Abnormalities in sleep patterns in individuals at risk for psychosis and bipolar disorder

SCHRES-06511; No of Pages 6 Schizophrenia Research xxx (2015) xxx–xxx

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Abnormalities in sleep patterns in individuals at risk for psychosis and bipolar disorder Marcio A. Zanini a,b,c, Juliana Castro c, Graccielle R. Cunha a,b, Elson Asevedo a,b, Pedro M. Pan a,b, Lia Bittencourt c, Fernando Morgadinho Coelho c, Sergio Tufik c, Ary Gadelha a,b, Rodrigo A. Bressan a,b, Elisa Brietzke a,b,⁎ a b c

Program for Recognition and Intervention in Individuals in At-Risk Mental States (PRISMA), Department of Psychiatry, Universidade Federal de São Paulo, São Paulo, Brazil Interdisciplinary Laboratory of Clinical Neuroscience (LINC), Universidade Federal de São Paulo, São Paulo, Brazil Sleep Institute, Department of Psychobiology, Universidade Federal de São Paulo, São Paulo, Brazil

a r t i c l e

i n f o

Article history: Received 1 July 2015 Received in revised form 12 August 2015 Accepted 17 August 2015 Available online xxxx Keywords: Sleep Polysomnography Psychosis Schizophrenia Bipolar disorder Early stages Prodromal At-risk mental states

a b s t r a c t Aim: To compare patterns of sleep and the presence of sleep disturbances in individuals in at-risk mental states (ARMS) for psychosis and bipolar disorder (BD) with a healthy control (HC) group. Methods: This was a comparative study involving 20 individuals in ARMS for psychosis or BD, according to the Comprehensive Assessment of At-Risk Mental States, and 20 age- and sex-matched healthy controls. Quality of sleep in the previous month was assessed using the Pittsburgh Sleep Quality Index, diurnal somnolence was evaluated using The Epworth Sleepiness Scale, and chronotype was determined using the Questionnaire of Morningness/Eveningness (QME). All of the participants underwent polysomnography (PSG) during the entire night for two consecutive nights. The first night aimed to adapt the subject to the environment, and only the data from the second night were used for the analysis. Results: Compared with the HC group, individuals in the ARMS group reported significantly worse sleep quality, as measured by the Pittsburgh Sleep Quality Index. Both groups had scores consistent with daytime sleepiness on the Epworth Sleepiness Scale, and there were no differences with regard to chronotype between the groups, with a predominance of the indifferent type in both groups. In the PSG assessment, we observed increased Sleep Latency (SL) and increased Rapid Eye Movement Sleep Onset Latency (REMOL) in the ARMS group, compared to the HC group. Conclusion: The results of this study indicated that sleep abnormalities could be found early in the course of mental diseases, even in at-risk stages, and support the further investigation of their predictive value in the transition to psychosis and BD. © 2015 Elsevier B.V. All rights reserved.

1. Introduction Schizophrenia and bipolar disorder (BD) are potentially severe psychiatric disorders that affect, together, approximately 3% of the population over a lifetime (Kessler et al., 1994). Despite advances in psychopharmacology, available treatments are limited in reducing BDand schizophrenia-associated morbidity and mortality (Brietzke et al., 2011; Yung et al., 1998). As a result, one of the most promising research lines in this field is the study of individuals who are most likely to develop severe mental disorders, focusing on prevention (Modinos et al., 2014). Findings from several research lines have converged on an understanding that although they are distinct diseases, schizophrenia and BD have in common many pathophysiological processes such as the following: genetic susceptibility conferred by polymorphisms in the genes ⁎ Corresponding author at: Rua Pedro de Toledo, 669-3rd Floor, Vila Clementino, São Paulo, SP. Brazil. E-mail address: [email protected] (E. Brietzke).

