Adolescents with Sleep Disturbance: Causes and Diagnosis

Chapter 2
Adolescents with Sleep Disturbance:
Causes and Diagnosis
Akemi Tomoda and Mika Yamazaki
Child Development Research Center,
Graduate School of Medical Sciences,
University of Fukui


Sleep Disorders

Edited by Chris Idzikowski, ISBN 978-953-51-0293-9, 202 pages, Publisher: InTech, Chapters published March 14, 2012 under CC BY 3.0 license
DOI: 10.5772/1500
Edited Volume

Adolescents with Sleep Disturbance:
Causes and Diagnosis
1. Introduction
In our previous study, circadian rhythm sleep disorders have been reported in pediatric and
adolescent populations (Tomoda, Miike, Uezono, & Kawasaki, 1994). Pediatric practitioners
now commonly encounter sleep disturbance in previously healthy children and adolescents
(Boergers, Hart, Owens, Streisand, & Spirito, 2007; Giannotti, Cortesi, Sebastiani, & Ottaviano,
2002; Stein, Mendelsohn, Obermeyer, Amromin, & Benca, 2001). The characteristic clinical
features are well known, but the specific causes remain unknown. New types of circadian
rhythm sleep disorders, such as familial advanced sleep phase syndrome (ASPS) and delayed
sleep phase syndrome (DSPS), non-24-h sleep-wake syndrome (non-24), and morningnesseveningness
have been described during the last decade. Such disorders are probably caused
by various disturbances of circadian expression of the clock gene (Archer et al., 2003; Ebisawa
et al., 2001; Iwase et al., 2002; Pirovano et al., 2005; Takimoto et al., 2005; Toh et al., 2001;
Wijnen, Boothroyd, Young, & Claridge-Chang, 2002). Polymorphisms in clock genes are
known to induce circadian rhythm sleep disorders. For example, mutations in the period2
(Per2) gene (S662G) or casein kinase1 d (CK16) gene (T44A) cause familial ASPS; furthermore,
missense polymorphisms in the Per3 (V647G) and CK1e (S408N) genes increase or decrease
the risk of developing DSPS.
In our clinical practices, we recognized that the majority of our patients have a circadian
rhythm disorder even though they usually do not mention or recognize this problem at the
first interview. We hypothesized that there could be certain relationship between
biological rhythm disorders in these patients and their indefinite symptoms as well as
their sleep disturbances. This chapter introduces sleep patterns, circadian rhythms of core
body temperature (CBT), glucose metabolism, and human clock gene profile in children and
adolescents with sleep disturbance.
2. Methods
2.1 Protocol
This study included 22 unmedicated patients with sleep disturbances (Table 1). All patients
satisfied diagnostic criteria for circadian rhythm sleep disorders of the Diagnostic and
Statistical Manual of Mental Disorders, 4th Edition, Text Revision (DSM-IV-TR®). The
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diagnosis was made by three raters using the Structured Clinical Interview. The severity of
those symptoms was measured using self-reported ratings (performance status scores), as
described previously {Kuratsune, 2002 #890;Tomoda, 2007 #925}. Their performance status
scores on admission were higher than 5 (mean, 5.6; SD, 0.8).
For at least one month prior to the initial assessment, prophylactic drugs (e.g. tranquilizers)
were not given. Patients who had just recently started treatment with antidepressants or
hypotension drugs, or who were diagnosed as having neurological illness, migraine,
obstructive sleep apnea, below average intelligence, or serious psychopathology were
excluded from the study. Serious psychopathology was evaluated by referral to at least one
psychiatrist if the patient presented with some indicative symptoms. No patient had a
history of drug abuse. Table 1 presents physical characteristics of the present subjects. The
protocol was approved by the Committee of Life Ethics, Graduate School of Medicine,
Kumamoto University. All participants gave written informed consent.
p-value: significant difference in ANOVA.
