1 CIRCADIAN RHYTHMS Association between Delayed Sleep Phase and Hypernyctohemeral Syndromes: a Case Study Diane B. Boivin, MD, PhD 1 ; Okan Caliyurt, MD 1 ; Francine O. James, MSc 1 ; Colin Chalk, MD, CM, FRCPC 2 1Center for Study and Treatment of Circadian Rhythms, Douglas Hospital Research Center, Montreal, Qc, Canada. Department of Psychiatry, McGill University, Montreal, QC, Canada; 2 Department of Neurology and Neurosurgery, Montreal General Hospital, McGill University, Montreal, QC, Canada Study Objective: We investigated whether the hypernyctohemeral syndrome (non 24-hour sleep-wake syndrome) may show a clinical association with the delayed sleep phase syndrome (DSPS) in a 39-year-old woman who developed sleep disturbances following a traumatic brain injury. Measurements and Results: Sleep-wake log documentation and wristactivity recordings for more than 6 consecutive months confirmed the patient s tendency to live on longer-than-24-hour days. Episodes of relative coordination to the 24-hour day were also noted, suggesting that the patient was transiently in and out of phase with environmental synchronizers too weak to fully entrain her to the geophysical environment. Interestingly, we noted a tendency to initiate sleep between 3:00 am and 5:00 am and wake up from sleep between noon and 1:00 pm. Conclusions: These results support an association between the hypernyctohemeral syndrome and the DSPS. This association may carry implications for the treatment of circadian rhythms disorders. Key Words: Delayed sleep phase syndrome, non 24-hour sleep-wake disorder, brain injury. Citation: Boivin DB; Caliyurt O; James FO; Chalk C. Association between delayed sleep phase and hypernyctohemeral syndromes: a case study. SLEEP 2004;27(3): INTRODUCTION Disclosure Statement No significant financial interest/other relationship to disclose. Submitted for publication March 2003 Accepted for publication December 2003 Address correspondence to: Diane B. Boivin, MD, PhD, Center for Study and Treatment of Circadian Rhythms, Douglas Hospital Research Center, 6875 LaSalle Boulevard, suite F-1127, Montreal, Québec, Canada H4H 1R3; Tel: (514) ext. 2397; Fax: (514) ; SLEEP, Vol. 27, No. 3, IN 1971, ELIOTT AND COLLEAGUES 1 PUBLISHED THE FIRST CASE STUDY OF A MAN LIVING ON 26-HOUR DAYS. Since then, similar cases have been described in either blind patients 2-7 or in patients with introvert personality and schizoid personality disorders For instance, Miles and colleagues 2 described the case of a psychologically healthy 28-year-old blind man, actively working, with severe and cyclic sleep-wake disturbances. Circadian rhythms of core body temperature, alertness, performance, cortisol, and urinary electrolytes excretion were free running with a period longer than 24 hours. The patient suffered from insomnia and excessive daytime sleepiness at approximately 20- week intervals. When sleep times were self-selected, he spontaneously adopted a sleep-wake cycle of 24.9 hours and was asymptomatic. A few cases of non 24-hour sleep-wake syndromes have been reported following traumatic brain injury or in brain-damaged children For instance, Okawa and colleagues 11 reported the case of a severely brain-damaged 12-year-old boy with an apparent non 24-hour sleepwake syndrome. His sleep disturbances appeared to cycle every 10 to 15 days with no obvious periodic changes in his cortisol rhythm. The diagnosis in this case is unclear, since analysis of the sleep-wake cycle shows a rather consistent 24-hour rhythm with some periods of desynchronization. This last report is not unusual because several cases of reported Hypernyctohemeral syndrome appear to have many characteristics of a delayed sleep phase syndrome (DSPS). Indeed, sleep-wake logs often simultaneously report long disrupted days and substantial periods where 24-hour rhythmicity is observable. It has been proposed that, in sighted individuals, the hypernyctohemeral syndrome might be a more severe form of DSPS. 17 Interestingly, some cases of DSPS have converted to a non 24-hour sleep-wake syndrome after chronotherapy on a 27-hour day. 16,18 The aim of the present study is to explore the association between DSPS and the hypernyctohemeral syndrome in a 39-year-old woman who developed sleep disturbances following traumatic brain injury. CASE DESCRIPTION In 2000, a 39-year-old woman was referred to our sleep clinic (DBB) by her neurologist (CC) for severe and cyclic sleep disturbances. In 1991, she suffered head trauma in a car accident that initially left her unconscious. In the months following the accident, she showed globally impaired cognitive function with deficient verbal and nonverbal memory. Four years after the accident, the patient had a brief depressive episode with suicidal ideation. A psychiatric evaluation performed then, and 2 years later, suggested features of a schizoid personality disorder. At the time of evaluation, the patient was pleasant and cooperative. In parallel with cognitive changes, the patient reported episodes of altered behavior and amnesia, possibly suggesting partial seizures. Her past