Abstract
Background
Sleep-related characteristics in schizophrenia patients and circadian rhythms in the etiology and course of schizophrenia continue to be investigated. This study aims to compare chronotype characteristics in schizophrenia patients, their unaffected siblings as a familial/genetic risk group and healthy controls.
Methods
The study was conducted with 171 individuals, including 56 schizophrenia patients, 56 siblings, 59 controls. Structured Clinical Interview for DSM-5, Munich Chronotype Questionnaire(MCQ) were applied to all participants, Brief Psychiatric Rating Scale, Calgary Scale for Depression in Schizophrenia were applied to the patient group, and Patient Health Questionnaire-9 was applied to the sibling and control groups.
Results
The corrected midsleep on free days of the three groups calculated according to MCQ are: patients 4:32 ± 1:55; siblings 4:31 ± 1:22; controls 4:36 ± 1:01. No statistically significant difference was found between the three groups in terms of corrrected sleep midpoint means, radian value means, and chronotype distributions calculated using MCQ (respectively; p > 0.952, p = 0.934, p = 0.376). Retrospective evaluation of the premorbid period showed that the morningness type was more common and the intermediate type was less common in the schizophrenia group compared to the control group. The sibling group showed a distribution between these two groups (p = 0.023). While the mean radian values for the mid-sleep points did not differ between the groups, a significant difference was found in terms of variance (schizophrenia: 0.119; sibling: 0.062; control: 0.036, p < 0.001). The variance of premorbid sleep midpoints radians was also found to be higher compared to the control group (schizophrenia: 0.1730; control: 0.0732, p = 0.001). The midpoint of sleep shifted to earlier hours with increasing age, and tended to shift to later hours with daily screen time, daily coffee consumption, and evening cigarette use (p < 0.05).
Conclusions
These findings suggest that schizophrenia patients have endogenous difficulties in regulating circadian rhythms and that their siblings may have similar, but milder, irregularities. Circadian irregularities seen in schizophrenia patients may be an independent phenomenon of this disorder and may be present the onset of the disease. So this situation should be taken into account in the evaluation of individuals at risk.
Keywords: Schizophrenia, Chronotype, Sibling, High risk of psychosis, Circadian rhythm, Morningness-eveningness
Background
Schizophrenia is a devastating and chronic mental disorder affecting 1% of the world’s population and characterized by cognitive, emotional, perceptual and behavioral disorders. Although the pathophysiology has not yet been fully elucidated, it is known that various biological, psychological and environmental factors contribute to the etiology [1–3]. Among these factors, family history stands out as one of the strongest predictors of risk. Family and twin studies consistently indicate that the familial aggregation of schizophrenia is largely attributable to shared genetic rather than environmental influences. According to a recent meta-analysis, first-degree relatives of an individual with schizophrenia have an approximately eightfold increased risk compared with relatives of healthy controls, and this risk increases further when more than one family member is affected [4, 5].
In recent years, circadian rhythms and chronotype expressions have received increasing attention in the etiology and course of schizophrenia. Considering that 40%-50% of sleep patterns and “chronotype” are genetically based [6], these factors may play a role as a potential endophenotype in schizophrenia patients. Supporting this view, a previous study demonstrated a significant association between chronotype and neurological soft signs in schizophrenia [7].
According to the differences between the circadian rhythms, people are divided into three different chronotypes: the morning chronotype, the intermediate chronotype and the evening chronotype. Individuals in the morning chronotype go to bed early, get up early and reach their peak mental and physical performance in the morning, while individuals in the evening chronotype go to bed later, get up later and reach their peak performance in the evening.Intermediate chronotypes are individuals who do not have a morning or evening preference and whose bedtime and wake-up times are between these two chronotypes [8].
Some studies have shown that the evening chronotype is a risk factor for severe mental disorders [9]. Studies have reported that schizophrenia patients have high levels of evening hronotypes [10–12] and that evening chronotypes show higher psychotic symptom severity in clinical [10] and non-clinical samples [13]. However, some studies have reported that patients with psychosis have a morning chronotype [14], evening chronotype [10] or intermediate chronotype [15], suggesting that there are conflicting data in the literature on chronotype. However, it has been reported that circadian mismatch and sleep-wake rhythm disorders in schizophrenia patients occur even in stable periods [16] and cannot be explained by daily functions, suggesting that these disorders may not only be a symptom of the disease but also an individual feature that occurs independently of the mental disorder [17].
