 12:00 14:00 16:00 18:00

Latence

Heure début période

Tests de latence d’endormissement

Grande variabilité du sommeil d’un individu à l’autre

Nombreux modèles de régulation du sommeil

Les rythmes circadiens

Synchroniseurs sociaux Alternance lumière-obscurité

Noyaux supra-chiasmatiques

Rythmes sécrétions glandulaires Rythmes température,

Cortisol Mélatonine

Rythme veille sommeil

Influence des gènes

Régulation circadienne

Modèle des oscillateurs

Modèle à 2 oscillateurs

Oscillateur fort

Oscillateur faible

Mais limites de ce modèle…

Modèles basés sur la régulation circadienne et homéostatique

Processus de régulation du sommeil

•  3 processus: - circadienne (processus C) - homéostasie (accumulation d’une dette de sommeil) (processus S) - ultradienne (rythme de 90 min: alternance SL et SP)

modèles de régulation du sommeil (modèle de l’alternance veille sommeil)

Régulation homéostasique

Activités à ondes lentes •  = « slow wave activity » •  = indicateur physiologique de l’homéostasie du

sommeil lent •  Sommeil lent (NREM sleep) = sommeil lent de

type 2, 3 •  Scoring selon la quantité d’ondes lentes •  Si analyse fine du signal : slow wave activity •  Correspondrait à l’activité delta (0,5 à 4 Hz) en

analyse spectrale + signal de très basse fréquence (0,7 à 0,8 Hz)

•  Dès 1937, il a été reconnu que l’intensité du sommeil pouvait être mise en évidence par la quantité d’ondes lentes sur l’EEG.

•  Plus il y a d’ondes lentes, plus la réponse aux stimuli diminue (seuil d’éveil élevé).

•  Ondes lentes : reflet de la profondeur (ou de l’intensité) du sommeil

Activités à ondes lentes

Evolution des ondes lentes au cours de la nuit

Etudes des siestes

•  Siestes en fin d’AM contiennent plus d’ondes lentes que celles de début de journée

•  Si nuit de courte durée, sieste de début de journée: plus d’ondes lentes

Privations de sommeil

•  Si privation de sommeil (totale ou partielle): augmentation du SL la nuit suivante.

•  De la même façon, augmentation des ondes lentes

•  Augmentation fonction de la durée de la période d’éveil

SWA

36 heures d’éveil

Si éveils durant la 1ere partie de nuit, décalage dans le temps des ondes lentes

•  Toutes ces données suggèrent donc que les ondes lentes ne sont pas un épiphénomène mais qu’elles reflètent bien un mécanisme de régulation du sommeil

Autre marqueur…

•  Puissance du rythme théta durant l’éveil

Existe-t-il une homéostasie pour le sommeil paradoxal? (comme pour le

sommeil lent) •  Privation totale de sommeil :

–  rebond immédiat de SL (et de SWA) –  Pour le SP : soit rebond retardé, soit absent

•  Privation sélective de SP: –  Rebond observé –  Mais moins important qu’attendu –  Survient en 2de partie de nuit (quand la « pression en

SWA » diminue)

Régulation différente homéostasie du SP dépend de celle du SL

Existe-t-il un indicateur électro-physiologique pour l’homéostasie du SP ?

•  Densité des mouvements oculaires : NON •  Diminution de l’activité alpha en sommeil

paradoxal durant la (ou les) nuit(s) de récupération : résultats variables

Régulation ultradienne

Régulation ultradienne des ondes lentes et des « fuseaux »

•  Rythme < 24h •  « Spindle frequency activity » (12-15 Hz) :

évolution en forme de U •  Evolution ultradienne différente entre ces

activités et les ondes lentes

SWA

fuseaux

36 heures d’éveil

Si éveils durant la 1ere partie de nuit, décalage dans le temps des ondes lentes

SWA

Fuseaux (activités dans la bande de fréquence 12-15 Hz)