Table 1. Circadian rhythm of core body temperature: Results of a cosinor analysis.
2.2 Recording of the sleep-wake rhythm
Each subject kept daily recordings (logs) of their time of sleeping and awaking for 4 or
longer weeks. These logs were used to analyze their sleep pattern during a 24-hour period.
According to the International Classification of Sleep Disorders (ICSD) revised by the
Association of Sleep Disorders Center in North America in 1990 (Diagnostic Classification
Committee, 1990), our patients were diagnosed as either delayed sleep phase syndrome
(DSPS), non-24-hour sleep-wake syndrome (non-24), irregular sleep, or long sleeper. DSPS is
characterized by difficulty in falling asleep at night and an inability to be easily aroused in
the morning, and this diagnosis corresponds to DSM-III-R: Sleep-Wake Schedule Disorder.
Non-24 presents sleep-wake cycles longer than 24 hours, and this corresponds also to DSMIII-
R: 307.45. Irregular sleep is characterized with no recognizable circadian patterns of sleep
onset or waking time, and this does not correspond a sleep disorder diagnosis in DSM-III-R.
Long sleeper have sleep times longer than 9 hours although they do not have any organic
abnormalities, and this correspond to DSM-III-R: 780.54.
Adolescents with Sleep Disturbance: Causes and Diagnosis
2.3 Circadian rhythm of core body temperature
Continuous monitoring of CBT for 3 days and at every one minute was carried out by using
a deep body temperature monitor (Terumo Corp., Tokyo, Japan).
Mean values of the 3 measurements at each time point during the 3 consecutive days were
used in the examination. A chronograph was used to determine the circadian rhythm, and
the single cosinor method, to analyze the CBT circadian variation for both groups (Halberg
et al. 1977). A cosine curve with a period of 24 hours was fitted to the data by using the least
squares method, and the following parameters were obtained: mesor (°C, rhythm-adjusted
average), amplitude (difference between the highest and lowest temperature), and
acrophase (time of the highest point in the rhythm defined by a fitted cosine curve). To
obtain data in normal age-matched persons, we recruited 9 healthy school children as
volunteers. They were 6 males and 3 females, aged 10-21 years (mean age, 17.3 years), and
who had no mental retardation, physical problems, or psychiatric psychopathology.
In statistical analysis, ANOVA was used, and when the p-value was less than 0.05, the group
difference was considered to be statistically significant.
2.4 Hormonal secretion profiles
Melatonin, cortisol, ß-endorphin and temperature circadian rhythms. 24-hour blood sampling was
performed through an indwelling catheter in a forearm vein at 4-hour intervals. Each blood
sample was immediately centrifuged at 4°C and stored at -80°C until melatonin, cortisol and
ß-endorphin were assayed by radioimmuno assay (RIA). The lower limit of melatonin
sensitivity was determined to be 3 pg/ml.
Comparative data concerning the timing of hormonal production were obtained for a group
of six normally-sighted healthy male volunteers aged 20-22 years (mean age, 20.6 years)
who had no mental retardation or serious psychopathology.
The recordings of the deep body temperature were carried out with a deep body
temperature monitor (Terumo Co., Tokyo, Japan) below Lanz’s point every 1 minute for
three consecutive days for the patient and the control group.
Both a chronograph and the single cosinor method were used to examine the rhythmicity
and to analyze the circadian variation.
A cosine curve with a period of 24 hours was fitted to the data using the least squares
method, and the following parameters were established; mesor (rhythm-adjusted mean),
amplitude (difference between mesor and nadir) and acrophase (lag of the crest time in the
best fitted cosine curve in relation to a given reference time). When the p-value was less than
0.05, the rhythm was considered to be statistically significant.
2.5 Evaluation of carbohydrate metabolism
A 3-h oral glucose tolerance test was performed the morning after a subject had fasted
overnight. After the fasting blood sample was drawn, a subject was given a solution
containing a predetermined amount of glucose based on body weight (1.75 g/kg to a
maximum of 75 g). After glucose ingestion, blood samples were drawn at 30, 60, 90, 120, 150,
and 180 min to measure blood glucose (BG) levels and immunoreactive insulin (IRI) response.