This raises the question of whether chronotype characteristics contribute to predisposition in the development of schizophrenia or are indicators of predisposition. Understanding chronotype in individuals with elevated familial and genetic risk may help address this gap. Risk groups for schizophrenia have been conceptualized in various ways in the literature: clinical high-risk for psychosis, at-risk mental state, prodromal, ultra-high-risk. Various authors have used various criteria to define these risk groups. These criteria include attenuated psychotic symptoms, brief limited intermittent psychotic episode, genetic risk; family history or first-degree relative with psychosis, schizotypal personality disorder, and functional detoriation. Recent studies have shown that approximately 22–29% of individuals in the high-risk group for psychosis transition to psychosis within the first three years following diagnosis [18] and approximately 12% have a first-degree relative with psychosis [19]. In this respect, unaffected first-degree relatives of patients represent an important population for investigating vulnerability markers associated with psychosis risk.
Evening chronotype in schizophrenia patients can be considered as a factor that negatively affects the course of the disease and impairs daily functioning. If chronotype contributes to clinical outcomes and reflects genetic vulnerability, examining chronotype patterns before the onset of psychosis—and in individuals at familial risk—becomes highly relevant. The number of studies that included siblings of schizophrenia patients is limited. In a study where the chronotype characteristics of siblings and schizophrenia patients were assessed with Morningness-Eveningness Questionnaire, the chronotypes of the patients and siblings were found to be similar to controls [20]. This confusing result indicates that the subject needs further investigation. Therefore, it was aimed to investigate the chronotype characteristics in schizophrenia patients and their siblings.
Based on most of these findings, it is hypothesized that the chronotype preferences of schizophrenia patients differ from healthy controls; the evening chronotype is more prevalent among schizophrenia patients. Furthermore, a milder but similar pattern may be present in unaffected siblings, reflecting genetic or familial vulnerability. And that the evening chronotype may be more prevalent in patients with schizophrenia in the pre-illness state. Therefore, the aim of this study was to compare the chronotype characteristics of schizophrenia patients, their unaffected siblings and healthy controls to assess the association of chronotype preference with genetic/familial psychosis risk.
Methods
This study was planned as a cross-sectional observational descriptive study and was conducted in the Psychiatry Clinic of an affiliated University Hospital.
Ethical considerations
Ethics committee approval of the study was obtained from the Clinical Research Ethics Committee No. 1 of the Ankara Bilkent City Hospital (Number: E1-23-3762) on 12/07/2023. Written informed consent was obtained from all the participants and, when necessary, their legal guardians. The study was conducted in accordance with the Declaration of Helsinki.
Participants
The study was conducted between August 2023 and November 2023 at the Psychiatry Clinic of Ankara Bilkent City Hospital. Schizophrenia patients who were admitted to the clinic as outpatients or hospitalized and their unaffected siblings were consecutively included in the study. In addition, a healthy control group consisting of hospital employees and their relatives were included in the study.
All participants were required to be between the ages of 18 and 65, to be able to read and write, to speak Turkish as their native language and to agree to participate in the study. All patients diagnosed with schizophrenia according to DSM-5 (Diagnostic and Statistical Manual of Mental Disorders 5th edition) criteria were clinically stable. In inpatients, evaluation was performed after response or remission. All of the patients were on antipsychotic medication. For the sibling group, it was required that the schizophrenia patient included in the study had a sibling, did not have psychotic disorder and agreed to participate in the study. If there was more than one sibling who met these conditions, the selection was made so that the most demographically similar sibling was selected.
Individuals with psychiatric illness as a result of SCID-5 interview in the control group and those with any psychotic disorder in the sibling group were not included in the study. For all three groups, individuals with a comorbid diagnosis of alcohol and substance use disorder, comorbid mental retardation, dementia, organic mental disorder and any neurological disease that may affect mental processes, and individuals with shift work were excluded.