•  Pourquoi cette différence? – Les oscillations EEG = reflet de l’activité

thalamo-corticale – Durant la transition veille-sommeil:

hyperpolarisation progressive neuronale : initialement dans la bande de fréquence des fuseaux puis dans celle des SWA : d’où l’aspect en U

Interactions entre les processus circadien et homéostatique

•  Ces 2 processus peuvent être manipulés indépendamment l’un de l’autre : processus indépendants

•  Protocole de désynchronisation forcée (sujet mis sur un rythme de 28h): – Endormissement le plus facile quand proche du

minimum thermique – Endormissement le plus difficile quand 16h

après minimum thermique

– SWA : reflet de l’homéostasie (donc dépendant de l’éveil et du sommeil)

– Ratio REM/NREM : sous le contrôle de l’homéostasie et du circadien

Modèle à 2 processus Processus S

Processus C

Permet d’expliquer notamment : - le rebond après privation, - le sommeil des travailleurs postés, -  court et long dormeur

Long dormeur

Court dormeur

Début de nuit: importance de la pression homéostatique

Modèle à 3 processus

« Hypothèse » pour le système homéostasique

•  Adénosine : Produit de dégradation de l’ATP

•  2 types de récepteurs de type 1 et 2 •  Accumulation d’adénosine pendant l’éveil.

Adénosine

Landolt et al., 2008

Bjorness et al., 2009

« Hypothèse » pour le système homéostasique

•  Adénosine : Produit de dégradation de l’ATP

•  2 types de récepteurs de type 1 et 2 •  Accumulation d’adénosine pendant l’éveil. •  Si adénosine injectée dans le tronc cérébral :

initiation du sommeil •  Antagoniste des récepteurs de l’adénosine :

théophylline et caféine

Ces 2 systèmes sont-ils réellement indépendants ?

Pour résumer…

Franken and Dijk, 2009, EJN

Franken and Dijk, 2009, EJN

Altération homéostasie

Autres modèles génétiquement modifiés

•  Bmal1: TST, fragmentation sommeil, SWA

•  Clock: SWS, SWA •  …

PER 3

•  Différents polymorphismes: 5/5; 4/4 •  PER 3 5/5: sommeil avec des caractéristiques

similaires à celles retrouvées chez des sujets du matin: –  Latence d’endormissement courte –  + de SLP –  + de SWA, notamment durant la 1ère partie de la nuit –  Sommeil ressemblant à un sommeil de récupération

après une privation de sommeil.

Viola et al., 2007

Viola et al., 2007

Dijk et Archer, 2009

Franken et Dijk, 2009

Pour conclure…. •  Modèle de Borbely n’est pas aussi simple •  Intrication des différents processus de

régulation du sommeil •  Pour compliquer: homéostasie différente

d’une région à l’autre

Implication de ces modèles pour comprendre les modifications du

sommeil liées à l’âge?

A l’adolescence

Adolescent Regulation of Sleep Dev Neurosci 2009;31:276± 284 281

ity to the phase-delaying effects of light would also cause the pacemaker to delay relative to the light cycle ( fig. 1 , model B) [39] . To provide a preliminary test for this hy-pothesis, the suppression of melatonin secretion by 1-hour light pulses was examined in early pubertal and late pubertal human adolescents. The photic suppression of melatonin secretion is mediated by the same pathways in the SCN as the discrete resetting of circadian rhythms [50] . Late adolescents were significantly less sensitiveto dim light exposure (15 lx) in the morning (03: 00±04: 00 h) than early adolescents, suggesting that a change in the shape of the PRC may have occurred during pu-berty [50] . Furthermore, adolescent humans (ages 15± 17 years) still showed a phase delay of endocrine rhythms (dim light melatonin onset phase) on a weekend schedule that provided bright morning light exposure [51] . These studies suggest that pubertal humans may have a blunted phase advance response to light exposure in the morning

and an exaggerated phase-delay response to light expo-sure in the evening.