medical history was notable for migraine, which began at age 25 years. At the time of referral, she was treated with valproate 375 mg twice per day as prophylaxis and oral morphine tablets (5 mg) as needed, roughly once per week. Symptoms of a sleep disorder were recognized a few years following the accident. The patient noticed being unable to maintain stable sleep times and tended to delay her bedtime later from one day to the next. Attempts to adopt a regular sleep schedule led to nighttime sleep disruption and daytime fatigue that resulted in a worsening of her headaches. She then decided to follow her natural tendency to live on longer than 24-hour days and reported some improvement of her sleep disruption. Upon her interview in our sleep disorder clinic in 2000, she reported no sleep or circadian-rhythm disturbances preceding the accident. No symptoms suggestive of periodic limb movements in sleep, sleep apneas and hypopneas, or parasomnias were reported, and these were ruled out by a polysomnographic recording in the sleep laboratory. Magnetic resonance imaging of the brain, with special attention to the hypothalamus and suprachiasmatic area, as well as an ophthalmologic examination, both performed in 2000, were normal.
2 INVESTIGATION OF SLEEP DISORDER Throughout the ambulatory investigation, the patient was instructed to follow her natural tendency to sleep. She thus went to bed and woke up at times of her own choosing, a condition that was consistent with her daily habits. Sleep times were confirmed by sleep-wake logs and by wrist actigraphy recording from the nondominant wrist (AW-64 monitor, Mini-Mitter, Bend, Oregon, USA) for more than 6 consecutive months. Ambulatory recordings were occasionally interrupted at the patient s request. Sleep-onset and -offset times were determined by a softwarederived algorithm (Sleepwatch, Mini-Mitter) based on the patientreported bedtimes. Only sleep episodes identified as main sleep episodes were included in our analyses. First, the sleep-wake pattern was double-plotted for visual inspection (Figure 1A). Descriptive statistics were then used to elucidate the patient s sleep-wake behavior. The frequency distributions of sleeponset and -offset times, as well as the likelihood of being asleep were determined as a function of time of day (Figure 1B, C, D). Sleep-wake cycles were defined as cycles of a main sleep episode followed by the waking episode preceding another main sleep episode. A frequency distribution of the length of the patient s sleep-wake cycles was also determined as a function of time of day (Figure 2A, B). In order to quantify the cycle length of the patient s sleep-wake behavior, we performed a fast Fourier transform analysis of all documented main sleep episodes (Figure 3). To this end, we selected the longest uninterrupted data train of sleep behavior (108 consecutive days). The sleepwake cycle was treated as a binary file (0 = asleep and 1 = awake). The analyses were performed using Matlab (The MathWorks, Natick, Mass, USA) considering a sampling rate of 1 sample per minute. We also documented the levels of illumination to which the patient was exposed. For a 25-day period beginning in late May 2001, the patient kept self-selected sleep times. Light levels were sampled every 2 minutes via a wrist-worn combined activity and light sensor (Actiwatch- L, Mini-Mitter). We first determined the patient s pattern of light exposure throughout the day by determining mean levels of ambient light intensity using 1-hour bins. Results were averaged into hourly bins starting at her reported time of awakening from main sleep episodes. Binned values were then analysed using analysis of variance (ANOVA) for repeated measures. In order to characterize the nature of light to which the patient was exposed, we determined the proportion of the patient s wake episodes spent in each of 4 illumination ranges: (1) < 1 lux; (2) 1 to 100 lux; (3) 100 to 1,000 lux; (4) > 1,000 lux (Figure 4A). We also calculated the mean number of minutes of the period of awakening spent in bright light (> 1,000 lux) using 4-hour bins (Figure 4B). Both of these approaches were used in prior studies 19 and allowed us to compare our patient s results to normative data reported for healthy young research subjects. RESULTS Visual inspection of the patient s sleep-wake log, expressed as a double-raster plot, demonstrated an irregular sleep-wake pattern with a tendency to delay bedtimes from one day to the next (Figure 1A). Sleep episodes were distributed throughout the day, with a clustering of sleep onsets between 3:00 and 5:00 AM and sleep offsets between noon and 1:00 PM (Figure 1B and 1C). Indeed, the frequency of occurrence of sleep onsets and offsets at these specific times of day exceeded the upper limit of the 95% confidence interval describing the mean frequency dis- Figure 1 (A) The patient s sleep habits over a 6-month period in Sleep episodes are shown as black bars, and are double-plotted for clarity. Sleep times were confirmed by wrist actigraphy recording and analyzed by a software-derived algorithm (AW-64 monitor