Process
Informed consent forms were obtained from all participants. All participants were first diagnostically interviewed using the DSM-5 Structured Clinical Interview for Mental Disorders (SCID-5). A sociodemographic data form was completed by the investigators for all participants, and the Munich Chronotype Questionnaire was administered to all three groups. Brief Psychiatric Rating Scale (BPRS) and Calgary Schizophrenia Depression Scale (CSDS) were applied to the schizophrenia group. In order to retrospectively evaluate the chronotypes of schizophrenia patients before they became ill, the Munich Chronotype Questionnaire was completed for the pre-illness period by interviewing the patients and their relatives. The Munich Chronotype Questionnaire and Patient Health Questionnaire were administered separately to the sibling and control groups.
Data collection tools
Sociodemographic data form
It is a form created by the researchers to record the sociodemographic characteristics of the participants. In this form, information such as age, gender, marital status, educational status, comorbidities, smoking-alcohol-substance use were collected.
Structured Clinical Interview for DSM-5 (SCID-5)
The DSM-5 Oriented Diagnostic Interview is designed to guide interviewing to make a diagnosis according to the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders. It was developed by First [21] and adapted into Turkish by Elbir et al. [22]. In this study, it was used to diagnostically evaluate the participants, to confirm the diagnosis of schizophrenia patients, and to identify any psychiatric illness in the sibling and control group and to exclude them from the study if necessary.
Munich Chronotype Questionnaire (MCQ)
The MCQ was developed by Roenneberg et al. [23]. It is used to assess individual circadian expressions. It asks simple questions about sleep-wake behavior separately for work and non-work days, and can assess it according to the local time appropriate to the geographical location of the individual. The MCQ is a self-report scale consisting of 7 subsections: personal information, work schedule, work details, sleep time on work days, sleep time on vacation days, time spent outdoors on work and vacation days, and stimulant use. The scale uses three basic parameters. (a) the midpoint of the start and end times of sleep on working days (b) the midpoint of the start and end times of sleep on free days (c) the midpoint of the start and end times of sleep on free days with an adjustment for sleep deprivation on working days (sleep-corrected midsleep on free days: MSFsc). It has been reported that there is a high correlation between the Adjusted Sleep Midpoint and biochemical markers such as melatonin, cortisol and physiological measures such as sleep behavior measured by actigraphy [24]. Therefore, in this study, it was preferred to use this scale to determine the chronotype preferences of the participants. The Turkish validity and reliability study of the MCQ-TR was conducted by Erdoğan et al. in 2021 [25].
Brief Psychiatric Rating Scale (BPRS)
The BPRS is one of the most frequently used scales to assess the severity of psychopathology in patients with schizophrenia. It is scored by the clinician, taking into account the patient’s statements during the interview with the patient and the behaviors observed in some items. The 18 items are scored on a Likert scale of 1–7. Higher scores indicate higher disease severity. It was developed by Overall and Gorham in 1962 [26]. In this study, it was used to assess the severity of psychotic symptoms in the patient group.
Patient Health Questionnaire-9(PHQ-9)
It is a self-report scale derived from the Patient Health Questionnaire that asks about 9 symptoms of depression according to DSM-IV criteria. When the PHQ-9 is administered, the respondent is asked to report how often they have experienced nine depressive symptoms during the last two weeks, with the options “Never”,“Some days”, “More than half of the days” and “Almost every day”. In the evaluation, 1–4 indicates minimal depression, 5–9 indicates mild depression, 10–14 indicates moderate depression, 15–19 indicates moderate-severe depression, and 20–27 indicates severe depression. The Turkish validity and reliability study of the scale was conducted by Sarı et al. and the cronbach alpha coefficient was calculated as 0.842 [27].
Calgary Depression in Schizophrenia Scale(CSDS)
It is a four-point Likert-type scale consisting of 9 items to assess schizophrenia patients in terms of depression and to measure the level and severity of depressive symptoms. The cut-off score for schizophrenia accompanied by depressive disorder in the Turkish version of the CSDI was determined as 11/12 [28]. It was developed by Addington et al. [29] and adapted to Turkish by Aydemir et al. in 2000 and the cronbach alpha coefficient was found to be 0.901 [28].