In the animal literature, one previous study character-ized the PRC of pubertal female mice (49 days of age), late pubertal (63 days of age) and adult mice [52] . When we compare the data of 49-day-old (P49) pubertal mice to the older animals ( fig. 2 ), an interesting trend emerges. The phase-delay portion of the PRC has greater amplitude in the P49 pubertal mice. The phase advance and daytime portions of the PRC also appear to have a different shape, but it is difficult to draw conclusions due to the few sam-ple points from these times. An earlier study showed that pubertal mice (42 days of age) adjust to a phase delay of the light-dark cycle much faster than adult mice [18] . These results suggest that pubertal animals may be rela-tively more sensitive to the circadian phase-delaying properties of light.

Entrainment of the Circadian Pacemaker Is Not the Only Determinant of the Final Phase of Circadian Output. Substantial evidence now indicates that adult diurnal and nocturnal species have a similar phasing of many aspects of SCN physiology [53, 54] . For example, the phase of the transcriptional-translational clock gene feedback loop in the SCN that generates 24 h of oscillation is very similar in the nocturnal rat and diurnal degu [55] . The phasing of clock gene expression relative to the environmental light cycle is thought to reflect the entrainment of the cir-cadian pacemaker [56] . Rhythms in deoxyglucose metab-olism, photic sensitivity , and neuropeptide expression (e.g. AVP and VIP) in the SCN are also similar in diurnal and nocturnal species [53, 54] . Therefore, the down-stream coupling (or phase relationship) between the cir-cadian pacemaker and central or peripheral systems plays an important role in determining the phase of behavior-al and endocrine rhythms. To determine whether the de-lay in circadian phase during puberty is caused by a change in the phase of the circadian pacemaker in the SCN, the Lee laboratory has begun to characterize the phasing of the clock gene expression in the SCN of puber-tal degus and rats.

The Developmental Changes Driving Adolescent Sleep Patterns

A number of studies provide strong support that the homeostatic and circadian regulation of sleep are sensi-tive to gonadal hormones. As this evidence has been ex-tensively reviewed elsewhere [57± 60] , we only briefly summarize it here. Activational (direct, transient) effects

± 250

± 100

± 150

± 200

± 50

00 2

Circadian time (Ascho! I)

Phas

e sh

ift (m

in)

4 6 8 10 12 14 16 18 20 22 24

50

100

150

P140P49

Fig. 2. Pubertal mice exhibit an exaggerated delay in circadian phase in response to evening light. Female mice were placed into constant darkness (DD) for two weeks and then exposed to a 15-min light pulse (150 lx). Circadian phase shift in response to the pulse was calculated in reference to sham (no pulse) conditions, and circadian time was defined in reference to the activity rhythms of the individual mice (activity onset = CT12). Therefore, unlike figure 1, if pubertal animals have a delay in the phase of the cir-cadian pacemaker, the phase of the PRC would not be delayed in this figure. The dotted line represents the phase response of mice that were likely to be pubertal at the time of the light-pulse (P49, n = 34) and the dark line represents the phase response of adults (P140, n = 34). Each point represents the average phase shift pro-duced by light presented during a 1.5-hour bin. The sample size for each bin is represented by the size of the data point (n = 1± 8). Adapted from Weinert and Kompauerova [52] .

Hagenauer /Perryman /Lee /Carskadon

Dev Neurosci 2009;31:276± 284280

the entrainment of diurnal mammals [41] . Since these ef-fects are long-lasting, the aftereffects of photoperiod on ! can often be observed for days after transferring an ani-mal into constant conditions [42] .

If changes in circadian entrainment underlie pubertal changes in the circadian phase, then the magnitude of phase change should be sensitive to the quality and inten-sity of the synchronizing cue. This appears to be the case. Research from the fat sand rat indicates that a greater magnitude of phase change during development occurs under conditions of short photoperiod (shorter duration of light per day) than with long photoperiod [20] . Pre-liminary evidence from the degu also suggests that the magnitude of pubertal phase change is sensitive to light-ing intensity [43] . What happens during puberty to pro-duce a phase delay?