DISC1, Dysbidin, NRG1 and DAO-A (Ivleva et al., 2008); affected cognitive domains, (Murray et al., 2004); structural neuroimaging changes (McDonald et al., 2004); decreases in neurotrophins, particularly in Brain-Derived Neurotrophic Factor (BDNF) (Balu and Coyle, 2011; Cunha et al., 2006) and inflammatory mediators such as cytokines (Smesny et al., 2010). The existence of a prodromal phase, a period during which symptoms are present with milder severity, with a shorter duration or lower frequency, preceding the onset of psychosis and BD has attracted increasing interest in the scientific community (Correll et al., 2014; Fusar-Poli et al., 2014; Noto et al., 2013). Some groups have developed criteria for identifying individuals with at-risk mental states (ARMS) for psychotic disorders (Amminger et al., 2006; Yung et al., 2004) and for BD (Bechdolf et al., 2010), using a combination of cognitive, behavioral, and emotional changes, in addition to non-specific genetic risk and functional decline. Prospective follow-up studies, using participants at ultra-high risk for psychosis, have shown that between 20 and 40% of the subjects developed psychotic episodes after 1 to 2 years of follow-up (Amminger et al., 2006; Yung et al., 2003).

http://dx.doi.org/10.1016/j.schres.2015.08.023 0920-9964/© 2015 Elsevier B.V. All rights reserved.

Please cite this article as: Zanini, M.A., et al., Abnormalities in sleep patterns in individuals at risk for psychosis and bipolar disorder, Schizophr. Res. (2015), http://dx.doi.org/10.1016/j.schres.2015.08.023

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M.A. Zanini et al. / Schizophrenia Research xxx (2015) xxx–xxx

Complaints about changes in sleep patterns are common in patients with schizophrenia and BD, and these changes tend to intensify with the proximity of an episode of acute exacerbation of both diseases (Bechdolf et al., 2010; Yung et al., 2003). The circadian system modulates mood, and changes in this system, including sleep deprivation as a result of travel or overwork, have negative effects on mood, causing irritability and emotional lability (Murray et al., 2002). The relationship between sleep disturbances and mood swings is a two-way street because high levels of agitation affect the quality of sleep and can lead to a vicious cycle between sleep disturbance and emotional dysregulation (Murray et al., 2009; Thayer, 1987). Sleep loss not only increases the negative emotional response but also decreases the response to positive events (Boivin et al., 1997). Sleep is an adaptive function of humans, during which the restoration of brain processes, including strengthening of the immune system, growth, major metabolic processes, memory consolidation and brain plasticity, occurs (Durmer and Dinges, 2005; Maquet, 1995; Stickgold et al., 2001). REM (rapid eye movements) sleep might be particularly important in processing and emotional modulation (Cartwright et al., 2006; Walker, 2009). Psychosis in schizophrenia is associated with an abnormal pattern of brain self-activation in waking, and it is hypothesized that selforganized dynamics of neuronal activity in sleep should likewise be affected (Vukadinovic, 2011). Studies using high-density EEG have shown a decrease in sleep spindles in adult patients with schizophrenia compared to non-psychotic patients receiving neuroleptics and healthy controls (Ferrarelli et al., 2007; Wamsley et al., 2012). Tesler et al. (2015) found a reduced sleep spindle density in research with nine adolescents meeting the criteria for an early onset schizophrenia spectrum disorder and summarized that sleep spindles are thought to be a reliable electrophysiological marker reflecting deficits in the integrity of the thalamocortical system in schizophrenia. Sleep alterations directly affect quality of life and interfere with emotional regulation in BD (Giglio et al., 2009; Michalak et al., 2007). Evidence exists for a relationship between the state of mood prior to sleep and EEG parameters during REM sleep, which seems to play an important role in emotional processing (Nishida et al., 2009). In a systematic review that investigated symptoms prior to outbreaks of manic or depressive episodes in bipolar patients, Jackson and colleagues concluded that changes in sleep patterns were the most common symptom predictor for mania (Jackson et al., 2003). A longitudinal study developed by Perlman et al. (2006) with 52 patients diagnosed with BD I, aged 18 to 75, reported that shorter sleep latencies were predictive of depressive episodes over 6 months of follow-up. Hirschfeld et al. (2003) investigated, through self-reported questionnaires, 600 patients with BD to determine the experiences of those with the disease; 78% reported some sleep disturbance as a common symptom when on the verge of a mood episode. Correll et al. (2007) conducted a retrospective study with 52 euthymic bipolar patients, age 7 to 21, and reported reduced need for sleep as one of the symptoms prior to the development of a manic episode in 39% of patients. In a retrospective investigation of prodromal signs of the first psychotic episode, Yung and McGorry (1996) described changes in sleep as the most common finding in 70–100% of patients. In one study involving 59 euthymic bipolar outpatients, Bauer et al. (2006) found an increase in sleep latency to be the most common predictor of the recurrence of a mood episode. Studies investigating sleep using PSG in individuals with schizophrenia have documented difficulties in initiating and maintaining sleep, increased total sleep time, little restful sleep, increased latency and reduced total REM sleep time, as well as a decrease in slow wave sleep (stage N3) (Keshavan et al., 1990; Poulin et al., 2003; Tandon et al., 1992). Keshavan et al. (2004) evaluated PSG findings from 81 firstdegree relatives of schizophrenic patients, aged 6 to 25, and noted alterations such as disrupted sleep and reductions in Slow Wave Sleep (SWS). In a previous study, Keshavan and Tandon (1993), suggested