Serum BG level was determined using the glucose oxidase reaction method. Serum IRI
response was measured using radioimmunoassay (Eiken Chemical Co. Ltd., Tokyo, Japan).
The BG levels, IRI response, cumulative BG (sigma BG), cumulative IRI (sigma IRI),
insulin/glucose ratio (delta IRI/delta BG), and insulinogenic index (sigma IRI/sigma BG)
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were then compared to normal control data that had been reported previously for 8 subjects
aged 12–16 years without a personal or family history of diabetes mellitus or any factor
affecting glucose metabolism (Iwatani et al., 1997). The control subjects were within ±2.0 SD
of standard height, and within ±20% of ideal body weight. All indices were calculated using
the same methods as those reported previously (Iwatani et al., 1997).
2.6 Experimental procedure for human clock gene measurement
Subjects were exposed to natural and fluorescent lighting of the institution during the
awake period. Lights were turned off during the sleeping period. An indwelling catheter
was placed in the antecubital vein for a 24-h period. Blood samples were taken at 4-h
intervals beginning at 10:00 a.m. on the second day of hospitalization and continued until
6:00 a.m. of the following day. Samples were obtained under dim light (less than 30 Lux)
without waking the patients during the sleeping period. We previously reported that
subjects 12 years of age and older show similar metabolic characteristics to those of an adult
(Iwatani et al., 1997). Therefore, we recruited 10 men aged 20–41 years (mean age, 27.4 years;
SD, 6.1 years) as normal subjects from whom data were obtained (Reppert & Weaver, 2002;
Takimoto et al., 2005): none had below-average intelligence, physical problems, psychiatric
psychopathology, or irregular sleep or meal schedules.
Blood was collected in blood RNA kit tubes (PAXgene; Qiagen K.K., Tokyo, Japan). The tubes
were incubated at room temperature for 24 h; then the total ribonucleic acid (RNA) was
isolated according to the manufacturer’s instructions. For quality assessment of total RNA
during protocol development, deoxyribonucleic acid (DNA) digestion of the samples was
performed with the RNase-Free DNase Set (Qiagen K.K.). Synthesis of complementary DNA
was conducted (ReverTra Ace--®; Toyobo Co. Ltd., Osaka, Japan) for use with the reversetranscription
polymerase chain reaction (RT-PCR) kit. Quantitative real-time RT-PCR
(TaqMan®) was performed using a sequence detection system (ABI PRISM® 7900; Applied
Biosystems, Foster City, CA) to determine the expression levels of hPer1, hPer2, hPer3, hBmal1,
hClock, and housekeeping gene h-actin expression relative to h-actin, with the standard
protocol described by the manufacturer. Relative expression of the clock gene was determined
as the ratio of expression of the clock gene to that of the -actin gene for each sample. Values
were normalized so that the peak value equaled 100%. The TaqMan® h-actin control reagents
and primer sets, Assays-on-DemandTM Gene Expression Product for hPer1, hPer2, hPer3,
hBmal1, and hClock were purchased from Applied Biosystems for the following: hPer1,
Hs00242988_m1; hPer2, Hs00256144_m1; hPer3, Hs00213466_m1; hBmal1, Hs00154147_m1;
hClock, Hs00231857_m1. In addition, hPer2 was selected as the daily expression of the clock
gene for determination of the circadian profile (Takimoto et al., 2005).
3. Results
3.1 Sleep-awake rhythm disturbance
Based on the self-recorded sleep-wake logs, all patients were diagnosed as having one of the
4 sleep disturbances, i.e., DSPS, non-24, irregular, and long sleeper. Among patients in these
4 disease categories, there were no significant differences in the duration of sleep
disturbance, ages when the symptom first started, and their current age.