An elongated ! would cause the circadian pacemaker and its rhythmic output to delay relative to the light cycle [39] ( fig. 1 , model A). In support of this hypothesis, hu-man adolescents have a ! of 24.27 h, a period length sig-nificantly longer than that found in adults (24.12 h) using similar protocols [8, 44] . Longitudinal research to better test this hypothesis is currently underway in the Carska-don laboratory.

Data from rodents are inconsistent with this human finding. Pubertal ! in male rats was longer than the adult period [17] : however, later work suggests that this change may be sex-specific and unrelated to pubertal changes in phase [Possidente et al., unpubl. data]. Similarly, a careful developmental analysis of the degu did not find changes in ! during puberty at the age of the delay in entrained phase [13] .

Enhanced Light-Elongation of ! . This discrepancy be-tween the results of human, rat, and degu studies might be explained by the presence or absence of light exposure during the free-running protocols. The pubertal rodents were exposed to constant darkness (DD, [13] ) or very dim red light (0.1 lx RR [17] ) while ! was measured. Whereas humans were exposed to a light cycle (LD; 20 vs. 0 lx) with a day length (T) that was outside of the range of entrain-ment for the circadian system (T = 28 h) [44] . Previous experiments have shown that light exposure can lengthen free-running period in five species that have pubertal phase delay [45± 49] . Therefore, ! may not be longer dur-ing puberty, but the circadian pacemaker may be more sensitive to the continuous effects of light. In support of this hypothesis, aftereffects of photoperiod on ! are more prolonged in pubertal than adult rodents [13, 43] .

Increased Sensitivity to the Phase-Delaying Effects of Light. An increase in the circadian pacemakerí s sensitiv-

Fig. 1. Two potential mechanisms underlying delayed circadian phase during puberty. These mechanisms are illustrated using a PRC depicting the circadian phase response of male degus to a light pulse presented at different times of the day. Phase shift mag-nitude is graphed in hours, with positive values indicating phase advance, and negative values indicating phase delay. Time of day is graphed in reference to the former light cycle (zeitgeber time, lights on during ZT 0± 12). Therefore, if pubertal animals have a delay in the phase of the circadian pacemaker, then the phase of the PRC would also be delayed in these models. Model a : An elon-gation of ! during puberty would cause the circadian pacemaker and its rhythmic output to phase delay relative to the light cycle. The delay would provide more light exposure at a phase when the pacemaker is sensitive to advancing phase shift and thus allow entrainment (because ! ± 24 h = " , with " representing the mag-nitude of necessary daily phase resetting). Model b: An increase in the circadian pacemakerí s relative sensitivity to the phase-de-laying effects of light would also cause the pacemaker to delay relative to the light cycle. This delay would result because the pacemaker would need more light exposure at a phase when it is sensitive to advancing phase shift.

6

b

± 1.5a

± 1.0

± 0.5

0± 6 ± 4 ± 2 0 2

Zeitgeber time

Daily light exposure

Phas

e sh

ift (+

= a

dvan

ce)

4 6 8 10 12 14 16 18 20 22 24 26

0.5

1.0

1.5

2.0

± 1.5

± 1.0

± 0.5

0

0.5

1.0

1.5

2.0

Daily light exposure

PubertalAdult

PubertalAdult

Zeitgeber time

Phas

e sh

ift (+

= a

dvan

ce)

2 4 8 10 12 14 16 18 20 22 24 26± 6 0± 2± 4

Lors du vieillissement

M Munch et al., 2007

SLEEP, Vol. 30, No. 6, 2007 783

the study, nor did they know how long any of the sleep and wake episodes lasted.