that SWS reductions can be associated with negative symptoms, brain structural alterations, reduced prefrontal metabolism and cognitive impairment. In a study that compared 33 adolescents at ultra-high risk (UHR) for psychosis with 33 healthy controls, Lunsford-Avery et al. (2013) found increased latency to sleep onset and greater sleep disturbances in the UHR group. Behavioral techniques such as sleep deprivation, light exposure, sound stimuli, and adjustments in feeding, working and social times are known to be effective ways to restore the sleep–wake cycle (Mistlberger et al., 2000). The effectiveness of such techniques is demonstrated clinically by phototherapy as a treatment for seasonal affective disorders and stabilization of biological rhythms to control TB relapses (Frank et al., 2007; Murray et al., 2006). The detection of changes in sleep or sleep–wake cycles in vulnerable individuals might provide a valuable indicator of neurobiological developmental deviations and data about the pathophysiology of at-risk states, supporting the study of changes in sleep patterns as predictors of transitions to major psychiatric disorders (Zanini et al., 2013). Nevertheless, sleep has received little attention in the study of ARMS, and these individuals have never been assessed using robust standardized methods. In this study, we explored changes in sleep in individuals with ARMS, aiming to understand the clinical presentation and neurobiology of putatively prodromal stages of psychotic and severe mood disorders. The objective of this study was to investigate sleep complaints using structured questionnaires and PSG findings in ARMS patients compared with healthy controls. 2. Methods 2.1. Subjects Twenty individuals in ARMS and 20 age- and sex-matched HC between the ages of 13 and 27 participated in the study. The subjects included in the ARMS group were selected from individuals seeking help from the Program for Recognition and Intervention in Individuals in At-Risk Risk Mental States (PRISMA), Federal University of São Paulo (UNIFESP). The HC group was recruited using posters calling for healthy volunteers for research and advertisements on Web sites. The inclusion criteria for the individuals in the ARMS group were as follows: having never presented with any psychiatric illness, according to the Structured Clinical Interview for DSM-IV Axis I Disorders, Clinician Version — SCID-CV (First et al., 1996) and Schedule for Affective Disorders and Schizophrenia for School-Age Children-Present and Lifetime Version — K-SADS-PL (Kaufman et al., 1997); having sought at least one health service for distress or functional impairment in the past year; and meeting the criteria for ultra-high risk for psychosis or high risk for BD. The criteria for ultra-high risk for psychosis were determined in accordance with those proposed by Yung et al. (2005), according to the classification of the Comprehensive Assessment of At-Risk Mental State (CAARMS) scale, translated and adapted to the Brazilian linguistic and cultural context. The criteria for high risk for BD followed those proposed by Bechdolf et al. (2010), measured by the CAARMS and clinical evaluation. Although the criteria to identify risk for BD remain under discussion, criteria developed by Bechdolf et al. (2010) were also adopted because they are similar to CAARMS and were prospectively validated. These criteria are summarized in Table 1. The inclusion criteria for the healthy controls were having never presented any psychiatric illness, according to the SCID-CV (First et al., 1996) and Schedule for Affective Disorders and Schizophrenia for K-SADS-PL (Kaufman et al., 1997), and no history of psychotic disorders or mood disorders in firstdegree relatives. Exclusion criteria for cases were as follows: diagnosis of BD type I or type II or a psychotic disorder, currently or during the lifetime, according to the SCID-CV (First et al., 1996), for individuals aged 16 years old or older or the K-SADS (Kaufman et al., 1997) for individuals younger than 16 years old; a current substance use disorder; risk of suicide or