More than 80% of our patients with sleep disorders showed a tendency of a day/night
reversal life style, especially in the period right after termination of school social life. An
overnight EEG study revealed a decrease in deep NREM sleep and delayed latency of the
Adolescents with Sleep Disturbance: Causes and Diagnosis
REM sleep phase (unpublished data). Most of them need about 10 hours sleep to keep
awake for the rest of the daytime. These data suggest a deteriorated quality of night sleep.
Even though sleep disorders are considered to begin in childhood and adolescents, there
have been no in depth reports on this problem.
3.2 Abnormal core body temperature rhythm
It has been known that the sleep-awake circadian rhythm and other circadian rhythms such
as the CBT and hormonal secretion rhythms are closely related to each other. With this
background we examined the circadian CBT rhythm in our cases using a special instrument
for CBT measurement. The CBT rhythm has been considered to well-match the brain
temperature rhythm, according to a basic study. The 41 subjects studied (24 males and 17
females), aged between 10 to 19 years (mean: 15.2 years), were referred to our clinic. To
obtain data for normal age-matched controls, we recruited healthy school children as
volunteers. The comprised 6 males and 3 females, aged 10-21 years (mean: 17.3 years) for
CBT controls. The results are summarized in Table 1. In those patients, the mesor of the
circadian CBT rhythm was significantly higher than that in the normal controls. In
particular, it is noteworthy that the mean CBT at nighttime was obviously higher in the
patients than in normal controls. In those patients, the nadir was also significantly higher
than in the normal subjects. The nadir recorded on appearance was significantly delayed in
the patients compared to in the normal subjects.
In those patients, the amplitude of circadian CBT rhythm was significantly lower (0.85 ±
0.36°C) than the normal subjects (1.51 ± 0.37°C) (P <0.005). Acrophase in the control subjects
was recorded on 17.44 ± 1.34 PM, whereas it was advanced in 6 patients to 15.10 ± 1.02 PM
(P <0.005), and delayed in 16 patients to 20.02 ± 1.18 PM (P <0.005). Advance or delay was
determined in comparison to the time defined in the control subjects. In our subjects, there
were no rhythmical changes in their CBT.
3.3 Disturbed hormonal secretion profiles
We have studied the hormonal circadian secretion rhythm, such as for melatonin, cortisol
and -endorphin. Each of them showed abnormal behavior, that is, a delayed peak secretion
time and a decrease in the secreted amount. As to cortisol secretion in the patients, the area
under the curve (AUC) was significantly smaller than in normal controls. In addition, the
cortisol peak secretion time was significantly delayed.
These data suggested that circadian rhythms are deranged in our patients, and clearly
explain that the starting time of daily life is seriously delayed, because of delayed
preparation for mental and physical activity supporting daily life. We would like to
emphasize the reason why those patients showed a bad condition in the morning and a
relatively good condition in the afternoon. The decreased total level of hormonal secretion
may be the main cause of the inactivity, dullness and stagnant condition.
3.4 Disturbed carbohydrate metabolism
Glucose tolerance was significantly lower in the patients than in normal controls: the mean
sigma blood glucose level was significantly higher (P < 0.05) and the insulinogenic index
was significantly lower (P < 0.05) in the patient group than in controls (Miike, Tomoda,
Jhodoi, Iwatani, & Mabe, 2004).
The mean blood glucose (BG) level was not significantly higher in the patient group than in
the controls at any time interval following oral glucose ingestion, except at 30 and 120 min
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(both P < 0.05) (Tomoda, Kawatani, Joudoi, Hamada, & Miike, 2009). The mean plasma insulin
concentration in the patient group was not significantly different from the controls at any time
interval following oral glucose ingestion, except at 120 and 150 min (P <0.001 and P <0.05,
respectively). However, individual patient insulin levels varied widely compared with the
corresponding BG levels. The insulin level did not correlate with the BG level in some patients.