Sleep Recordings and Data Analysis

Sleep episodes were polysomnographically recorded using the Vitaport Ambulatory system (Vitaport-­3 digital recorder TEMEC Instruments BV, Kerkrade, the Netherlands). Twelve EEG deriva-­tions (F3, F4, Fz, C3, C4, Cz, P3, P4, Pz, O1, O2, Oz referenced against linked mastoids), two electrooculograms, one submental electro-­myogram, and one electrocardiogram were recorded. All EEG sig-­nals were filtered at 30 Hz (fourth-­order Bessel-­type antialiasing low-­pass filter, total 24 dB/Oct), and a time constant of 1.0 second was used prior to online digitization (range 610 μV, 12 bit AD converter, 0.15 μV/bit;; storage sampling rate at 128 Hz). The raw signals were stored online on a Flash RAM Card (Viking, Rancho Santa Margarita, Calif) and downloaded offline to a PC hard drive. All sleep episodes were visually scored on a 20-­second epoch ba-­sis according to standard criteria.32 EEGs were subjected to spec-­tral analysis using a fast Fourier transform (10% cosine 4-­second window), which resulted in a 0.25-­Hz resolution. EEG artifacts were detected by automated artifact-­detection software (CASA, 2000 Phy Vision BV Kerkrade, The Netherlands). Artifact-­free 4-­second epochs were averaged over 20-­second epochs and matched with the 20-­second epochs of the visual sleep scoring. Sleep stages (1-­4), rapid eye movement (REM) sleep, wakeful-­

ness, and movement time (MT) were expressed as percentage of total sleep time (TST) during the respective night for all partici-­pants (∑ stages 1-­4, REM sleep). TST and sleep latencies and REM sleep latency (RL) were indicated in minutes. All sleep latencies (latency to stage 1[SL1], latency to stage 2 [SL2], RL) were log-­transformed before statistical analysis. Sleep efficiency (SE) was defined as follows: SE = TST/time between lights off and lights on x 100. Wakefulness after lights off (WALO;; % of TST) and wake-­fulness after sleep onset (WASO;; % of TST) were also measured. Non-­rapid eye movement (NREM) sleep was defined as stages 2 to 4 (% of TST). In order to compare sleep stages during the 10 naps with those in the baseline night, all sleep stages were additionally expressed as percentage of TST during the baseline night.EEG spectra during the baseline and recovery nights were cal-­

culated in the frequency range from 0.5 to 25 Hz for the mid-­line derivations (Fz, Cz, Pz, and Oz) on log-­transformed data. The recovery night values were expressed as percentage of baseline mean. For graphical illustration, the log-­transformed mean val-­ues per participant were averaged for each age group separately and then retransformed. Sex differences in EEG power density were assessed by repeated-­measures ANOVAs (rANOVA), which yielded a significant 3-­way interaction (sex × age group × deri-­vation) for relative EEG power density in the frequency range between 0.5 and 1 Hz (3-­way rANOVA;; F3,81 > 2.8, P < 0.05). However, posthoc comparisons (Duncan’s multiple range test) between men and women for the different EEG derivations and age groups revealed no significant sex differences in this frequen-­cy range (0.5-­1 Hz;; P >0.1).NREM/REM sleep cycles were defined according to the criteria

of Feinberg and Floyd,33 with the exception that, for the last sleep cycle, no minimum REM-­sleep duration was required. Thereafter, each sleep cycle was divided into 10 equal time intervals during NREM sleep and 4 equal time intervals during REM sleep. Accumulated SWA was binned into 15-­minute intervals during

11 naps (the first 75 minutes of the recovery night were consid-­ered as an additional nap) and into 30-­minute intervals for base-­line and recovery nights, respectively. Accumulated SWA was expressed as percentage of baseline means for all participants (during NREM sleep;; for Fz). The rANOVA for SWA accumula-­tion during baseline and recovery nights was done for the first 7 hours (in order to include all participants in the analysis). To investigate the decay of EEG delta-­power density (0.5-­1.25