Statistical analysis
Descriptive statistics are presented as mean and standard deviation or median and interquartile percentage for continuous variables, and frequency and percentage for categorical variables. The normal distribution properties of the data were evaluated using the Kolmogorov-Smirnov test and taking into account the kurtosis and skewness values. Chi-square test was used to compare categorical variables, Student’s t test and ANOVA tests were used to compare numerical variables. Repeated Measures t-test was used to examine repeated measurements in the same group. The Rayleigh test and Watson-Williams Tests were also used to analyze circular variables such as the clock indicating the midpoint of sleep by calculating radian values. Bootstrap permutation test was used to examine the variance difference of the groups, and Levene’s test for homogeneity of variance was used to compare the past and current variance values of the same group. Circular Regression Analysis was used when regression analysis was required. If the p value was less than 0.05, the difference between the groups was considered statistically significant. Bonferroni correction was used when post-hoc correction was required. Statistical analysis was performed using IBM SPSS Statistics 26.0 for Windows, Jamovi 2.6 and R programs (circular and ggplot2).
Results
The study included 63 schizophrenia patients admitted to our clinic between August 2023 and November 2023, Although the patients agreed to participate in the study, 3 of the sibling group members were not included in the study because they refused to participate. Four siblings were not included in the analyses due to missing data. Of the 63 participants who were evaluated as healthy controls, 4 were excluded from the study due to their use of SSRI/SNRIs for anxiety disorder. As a result, 56 patients with schizophrenia, 56 unaffected siblings of these patients and 59 healthy controls were included in the study. Sociodemographic data of the participants are presented in Table 1.
Table 1.
Sociodemographic and clinical characteristics of the groups
| Variable (n(%)) | Total (n = 171) | Schizophrenia | Siblings | Control | p |
|---|---|---|---|---|---|
| Age(years), (mean ± SD) | 35.9 ± 10.76 | 37.02 ± 10.71 | 37.2 ± 9.90 | 33.54 ± 11.35 | 0.106 |
| Gender | < 0.001* | ||||
| Female | 91(53.2) | 12(21.4)a | 35(62.5)b | 44(74.6)b | |
| Male | 80(46.8) | 44(78.6)a | 21(37.5)b | 15(25.4)b | |
| Employment | < 0.001* | ||||
| Unemployed | 40(23.4) | 26(46.4)a | 10(17.9)b | 4(6.8)b | |
| Student | 22(12.9) | 2(3.6)a | 3(5.4)a | 17(28.8)b | |
| Works independently | 68(39.8) | 11(19.6)a | 29(51.8)b | 28(47.5)b | |
| Working with support | 4(2.3) | 4(7.1)a | 0(0)a | 0(0)a | |
| Housewife | 23(13.5) | 4(7.1)a | 12(21.4)b | 7(11.9)a, b | |
| Retired | 9(5.3) | 4(7.1)a | 2(3.6)a, b | 3(5.1)b | |
| Disability retiree | 5(2.9) | 5(8.9)a | 0(0)b | 0(0)a | |
| Marital status | < 0.001* | ||||
| Single | 90(52.6) | 39(69.6)a | 19(33.9)b | 32(54.2)a, b | |
| Married | 65(38.0) | 8(14.3)a | 31(55.4)b | 26(44.1)b | |
| Widowed | 1(0.6) | 0(0)a | 1(1.8)a | 0(0)a | |
| Seperated/divorced | 15(8.8) | 9(16.1)a | 5(8.9)b | 1(1.7)b | |
| Education year(mean ± SD) | 13.5 ± 4.33 | 11.2 ± 3.88a | 13.6 ± 3.80b | 15.5 ± 4.24c | < 0.001* |
| Tobacco consumption, N(%) | < 0.001* | ||||
| Never used | 85(49.7) | 13(23.2)a | 32(57.1)b | 40(67.8)b | |
| Smoker | 76(44.4) | 39(69.6)a | 24(42.9)b | 13(22.0)b | |
| Ex-smoker | 10(5.8) | 4(7.1)a, b | 0(0)b | 6(10.2)a | |
| Alcohol use, N (%) | 0.032* | ||||
| Not using | 133(77.8) | 50(89.3)a | 42(75.0)a, b | 41(69.5)b | |
| Social drinker | 38(22.2) | 6(10.7)a | 14(25.0)a, b | 18(30.5)b | |
| Substance use N(%) | 0.356 | ||||
| No | 170(99.4) | 55(98.2) | 56(100) | 59(100) | |
| Yes | 1(0.6) | 1(1.8) | 0(0) | 0(0) | |
| Comorbid diseases | 0.001* | ||||
| No | 137(80.1) | 36(64.3)a | 48(85.7)b | 53(89.8)b | |
| Yes | 34(19.9) | 20(35.7)a | 8(14.3)b | 6(10.2)b | |
| Psychiatric disorder | < 0.001* | ||||
| No | 110(64.3) | 0(0)a | 51(91.1)b | 59(100)b | |
| Yes | 61(35.7) | 56(100)a | 5(8.9)b | 0(0)b | |
| Family history | < 0.001* | ||||