The mean sigma BG level in the patient group was significantly higher than that of controls
(910.3 ± 189.9 vs. 865.1 ± 60.5 mg/dl, P = 0.027). However, the mean sigma IRI was not
significantly different (patients vs. controls = 431.6 ± 194.8 vs. 892.8 ± 440.5 μU/ml, P = 0.103).
The insulin/glucose ratio, the initial insulin response 30 min after glucose ingestion, was not
significantly different (patients vs. controls = 0.95 ± 0.63 vs. 2.43 ± 1.03, P = 0.315). However, a
significant difference was found in the insulinogenic index (patients vs. controls = 0.48 ± 0.20
vs. 1.04 ± 0.50, P = 0.044). The results are summarized in Table 2.
3.5 Abnormal mammalian circadian clock
18 of 22 unmedicated patients were examined. The mRNA level of hPer2 was significantly
higher at 6:00 in the control subjects. In contrast, the mRNA level of hPer2 was higher at 6:00
in only 3 patients, at 2:00 in 3, at 10:00 in 4, at 14:00 in 3, and at 18:00 in 5. The timing of the
hPer2 peak expression level was significantly later in the patients than in the control subjects
(P < 0.05, Mann–Whitney’s U-test). The most phase-advanced cases (cases 1, 2, 11) showed
the hPer2 peak at 2:00, although the most phase-delayed cases (cases 9, 10, 15–17) showed
the hPer2 peak at 18:00.
There were no significant differences in expression levels of hPer1, hPer3, hBmal1, hClock.
4. Discussion
Deranged circadian rhythms have been well recognized in jet lag. In this condition, one may
have symptoms, and i.e. dysfunction of the autonomic nervous system, sleep awake rhythm,
mental and physical activity. We presume that those patients with sleep disturbance
suffered from an atypical but continuous jet lag condition in their daily life.
The international classification of sleep disorders (ICSD) was revised as a new sleep
disorder nosology by the Association of Sleep Disorders Center in North America in 1990.
Circadian rhythm sleep disorders, such as the delayed sleep phase syndrome (DSPS) and
the non-24-hour sleep-wake syndrome, have been described as new types of sleep-wake
disorders in the last decade. In this study, we presented children or adolescents who were
evaluated as not having physical abnormalities, psychiatric disorders, or specific social
problems, but they were suspected to have sleep disturbance because of their daily life
pattern. They were healthy in terms of physical and psychiatric examinations, but unable to
attend school because their overall conditions did not allow. Those patients who satisfied
our inclusion criteria to this study accounted for 40% of the total school refusal cases whom
we examined in a 2-year period. This portion is quite large, and indicates the difficulty to
prescribe appropriate therapy for these patients.
In our study, all 22 patients were diagnosed as having sleep-wake rhythm disturbance
based on their sleep log evaluation and CBT monitoring. Their body temperature rhythm
was disturbed in the manner typically shown in adult sleep disorder patients. Among our 6
school refusal patients diagnosed as having non-24, 3 did not show clear rhythm of CBT.
Because non-24 is considered most difficult to treat among the 4 categories of sleep disorder,
this therapeutic difficulty could be attributable to the severely disturbed CBT rhythm.
Adolescents with Sleep Disturbance: Causes and Diagnosis
Table 2. Type of sleep disturbance, and times of hPer2 peak, cortisol peak, and lowest core
body temperature (CBT) over 24 h, and results of component analysis of the cardiographic
R–R interval and glucose tolerance test of each patient(Tomoda et al., 2009).
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The 2 biological rhythms (sleep and CBT) are sometimes desynchronized with each other,
e.g., when the person was completely isolated from time cues. Once the desynchronization
occurred, psychosomatic symptoms, such as headache, gastrointestinal discomfort, or
general fatigue. These symptoms could make the affected person unable to perform
ordinary daily activities.