Please cite this article as: Zanini, M.A., et al., Abnormalities in sleep patterns in individuals at risk for psychosis and bipolar disorder, Schizophr. Res. (2015), http://dx.doi.org/10.1016/j.schres.2015.08.023

M.A. Zanini et al. / Schizophrenia Research xxx (2015) xxx–xxx Table 1 Criteria for ARMS. Ultra-high risk for psychosis Attenuated positive symptoms Presence of positive symptoms in moderate severity but not reaching clearly the psychotic band; present more than one time per month for more than 1 h per week, in the past year, associated with a reduction in social and occupational functioning Brief intermittent psychotic symptoms Presence of brief episodes of a full psychotic illness, which might involve all of the symptoms of a psychosis (particularly delusions and hallucinations) Trait and state risk factors Vulnerable family history of psychosis in a 1st-degree relative or a diagnosis of schizotypal personality disorder, associated with a decline in social and occupational functioning Bipolar at-risk Subthreshold mania At least two consecutive days, not to exceed four days: humor abnormally elevated, expansive or irritable mood accompanied by at least two of the following criteria: (1) inflated self-esteem or grandiosity; (2) decreased need for sleep; (3) more talkativeness than usual or pressure of speech; (4) flight of ideas or subjective experience of quick thinking; (5) distractibility; (6) increase in goal-directed activities or psychomotor agitation. Depression ± cyclothymic features For at least one week: depressed mood or loss of interest or pleasure, accompanied by at least two of the following criteria: (1) significant weight loss; (2) insomnia or hypersomnia nearly every day; (3) psychomotor retardation or agitation; (4) fatigue or loss of energy; (5) feelings of worthlessness or excessive or inappropriate guilt; (6) diminished ability to think or concentrate; (7) recurrent thoughts of death or suicide; cyclothymic characteristics Depression ± genetic risk For at least one week: depressed mood or loss of interest or pleasure accompanied by at least two of the following criteria: (1) significant weight loss; (2) insomnia or hypersomnia nearly every day; (3) psychomotor retardation or agitation; (4) fatigue or loss of energy; (5) feelings of worthlessness or excessive or inappropriate guilt; (6) diminished ability to think or concentrate; (7) recurrent thoughts of death or suicide First-degree relative with bipolar disorder.

suicidal behavior; the presence of acute or unstable general medical comorbidities; pregnancy; postpartum status and current breastfeeding; organic brain disease; or the inability to understand and provide informed consent.