| No | 88(51.5) | 31(55.4)a | 0(0)b | 57(96.6)c | |
| Yes | 83(48.5) | 25(44.6)a | 56(100)b | 2(3.4)c | |
| BMI(kg/m2)(mean ± SD) | 26.82 ± 5.52 | 28.81 ± 6,28a | 25.97 ± 3.87b | 25.74 ± 5.66b | 0.004* |
Categorical variables are shown as N (%) and continuous variables as (mean ± SD). Categorical variables were analysed by the chi-square analysis method; continuous variables were analysed by ANOVA method. p<0.05 was considered significant. mean ± SD: Mean±standard deviation; Different uppercase letters indicate a significant difference between the column ratios as a result of chi-square analysis and Bonferroni correction
The mean age of the participants was 35.9 ± 10.8 years and there was no significant difference between the three groups in terms of mean age (p = 0.115). When gender distribution was analyzed, it was observed that the proportion of males was higher in the patient group compared to the sibling and control groups (81%, 37.5%, 25.4%; p < 0.001). In terms of marital status, the majority of individuals in the patient group had never been married (71.4%), while the proportion of married individuals was higher in the sibling and control groups (%55.4 ve %44.1, p < 0.001). In terms of education level, the patient group had the lowest education level (11.0 ± 3.8 years), while the sibling group had less education than the healthy control group(13.6 ± 3.8 and 15.46 ± 4.2 years, p < 0.001). In terms of employment status, the proportion of individuals working in an income-generating job is significantly lower in the patient group (%25.4, %51.8, %47.5; p < 0.001). BMI value of the patient group was higher than the other two groups(28.42 ± 6.13, 25.90 ± 3.86, 25.70 ± 5.65 kg/m²; p = 0.010). Smoking was highest in the patient group (66.7%, 42.9%, 22.0%), whereas alcohol use was highest in the control group (9.5%, 30.5%; p = 0.013). The presence of additional medical diseases is significantly higher in the patient group (%34.9, %14.3, %10.2; p = 0.001). A significant difference was found between the groups in terms of family history of psychiatric disorders, and the highest rate was found in the sibling group (100%, 44.4%, 3.4%; p < 0.001) (Table 1).
When looking at the medications used by the participants; thirty-seven of the patients were using a single antipsychotic, and 19 were receiving antipsychotic polypharmacy. The medications used as monotherapy were as follows: aripiprazole oral/LAI (7/3), paliperidone palmitate/oral (7/2), olanzapine oral (7), risperidone oral/LAI (2/2), amisulpride (2), haloperidol decanoate (2), clozapine (2), and quetiapine (1). Of the combination antipsychotic treatments, 4 involved clozapine augmentation, while 15 consisted of combinations of other antipsychotics. Only 2 of the siblings were using SSRIs (sertraline, escitalopram) for anxiety disorder and obsessive–compulsive disorder. Since the types of drugs used were numerous, further analyses were not performed according to the drugs used.
When the clinical scale scores were compared, PHQ-9 scores were found to be similar in siblings and control group(respectively; 7.11 ± 5.38 and 6.22 ± 3.61; p = 0.299). The BPRS score was 21.48 ± 9.81 and the CDSS score was 1.29 ± 1.75.
The mean sleep-corrected midsleep point (MSFsc) of the participants was 4:33 ± 1:28 and no significant difference was found between schizophrenia (4:32 ± 1:55), sibling (4:31 ± 1:22) and control (4:36 ± 1:01) groups (p = 0.952). Chronotype distributions were determined based on the cut-off values (3:38 − 8:27) reported in the Turkish adaptation of the Munich Chronotype Questionnaire, but no significant difference was observed between the groups (p = 0.376). When the pre-diagnosis corrected sleep midpoint and chronotype distributions of the patient group were calculated, the mean MSFsc was 4:02 ± 1:40 and no significant difference was found between the sibling and control groups (p = 0.071). Pre-disease chronotype distribution was 48.0% intermediate type and 52.0% morning type. No significant difference was found when the pre-disease and current MSFsc values of the patient group were compared (p = 0.077) (Tables 2 and 3).