Furthermore, our findings obtained in this study suggest that physiological homeostasis
might be seriously impaired by sleep deprivation and emotional distress, as reflected clearly
by depressive symptoms in these patients. Easy fatigability and disturbed learning and
memorization are among the primary characteristics of sleep disturbance and chronic
fatigue in adolescents (Miike et al., 2004). Fatigue and gastrointestinal discomfort were quite
severe in our patients. Another feature of this illness is the individuality of symptom
patterns and the unpredictability of symptom severity.
It is particularly interesting that diurnal hypersecretion of glucocorticoids and altered
regulation of the hypothalamo–pituitary–adrenocortical axis are known in patients with
poorly controlled or uncontrolled diabetes (Archer et al., 2003; Chiodini et al., 2006; Roy,
Roy, & Brown, 1998). We found no cortisol hypersecretion in the present patients,
suggesting the absence of diabetic status. However, those patients with sleep disturbance
had glucoregulatory dysfunction. Results of a previous study show that emotionally
stressful events result in hyperglycemia in diabetic patients (Lustman, Carney, & Amado,
1981). On the other hand, sleep deficit has a harmful impact on carbohydrate metabolism
and endocrine function, even in healthy subjects (Spiegel, Leproult, & Van Cauter, 1999).
Abnormalities of the biological stress response (hypothalamic–pituitary–adrenal axis and
autonomic nervous system) were also identified in a previous animal study, the results of
which suggested that cortisol can act directly on the central nervous system (Sandoval, Ping,
Neill, Morrey, & Davis, 2003). Multiple factors including autonomic nervous system
dysfunction, derangement of neuropeptides in the hypothalamus, and hormonal imbalance
might also affect the glucoregulatory metabolism.
The biological clock (circadian clock) in human beings is formed and regulated through
interrelationships of various clock genes such as Per1, Per2, Per3, Bmal1, Clock, Cry1, Cry2,
Bmal, Rev-ervA, CK1 d/e, and glycogen synthase kinase 3-b (GSK3ß) (Ebisawa et al., 2001;
Gietzen & Virshup, 1999; Jones et al., 1999; Takano et al., 2004; Toh et al., 2001; Vanselow et
al., 2006). Currently, the markers of circadian rhythms are considered to be the profiles of
plasma melatonin, cortisol, and core body temperature (Tomoda, Miike, Yonamine, Adachi,
& Shiraishi, 1997). However, even if these markers show normal rhythmic patterns, certain
patients suffer from circadian rhythm sleep disorders and indeterminate symptoms,
suggesting that these markers may not be reliable for the diagnosis of circadian rhythm
sleep disorders.
Presumably, autonomic and metabolic dysfunction causing sleep disturbance may be
related to the hPer2 phase shift because of chronobiological abnormality. Results of a
previous study indicate that such disturbances might be related closely to the
desynchronization of biorhythms, particularly the circadian rhythm of body temperature
and the sleep–wake rhythm (Tomoda, Jhodoi, & Miike, 2001; Tomoda et al., 2000). Previous
and present results suggest that sleep deprivation may originate from a dysfunctional
network of brain areas related to the circadian rhythm and peripheral nervous system
involved in the autonomic nervous system including cardiac function and gastrointestinal
digestion. However, dysregulation of the circadian rhythm is neither the only nor the
Adolescents with Sleep Disturbance: Causes and Diagnosis
dominant factor in the pathogenesis of such conditions. Immunological, autonomic, and
neuroendocrine abnormalities might be mutually dependent and reinforcing factors. More
studies must be done to elucidate this mechanism and to reveal the relation between clock
gene expression in the suprachiasmatic nucleus and the peripheral blood cells. Furthermore,
additional study of a larger series of cases will elucidate the usefulness of this technique.
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temperature rhythm and sleep disturbance in school refusal children and
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Edited by Dr. Chris Idzikowski
ISBN 978-953-51-0293-9
Hard cover, 190 pages
Publisher InTech
Published online 14, March, 2012
Published in print edition March, 2012
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