Hz) across the baseline and the recovery night in young and older volunteers, an exponential decay function was fitted to the data of all participants and NREM cycles: delta = delta0 x e

(-­rt);; with delta0 = intercept on the y axis, delta = mean EEG delta power per sleep cycle, r = slope of the decay, t = average timing of the cycle midpoint.To evaluate the lowering of sleep pressure in both age groups,

we simulated the homeostatic build-­up of sleep pressure across the baseline night, 10 naps, and the recovery night with an ex-­ponential rising component of process S during wakefulness and an exponential decay rate during sleep 1,8 (data not shown). The simulation included all sleep stages and REM sleep, and was per-­formed based on the formula: Asim,t = Smax-­(Smax-­ Asim,0)× exp

(-­t/τ). Asim,t is the simulated value of Process S at time t, Asim,0 the initial value at time 0, and Smax represents the asymptote of the exponen-­tial function. The time constant was 18.8 hours during wakeful-­ness and 4.2 hours during sleep, according to 1,8. The simulations were based on the 20-­second epoch visual-­scoring data. For the

Time of Day (h)

24 8 24 16

Day 1 BL 1

Day 3

Day 4 REC

Sleep (0 lux)

Wakefulness (<8 lux)

Constant posture in bed

Day 2 BL 2

Figure 1—Schematic illustration of the study protocol with two 8-­hour baseline (BL) sleep episodes, ten 75-­minute naps and one 8-­hour recovery sleep episode (REC). Black bars (0 lux) indicate scheduled sleep episodes and white bars episodes of scheduled wakefulness (< 8 lux). Hatched bars delineate the time of controlled posture position (semirecumbent during wakefulness and supine during sleep).

Homeostatic Sleep EEG Changes with Aging —Munch et al

SLEEP, Vol. 30, No. 6, 2007 788

estimation of the delta decay rates during the recovery night per-­formed for Fz, Cz, Pz and Oz revealed R-­values ≤ 0.5 for both age groups (for Fz see Table 2). Figure 6A shows the accumulated relative SWA (percentage

of baseline mean;; on a log-­scale) during the first 7 hours of the baseline and recovery sleep episode (30-­minute intervals;; n = 16 for the young and n = 15 for the older group). There was no sig-­nificant interaction between the factors age × night × time interval (3-­way rANOVA;; P > 0.2), nor any other interaction with the fac-­tor age.

Baseline Night vs Naps

The accumulation of relative SWA (percentage of baseline mean) within 11 naps (nap 11 = first 75 minutes of recovery night) is shown for both age groups across 15-­minute intervals in Figure 6B. In the older group, significantly higher SWA values were found

in three time intervals during the first nap and in two and three time intervals, respectively, during nap 4 and 10 (coincided with the wake maintenance zone in the evening), as well as during nap 6 and 7. Lower relative SWA occurred in the older participants dur-­ing nap 5 (P < 0.05;; all Mann-­Whitney U test and corrected for multiple comparisons). Young participants had, on average, signifi-­cantly more accumulated SWA across the nap sleep episode than the older group (P < 0.05;; 1-­way ANOVA with mean values of accumulated SWA during 10 naps for Fz ;; F1,29 = 11.8, on log-­ratios;; n = 16 for the young and n = 15 for the older).

DISCUSSION

We have investigated the impact of low sleep pressure on sleep structure and spectral components of the sleep EEG in young and older volunteers. The main differences in the spectral EEG com-­ponents between the age groups across the entire recovery night

24

Figure 5

Older

0 2 4 6 8

EEG Delta Pow

er Density (%

of B

L mean)

0.0

0.5

1.0

1.5

2.0

Hours since Sleep Onset (h)

0 2 4 6 8

0.0

0.5

1.0

1.5

2.0

Young

BLREC

-­-­-­-­__

Figure 5—Fitted exponential decay function [delta = delta0 x e(-­rt)] to relative EEG delta power (0.5-­1.25 Hz;; percentage of baseline night) NREM

sleep across all NREM sleep episodes for Fz. Left-­hand panel: young (n = 16), right-­hand panel: older participants (n = 15). Open circles and dashed lines indicate baseline (BL) night values, and, filled circles together with solid lines, the values for the nonlinear regression during the recovery (REC) night (one data point of a younger participant during the baseline night is not shown, was denoted as an outlier, see results).