and Sleepwatch software, Mini-Mitter, Bend, Oregon, USA). Frequency of temporal distribution of sleep onset (B) and sleep offset (C) throughout the day, as determined from sleep logs and plotted in 1-hour bins. Within panels B and C, dotted lines represent the upper limit of the 95% confidence interval (mean +2 SD) describing the number of observations. (D) Percent probability of the patient being asleep at particular times of day. The dotted line represents the median value of this probability. SLEEP, Vol. 27, No. 3, Figure 2 (A) Distribution of sleep-wake cycle length, plotted with a 15-minute resolution. A sleep-wake cycle is defined as a sleep episode, reported as a main sleep episode by the patient, immediately followed by a waking episode. Analyses excluded sleep episodes reported as naps. Descriptive statistics were used to determine the duration of our patient s sleep-wake cycles. (B). Sleep-wake cycles (hatched) with mean duration withing 1 SD of the initial mean cycle length were included; associated wake periods (white), and sleep periods (black) were plotted with a 60-minute resolution. The sharp peak at 24 hours observed in panel A was interpreted as being the result of relative coordination to the environment and was thus excluded from these last analyses.
3 Figure 3 Results of spectral analysis for a period of activity expressed as power density observed per cycle length (in hours). As detailed in the Methods section, each minute of data was scored as 0 = sleep or 1 = wake and analyzed over 108 consecutive days. Prominent peaks were detected at 25.20, 24.04, and hours, in order of importance. Figure 4 The patient s pattern of light exposure from May to June 2001, as measured with a wrist-worn light sensor. (A) Proportion of wake periods spent in each of 4 intensity ranges. (B) Number of minutes within the wake period spent in bright light (> 1,000 lux). Means were calculated using 4-hour bins starting at the patient s reported time of awakening. (C) The patient s hourly mean levels of light exposure based on the time of awakening. To account for the variability in the patient s day length, the right axis shows the number of days included in each hourly mean. All error bars are ± SD. tribution (Figure 1B and 1C). Between 3:00 AM and 3:00 PM, the probability that the subject was asleep exceeded the median value for the likelihood of sleep throughout the day (Figure 1D). The distribution of sleep-wake cycle length was skewed and revealed the presence of a number of very short cycles, a predominance of near-24-hour cycles, and very long cycles (Figure 2A). The mean length (± SD) of all sleep-wake cycles was 23:27 ± 6:43 hours and not normally distributed. In order to restrict our analyses to a cycle of about a day, we reran descriptive statistics on the sleep-wake cycles falling inside the 95% confidence interval for mean cycle length. Approximately 12.5% of these remaining sleep-wake cycles showed a period of exactly 24 hours. This created a sharp peak of 24-hour sleep-wake cycles in the frequency distribution of duration of the sleepwake cycle (Figure 2A). We found that the majority of remaining cycles (87.5%) were normally distributed with a mean length (± SD) of 25:05 ± 2:23 hours and were composed of 33% sleep and 66% wake episodes (Figure 2B). The sleep-wake ratio on these rest-activity cycles was therefore comparable to that of healthy subjects. On average, main sleep episodes lasted (± SD) 8:21 ± 2:13 hours and main wake episodes lasted (± SD) 16:44 ± 2:26 hours. Results of the fast Fourier transform analysis of all sleep-wake cycles are represented in Figure 3, where periodogram values are plotted against the length of the cycle. The analysis revealed significant daily components with periods of 25.20, 24.04, and hours, in order of importance. ANOVA for repeated measures performed on hourly levels of light exposure relative to time from reported awakening revealed a significant variation in levels of illumination throughout the waking episode (F 21,504 = 4.61, P <.0001). Our analysis of this patient s pattern of light exposure revealed that the proportion of waking episodes spent in light within the < 1-lux, 1- to SLEEP, Vol. 27, No. 3,
4 100-lux, and > 1,000-lux ranges was within one SD of mean values reported for healthy subjects in the summer months (Figure 4A). 19 The proportion of her waking episodes spent in light of 100 to 1,000 lux was within 2 SDs of that reported for healthy populations at this latitude. 19 However, the patient consistently spent an average of less than 5 minutes per 4-hour bin in light of > 1,000 lux. This value was lower than that reported for healthy subjects during summer months and comparable to normative values reported for winter months (Figure 4B). 19 Highest mean light-intensity values were achieved early in her waking episodes (Figure 4C). DISCUSSION The analysis of our patient s sleep-wake pattern revealed the presence of longer than 24-hour cycles that document her tendency to free run and delay her sleep times by 1 to 2 hours each day. This finding is consistent with the recent report of free-running rhythms of urinary 6-sulphatoxy melatonin in this patient. 