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to 21. The higher the score is, the worse the quality of sleep. A global score N 5 indicates that the individual is experiencing great difficulty in at least two components or moderate difficulties in more than three components. 2.2.1.2. Epworth Sleepiness Scale. The Epworth Sleepiness Scale is a selfreport questionnaire that assesses subjective daytime sleepiness, based on the possibility of dozing in eight everyday situations. To assess the likelihood of dozing, an individual uses a scale of 0–3, where 0 corresponds to no chance of dozing, and 3 represents a high probability. The scores range from 0 to 24, with 0 to 6 = normal; 7–9 = borderline; 10–14 = mild daytime sleepiness; 15–20 = moderate daytime sleepiness; and N 20 = severe daytime sleepiness. The scale was developed by Johns (1991) and was translated and adapted for use in Brazil by Bertolazi et al. (2011). 2.2.1.3. Questionnaire of Morningness/Eveningness (QME). Developed by Horne and Ostberg (1976), the QME identifies the chronotypes of individuals as morning or evening. The total score ranges from 16 to 86 points and is the sum of the individual scores of 19 items. The cutoff points suggested by the authors, which define the individual's chronotype, are 16–30, evening; 31–41, moderately evening; 42–58, indifferent; 59–69, moderately morning; and 77–86, morning. The Brazilian Portuguese version was translated and validated by BeneditoSilva et al. (1990). 2.2.2. Polysomnography (PSG) All of the participants underwent two PSG exams over the entire night for two consecutive nights, using the EMBLA S700080 digital system. The first night aimed to adapt the subject to the environment, and only the data from the second night were used for the analysis. The following physiological variables were monitored continuously and simultaneously: electroencephalography (C3-A2, C4-A1, F4-M1, M2-F3, O1A2, O2-A1); electrooculography (EOG) (EOG-Left-A2, A1-Right EOG); surface electromyography (submental region of the muscle, the tibial anterior muscle, masseter and seventh intercostal space); electrocardiography (modified V1 lead); airflow (thermocouple and pressure transducer); respiratory effort (chest and abdomen), recorded by inductance plethysmography; snoring; body position; and oxyhemoglobin saturation. All of the PSG recordings were performed and staged according to the standard criteria established by the Standard Handbook of the American Academy of Sleep Medicine 2007 (Iber et al., 2007). 2.3. Statistical analysis

The research consisted of a comparative, case-control study and was approved by the UNIFESP Ethics Committee. All of the individuals or their parents provided written informed consent prior to enrollment. The research protocol included the following assessments:

Statistical analyses were performed by SPSS version 17. Chi-squared tests were performed on categorical demographic and clinical variables, with the continuity correction of Yates. To assess whether the means of the variables were the same or different, the Shapiro–Wilk test was used. The Mann–Whitney parametric test was used to evaluate variables in violation of normality, and t-tests were used to assess variables that followed a normal distribution. The statistical significance level was P b 0.05.

2.2.1. Questionnaires for sleep evaluation

3. Results

2.2.1.1. The Pittsburgh Sleep Quality Index. This instrument, developed by Buysse et al. (1989) at the University of Pittsburgh, was translated, adapted and validated for use in Brazil by Bertolazi et al. (2011). This index evaluates the quality of sleep in the past month to classify patients as “good sleepers” or “bad sleepers”. The questionnaire consists of 19 (nineteen) self-rated questions, grouped into seven components, with weights distributed on a scale of 0–3, which consider subjective perceptions of sleep quality, the time required to fall asleep, the duration of sleep, sleep efficiency and daytime dysfunction. The scores are totaled, and these components produce an overall score, which ranges from 0

The sample consisted of 20 healthy controls (HC) and 20 individuals in ARMS, of whom 13 (65%) met the criteria of at-risk for BD and 7 (35%) for psychosis. There were no patients fulfilling criteria for both ARMS subgroups simultaneously. Sixty-five percent of the participants were male in both groups, and the groups were also homogeneous with regard to age (18.7; ± 3.94 years), years of education (11.25; ± 2.70 years) and body mass index (22.27; ± 4.02 kg/m 2). Eight (40%) participants in the ARMS group were taking psychotropic medication. The demographic and clinical characteristics of the sample are described in Table 2.

2.2. Procedures

Please cite this article as: Zanini, M.A., et al., Abnormalities in sleep patterns in individuals at risk for psychosis and bipolar disorder, Schizophr. Res. (2015), http://dx.doi.org/10.1016/j.schres.2015.08.023

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M.A. Zanini et al. / Schizophrenia Research xxx (2015) xxx–xxx

Table 2 Clinical and demographic characteristics of the sample.