Table 2—Nonlinear Regression Analysis for the Decay of EEG Delta Power During Baseline and Recovery Nights in Young and Older Partici-­pants

Young Older

Baseline Recovery Baseline Recovery

Estimated Decay Rate, /h 0.209 ± 0.018 0.119 ± 0.024 0.144 ± 0.017 0.074 ± 0.0295% Confidence Interval 0.174-­0.244 0.072-­0.166 0.111-­0.177 0.035-­0.113R value 0.85 0.53 0.75 0.44P < 0.05 * ** * ** * ** *

Parameters of the nonlinear regression analysis for the decay of EEG delta power during baseline and recovery nights for both age groups are indicated for Fz during all NREM sleep episodes (mean of all cycles ± SEM). The 95% confidence intervals are shown for both age groups and nights;; *indicates the lack of overlap of mean values with the 95% confidence intervals between baseline and recovery night within the respective age groups and **between young and older volunteers for the baseline and recovery night (P < 0.05).

Homeostatic Sleep EEG Changes with Aging —Munch et al

Implication de ces processus de régulation en pathologie

Troubles du rythme circadien

•  Liés à l’environnement : - Travail posté - Jet-lag

•  Troubles endogènes : - Syndrome de retard de phase - Syndrome d’avance de phase - Rythmes hypernycthéméraux - Absence de rythme

Travail posté

Troubles du rythme circadien

•  Liés à l’environnement : - Travail posté - Jet-lag

•  Troubles endogènes : - Syndrome de retard de phase - Syndrome d’avance de phase - Rythmes hypernycthéméraux - Absence de rythme

Anomalies de fonctionnement du processus circadien

Troubles de l’hygiène veille sommeil •! Perturbation de l’homéostasie du sommeil? •! De l’horloge?

Homéostasie et pathologie du sommeil : un exemple

CAS CLINIQUE

•  JF de 18 ans •  Apparition d’une SDE depuis 1 an •  Difficultés le matin pour se lever +++ •  Siestes prolongées quand cela est possible •  Céphalées fréquentes •  Difficultés scolaires liées aux retards répétés et aussi

à la difficulté de concentration en cours •  Pas de cataplexie •  Pas d’hallucination ni de paralysie du sommeil •  Pas de traitement actuellement, ni de prise de

toxiques

Temps de sommeil minimal : 11 heures/ 24 heures

Sieste

TTS >10 h

Heure

Début d’enregistrement (lumières éteintes) 22:01 Temps au lit (min) 715 Endormissement 22:07 Période de sommeil

(min) 697 Eveil final 09:44 Temps total de

sommeil (min) 660 Fin d’enregistrement (lumières allumées) 09:56

Latences (min) Stade 1 6.0 Stade 2 7.5 SWS 9.5 REM 118.5

Temps passé en chaque stade de sommeil

(min) (% du TST) Stade 1 28 4.3 Stade 2 203 30.8 SWS 282 42.7 REM 146 22.1 Eveil (après endormissement) 49 8.4 Temps total de sommeil (TST) 660 100.0

•  Alternance veille sommeil ne se fait plus normalement

Conclusion

•  Existence de différents processus de régulation de l’alternance veille sommeil

•  Fonctionnent l’un avec l’autre et non pas en parallèle

•  Mais nécessité qu’ils soient en phase pour permettre un sommeil et un éveil de bonne qualité

•  Nombreuses pathologies du sommeil liées à un trouble de la régulation du sommeil

•  Fonctions du sommeil…