Table 2.
Chronotype rates determined according to MSFsc based on cut-off values
| Patients n(%) |
Siblings n(%) |
Controls n(%) |
p | ||
|---|---|---|---|---|---|
| Chronotype according to MSFsc in the last 1-month N (%) | Morning type | 20(35.7) | 17(30.4) | 14(23.7) | 0.376 |
| Intermediate type | 35(62.5) | 39(69.6) | 45(76.3) | ||
| Evening type | 1(1.8) | 0(0) | 0(0) | ||
| Chronotype according to MSFsc Before Diagnosis N (%) | Morning type | 26(52.0)a | 17(30.4)a, b | 14(23.7)b | 0.023* |
| Intermediate type | 24(48.0)a | 39(69.6)a, b | 45(76.3)b | ||
| Evening Type | 0(0) | 0(0) | 0(0) | ||
Chi-square analysis, Bonferroni correction was used. p < 0.05 was accepted significant
Table 3.
Mean MCTQ scores and midsleep time of three groups and comparison between groups
| Variable | 1. Patients | 2. Siblings | 3. Controls | p-value |
|---|---|---|---|---|
| Midpoint of Sleep (Pre-Diagnosis) | 4:02 ± 1:40 | 4:31 ± 1:22 | 4:36 ± 1:01 | 0.071 |
| (Min-Max) | (1:15 − 7:30) | (1:45 − 7:45) | (2:15 − 7:00) | |
| Midpoint of Sleep (Current) | 4:32 ± 1:55 | 4:31 ± 1:22 | 4:36 ± 1:01 | 0.952 |
| (Min-Max) | (0:40 − 9:00) | (1:45 − 7:45) | (2:15 − 7:00) |
MCTQ: Munich Chronotype Questionnaire MST: Mid-sleep Time. Oneway ANOVA test
When the radian values of the sleep midpoints of the three groups were calculated, the averages were found to be 1.184 for the patient group, 1.186 for the sibling group and 1.208 for the control group. In the analysis performed with the Watson-Williams test, no significant difference was found between the groups in terms of mean sleep midpoint radian values (F = 0.068, df1 = 2, df2 = 168, p = 0.934). However, it was found that the variances between the groups differed significantly.
In the pre-disease period analyses, the mean radians of sleep midpoints were calculated as 1.055 for the patient group, 1.186 for the sibling group and 1.208 for the control group. Watson-Williams test results showed that there was a statistically significant difference between the groups(F = 3.096, df1 = 2, df2 = 168, p = 0.048) (Table 4).
Table 4.
Means and variances of sleep midpoint radian values of the groups and comparisons between groups
| Watson-Williams test for homogeneity of means | Bootstrap permutation test of variances | |||||
|---|---|---|---|---|---|---|
| Groups | means (radian) | p-value | Variance | p-value | ||
| According to the current sleep midpoint | < 0.001 | |||||
| 1. Patient | 1.1842 | p:0.934 (for 3 group) | 0.1187 | Patient vs. Sibling | 0.004 | |
| 2. Sibling | 1.1858 | 0.0616 | Patient vs. Control | < 0.001 | ||
| 3. Control | 1.2077 | 0.0355 | Sibling vs. Control | 0.017 | ||
| According to the pre-diagnosis sleep midpoint | ||||||
| Watson-Williams test for homogeneity of means | Variance | p-value | ||||
| means (radian) | p:0.048 | 0.003 | ||||
| 1. Patient | 1.0552 | 1vs2 p:0.232 | 0.1730 | Patient vs. Sibling | 0.169 | |
| 2. Sibling | 1.1858 | 1vs3 p:0.062 | 0.1288 | Patient vs. Control | 0.001 | |
| 3. Control | 1.2077 | 2vs3 p:1.000 | 0.0732 | Sibling vs. Control | 0.017 | |
When the mean values of the pre-disease and current values of sleep midpoints in the patient group were analyzed by Rayleigh test, a significant difference was found between the averages (p < 0.001). The differences of the current and pre-disease sleep midpoint radian values of the patient group were analyzed by paired sample test, and the difference between the pre-disease and current values was found to be -0.127 rad, the minute equivalent of this was calculated as 29.14 min. Levene’s test was performed to test the homogeneity of the variances of the sleep averages of the patient group, and no significant difference was found between the pre-disease period and the current variance (Table 5).