Age in years; mean (SD) Sex; male (%)/female (%) BMI in kg/m2; mean (SD) Years of education; mean (SD) ARMS psychosis; n (%) ARMS BD; n (%) Currently taking psychiatric medication (%) SSRI Second-generation antipsychotic Benzodiazepine The Pittsburgh Sleep Quality Index score; mean (SD) Epworth Sleepiness Scale; mean (SD) QME; mean (SD) Chronotype Evening Moderately evening Indifferent Moderately morning Morning

ARMS (n = 20)

HC (n = 20)

T-value

P-value

18.3 (±3.91) 13 (65)/7 (35) 21.09 (±3.64) 10.65 (±2.68) 7 (35%) 13 (65%) 8 (40%) 3 3 2 7.70 (±3.68) 8.20 (±4.29) 44.50 (±10.04)

19.1 (±4.02) 13 (65)/7 (35) 23.45 (±4.12) 11.85 (±2.66) – – 0

−0.638 −1.921 −1.422 – –

0.527 0.263 0.062 0.163 – –

2.877 −0.809 −1.385

0.007 0.424 0.174

1 (5%) 7 (35%) 10 (50%) 2 (10%) 0

0 4 (20%) 14 (70%) 2 (10%) 0

4.95 (±2.16) 9.35 (±4.69) 48.45 (±7.86)

ARMS: at-risk mental state; HD: healthy controls; SD: standard deviation; BMI: body mass index; SSRI: selective serotonin reuptake inhibitor; QME: Questionnaire of Morningness/ Eveningness. Bold represents statistical significant associations.

In the subjective assessment of sleep patterns, using standardized scales, 15 (75%) subjects in the ARMS group and 6 (30%) in the HC group had scores N 5 on the Pittsburgh Sleep Quality Index, indicating a significantly higher frequency of low-quality sleep in the ARMS group compared to the HC (P = 0.007). Both the ARMS and HC groups showed a high frequency (70%) of scores on the Epworth Sleepiness Scale, consistent with mild daytime sleepiness, with no significant differences between them (P = 0.42). Both groups were predominantly composed of the indifferent chronotype (10 [50%] subjects in the ARMS group and 14 [70%] in the HC group). Moderate evening type was present in 7 individuals (35%) in the ARMS group and 4 (20%) in the HC; 2 (10%) subjects in each group were of the moderate morning type, and only 1 (5%) in the ARMS group was the evening type. Comparing the polysomnographic parameters between groups, there were statistically significant differences in the variables Sleep Latency (SL) and Rapid Eye Movement Sleep Onset Latency (REMOL). Individuals in the HC group required an average of 12.91 min (± 15.65) to fall asleep, while the ARMS group required 25.98 min (± 20.31) (P = 0.023). The first REMOL was 89.76 min (± 37.8) for the HC group and 121.99 min (±52.29) (P = 0.032) for individuals in

HC (n = 20)

TST (min); mean (SD) 372.69 (±82.71) 379.34 (±42.65) SE (%); mean (SD) 85.15 (±14.51) 90.51 (±8.26) SL (min); mean (SD) 25.98 (±20.31) 12.91 (±15.65) REMOL (min); mean (SD) 121.99 (±52.29) 89.76 (±37.82) WASO (min); mean (SD) 41.72 (±53.86) 28.11 (±36.55) N1 (min); mean (SD) 5.48 (±3.00) 6.50 (±4.44) N2 (min); mean (SD) 49.46 (±11.01) 47.29 (±6.33) N3 (min); mean (SD) 25.40 (±7.27) 26.35 (±5.30) REM (min); mean (SD) 19.67 (±8.33) 19.87 (±4.45) AI (n/h); mean (SD) 9.54 (±5.56) 13.14 (±18.29) AHI (n/h); mean (SD) 1.93 (±6.88) 1.04 (±1.19) LPMI (n/h); mean (SD) 2.72 (±7.43) 1.38 (±2.35)

4. Discussion This study aimed to explore subjective sleep complaints and polysomnographic findings in ARMS individuals. The results suggested that individuals in ARMS reported significantly worse quality of sleep compared to HC, as evidenced by higher scores on the Pittsburgh Sleep Quality Index. The ARMS group had global scores N 5, indicating great difficulty in at least two parameters or moderate difficulties in more than 3. In addition to these data, which depended upon the perceptions of individuals about sleep itself, the ARMS group showed an increase in SL and in REMOL on the PSG, compared to the HC group,

Table 4 Comparison between individuals in UHR for psychosis and at-risk for BD. At-risk for psychosis At-risk for BD (n = 13) (n = 7)

Table 3 Comparison of PSG findings between the ARMS group and HC group. ARMS (n = 20)

ARMS. There were no significant differences in the other parameters listed in Table 3 between the ARMS and HC groups. Considering only the ARMS group, there were no differences between the individuals at risk for psychosis and those at risk for BD, either in subjective or polysomnographic parameters, as detailed in Table 4.