20 The occurrence of a 24-hour cycle length in 12.5 % of her sleep-wake cycles may correspond to a phenomenon known as relative coordination. 21 This observation suggests that the patient was transiently in and out of phase with environmental synchronizers too weak to fully entrain her to the 24-hour day. Indeed, our analyses revealed that the patient was minimally exposed to bright light (> 1,000 lux), suggesting that her exposure to the more powerful synchronizing effect of environmental outdoor light was limited (Figure 4B). In fact, her pattern of exposure to bright light more closely resembled that of healthy subjects studied during winter months. 19 Nevertheless, we cannot consider her an outlier based on her levels of light exposure, since it appears that she would fall within the 95% confidence interval for bright-light exposure in healthy subjects studied during summer months. Moreover, predominant exposure to light of indoor intensities should not preclude the capacity to maintain a 24-hour sleep-wake schedule. 22,23 It is proposed that relative coordination could account for the clustering of sleep onsets and offsets at specific times of day. The late timing of sleep periods clustered between approximately 4:00 AM and approximately 12:00 supports an association between DSPS and a hypernyctohemeral sleep-wake cycle. Prior to her accident, the patient kept late bedtimes (around 1:00-2:00 AM) but woke up at conventional hours. The diagnostic criteria for a DSPS could not be identified retrospectively. The presentation of DSPS following head injury has been previously reported in a number of cases Much like the patient described by Kagmar-Parsi et al, 16 our patient reported an improvement in her sleep quality when she delayed her bedtimes from one day to the next. The non 24-hour sleep-wake syndrome could thus be seen as a late complication of a delayed sleep tendency in which the patient deliberately decides to go to bed later to intensify sleepiness and increase the likelihood of falling asleep. 16 Indeed, the presentation of a non 24-hour sleep-wake syndrome has been reported in a case of DSPS following chronotherapy on a 27-hour day. 18 In rodents, a non 24-hour rest-activity cycle may arise as a physiologic aftereffect of lengthening the rest-activity cycle. 28 An alternative explanation for our observations could be that the patient had a hypernyctohemeral syndrome and attempted to entrain to a 24-hour day. However, during the period of ambulatory recordings, the patient was instructed to follow her natural sleep tendency. Thus, while we maintain that our patient presents elements of both DSPS and hypernyctohemeral syndromes, we cannot establish with certainty the order of presentation of these sleep-wake disorders. It is also important to consider the role of exposure to light and darkness in the etiology of the hypernyctohemeral syndrome. Indeed, McArthur and colleagues have previously reported the case of a 41-yearold sighted man with reduced sensitivity to light who presented a non 24-hour sleep-wake syndrome. 29 Similarly, the reduction of exposure to strong environmental synchronizers in our patient may contribute to the maintenance of her sleep-wake disorder. A recent laboratory investigation of the patient revealed that she initiated sleep on the falling limb of her endogenous circadian rhythm of plasma melatonin. 20 We previously reported that peak urinary 6-OHMS levels were usually observed at the end of her waking episodes at home. 20 By virtue of this phase alignment, light exposure would extend over the delay portion of her phase-response curve, which may reinforce her tendency to live on longer days despite the fact that the light to which she was exposed was of relatively low intensities. 30,31 Abnormal phase relationships between sleep-wake times and the circadian pacemaker have been reported in other cases of hypernyctohemeral syndrome 32,33 and DSPS. 34 The etiology of these phase relationships remains unclear but could involve a long circadian period or an abnormal circadian variation of sleep propensity. These speculations should be tested experimentally. Our continued investigation of this case may provide more clues as to the origin and nature of her sleep-wake disorder. At this time, we can identify no lesions that could account for either the posttraumatic sleep-wake disorder or the hypothesized reduced photic sensitivity. However, we cannot exclude the possibility of undetectable lesions that may underlie the observed behavior. 35,36 The possibility that the hypernyctohemeral syndrome could be a more severe form of DSPS has potential therapeutic applications. For instance, it may become necessary to adopt a compromise course of action in cases such as this one. Thus, an initial approach may be to reentrain the patient to a 24-hour sleep-wake cycle, where realignment of an apparently delayed bedtime to a more socially acceptable schedule may be achieved thereafter. 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