T-value

P-value

−0.284 −1.542 −2.273 2.233 −1.312 −0.284 0.764 −0.472 −0.338 −0.338 −1.388 −0.591

0.779 0.123 0.023 0.032 0.192 0.776 0.451 0.639 0.738 0.738 0.174 0.620

ARMS: at-risk mental state; HD: healthy controls; SD: standard deviation min: minutes; TST: total sleep time; SE: sleep efficiency; SL: sleep latency onset; REMOL: Rapid Eye Movement Sleep Onset Latency; WASO: wake time after sleep onset; N1: non-REM sleep stage 1; N2: non-REM sleep stage 2; N3: non-REM sleep stage 3; REM: rapid eye movement sleep stage; AI: arousal index; AHI: apnea/hypopnea index; LPMI: leg periodic movements index. Bold represents statistical significant associations.

TST min, mean (SD) 386.86 (±74.34) SE %, mean (SD) 88,67 (±5.30) SL min, mean (SD) 19.82 (±13.03) REMOL min, mean (SD) 126,44 (±54,52) WASO min, mean (SD) 28.62 (±20.94) N1 min, mean (SD) 5.01 (±1.80) N2 min, mean (SD) 47.27 (±11.00) N3 min, mean (SD) 26.78 (±7.00) REM min, mean (SD) 20.95 (±7.82) AI, mean (SD) 10.10 (±6.06) AHI, mean (SD) 2.77 (±8.52) PLM, mean (SD) 3.62 (±9.12) Pittsburg score, 8.15 (±3.48) mean (SD) Epworth score, 7.69 (±4.55) mean (SD)

346.37 (±96.78) 78.61 (±23.10) 37.41 (±27.05) 113.71 (±50.91) 66.03 (±85.13) 6.36 (±4.54) 36.6 (±10.58) 22.83 (±7.58) 17.29 (±9.35) 8.50 (±4.75) 0.37 (±0.42) 1.04 (±1.90) 6.86 (±4,18) 9.14 (±3.93)

Test value

P-value

−0.991 −0.238 1.986 −0.509 −0.674 0.958 1.229 −1.172 −0.934 −0.396 −0.532 −0.293 0.741

0.351 0.817 0.062 0.617 0.536 0.351 0.235 0.256 0.363 0.699 0.643 0.817 0.408

0.520 0.643

min: minutes; TST: total sleep time; SE: sleep efficiency; SL: sleep latency onset; REMOL: Rapid Eye Movement Sleep Onset Latency; WASO: wake time after sleep onset; N1: nonREM sleep stage 1; N2: non-REM sleep stage 2; N3: non-REM sleep stage 3; REM: rapid eye movement sleep stage; AI: arousal index; AHI: apnea/hypopnea index; LPMI: leg periodic movements index.

Please cite this article as: Zanini, M.A., et al., Abnormalities in sleep patterns in individuals at risk for psychosis and bipolar disorder, Schizophr. Res. (2015), http://dx.doi.org/10.1016/j.schres.2015.08.023

M.A. Zanini et al. / Schizophrenia Research xxx (2015) xxx–xxx

which, in turn, was predominantly composed of “good sleepers” according to the Pittsburgh Sleep Quality Index. In our study, individuals from the ARMS group showed an average increase of 13 min in SL, compared to the HC group. Lunsford-Avery (2013) associated increases in latency and sleep fragmentation (accessed by the Index of the Pittsburgh Sleep Quality) with negative symptoms in ARMS individuals compared to healthy controls. Furthermore, in adolescents at risk for psychosis, increased SL and decreased SE were associated with bilateral volumetric reductions in the thalamus, which is a structure that is important for sleep health. However, the increase in sleep latency in the ARMS group in our study was not severe. The increases in both SL and REMOL showed that the ARMS individuals required more time to fall asleep and, once sleeping, entered REM sleep later than the HC group. During REM sleep, the processing of memories and emotions occurs, together with generalized muscular weakness (Walker, 2009). It is understandable that individuals in the HC had perceptions of better quality sleep as evidenced by the Pittsburgh Sleep Quality Index because they both fell asleep and entered REM sleep more rapidly than the ARMS group. An interesting aspect of our results is the presence of a longer REM latency in ARMS compared with HC, which contrasts with some data indicating shorter REM latency in schizophrenia, BD and especially major depressive disorder (Gruber et al., 2011; Keshavan et al., 1990; Poulin et al., 2003; Tandon et al., 1992). Although it is not possible to be sure why ARMS individuals have a longer REM latency, one hypothesis is that because of their functional decline, this group shows a reduction in active activities and takes more and longer naps during the day, reducing their sleep pressure as described by Borbély and Achermann (1992). According to Borbély and Achermann's sleep homeostasis model, a sleep/wake dependent process (Process S) underlies the rise of sleep pressure during waking hours and their decay during sleep, and disruptions in the sleep wake cycle, with naps and inadequate sleep hygiene, can reduce the pressure for sleep, leading to a delay in deepening sleep. This hypothesis should be confirmed in sleep–wake studies with this population. Regarding the assessment of daytime sleepiness, participants from both groups had scores consistent with mild daytime sleepiness, without statistically significant differences between them. This finding can be explained by reductions in total sleep time evident in both groups, both of whom slept 380 min on average, while the population is expected to sleep approximately 480 min (Horne and Ostberg, 1975). In a cross-sectional study conducted by Gruber et al. (2011), a total time of sleep shorter than 6 h and longer than 9 h in BD patients was associated with reduced quality of life. Evening individuals, who have a greater willingness in the day and who sleep later and feel less productive in the morning, commonly report sleep deprivation (Dagys et al., 2012). Although the impact of chronotype depends on socially established schedules, evening people frequently are not able to follow their chronotype, tending towards chronic sleep deprivation. In the present study, there was no relationship between sleep deprivation and chronotype, probably because our sample consisted primarily of indifferent subjects. Taken together, our results indicated the presence of changes in the subjective evaluation of sleep quality in the ARMS group, compared with a HC group, and increased SL and REMOL in ARMS patients. These findings explain the moderate scores on the Epworth scale, even in the control group. Thus, one could assume that the changes found in the group of ARMS cases were due to a state of abnormal functioning of the central nervous system. Future studies could identify more specifically the relationships between sleep disturbances and other functional measurements, such as cognitive performance, using assessments of brain structure such as those obtained by structural neuroimaging. Furthermore, our results indicated that sleep disturbances could already be found in the very early stages of severe mental illnesses, offering a foundation for further study of sleep abnormalities

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as a possible predictor of the transition to psychosis or BD in individuals at risk. The results of this study should be interpreted in light of its limitations. The relatively small sample size did not allow for definitive conclusions about the absence of differences in some parameters or for subgroup analyses. However, even in this small sample, it was possible to demonstrate differences in the perception of sleep quality and in polysomnographic findings related to SL and REMOL. Another limitation was the use of medications by part of the sample, which might have had an impact on subjective and objective parameters. Nevertheless, this study also has important strengths. The enrolled patients were submitted to an extensive assessment such that only individuals in ARMS, according to standardized criteria, were included, and there was no recruitment of people who had already exceeded the threshold for psychosis or BD. Furthermore, the use of PSG for two nights assured greater adaptation of the subjects to the exam environment, thereby minimizing false-positive results. Taken together, the results of this study indicated that sleep abnormalities could be found early in the course of mental diseases, even in at-risk stages, and support the further investigation of their predictive value in the transition to psychosis and BD.

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Please cite this article as: Zanini, M.A., et al., Abnormalities in sleep patterns in individuals at risk for psychosis and bipolar disorder, Schizophr. Res. (2015), http://dx.doi.org/10.1016/j.schres.2015.08.023