Table 5.
Examining the current and pre-illness mid-sleep values of the patient group
| Current sleep midpoint | Pre-illness sleep midpoint | Difference | Rayleigh Test of Uniformity | Levene’s Test for Homogeneity of Variance | p-value | ||
|---|---|---|---|---|---|---|---|
| Mean radian | 11.842 | 10.552 | -0.1272 radyan (29.14 min) | R: 0.8855 | < 0.001 | ||
| Variance | 0.1187 | 0.0824 | F:2.2975 | 0.1325 | |||
Difference was calculated by paired sample test
The figure below shows the sleep midpoints of the three groups as a rose diagram (Fig. 1).
Fig. 1.
Rose diagram representation of sleep midpoint radians distributions.
Possible relationships between participants’ midseep point values and BPRS, CSDS, and PHQ-9 scores were examined using circular–linear correlation. No significant relationship was found between MSFsc and BPRS (r=-0.261 p: 0.149), CSDS (r = 0.153 p: 0.520), and PHQ-9 (siblings r = 0.218 p: 0.266; controls r = 0.166 p:0.444) scores.
When the factors affecting sleep midpoint (radian) were analyzed by regression analysis, age, daily screen exposure, daily coffee consumption and evening cigarette consumption had a significant effect on sleep midpoints(p < 0.05). It was found that a one year change in age can shift the sleep midpoint to 13 min 45 s earlier (phase advance), daily screen time (per hour) can shift the sleep midpoint to 16 min 02 s later, coffee consumption (cup) to 20 min 39 s later, and evening cigarette consumption (number) to 22 min 55 s later (phase lag) (Table 6).
Table 6.
Factors affecting radian values of midsleep points; circular regression analysis
| Variable | Estimate | Estimate Error | l-95% CI | u-95% CI | Bulk ESS | Tail ESS |
|---|---|---|---|---|---|---|
| Age * (year) | -0.06 | 0.02 | -0.11* | -0.02* | 30,435 | 16,561 |
| BMI(kg/m2) | -0.00 | 0.02 | -0.05 | 0.04 | 31,695 | 15,349 |
| Last Meal (hour) | 0.01 | 0.07 | -0.13 | 0.16 | 30,301 | 15,641 |
| Sibling group | -0.01 | 0.06 | -0.13 | 0.10 | 20,394 | 16,102 |
| Control group | -0.02 | 0.07 | -0.15 | 0.11 | 20,825 | 15,772 |
| Gender, male | -0.05 | 0.05 | -0.16 | 0.05 | 22,387 | 17,158 |
| Comorbidity, yes | 0.07 | 0.06 | -0.04 | 0.19 | 28,244 | 15,932 |
| Education Duration (year) | -0.03 | 0.03 | -0.08 | 0.02 | 27,883 | 14,680 |
| Daily Monitor Usage* (hour) | 0.07 | 0.02 | 0.02* | 0.11* | 30,919 | 15,293 |
| Workday per week | 0.02 | 0.03 | -0.03 | 0.07 | 24,753 | 16,688 |
| Outdoor duration workday (hour) | -0.01 | 0.02 | -0.06 | 0.04 | 28,917 | 15,233 |
| Outdoor duration weekend (hour) | -0.01 | 0.02 | -0.06 | 0.04 | 28,694 | 15,993 |
| Smoke per day (number per day) | -0.04 | 0.05 | -0.13 | 0.06 | 18,288 | 14,843 |
| Coffee per day* (cup per day) | 0.09 | 0.04 | 0.02* | 0.16* | 23,043 | 16,354 |
| Tea per day (cup per day) | -0.01 | 0.02 | -0.06 | 0.04 | 20,112 | 15,721 |
| Smoke in the evening*(number per day) | 0.10 | 0.05 | 0.01* | 0.19* | 17,796 | 14,968 |
| Coffee in the Evening (cup per day) | -0.04 | 0.03 | -0.11 | 0.02 | 23,751 | 16,786 |
| Tea in the Evening (cup per day) | 0.01 | 0.03 | -0.04 | 0.07 | 20,369 | 14,976 |
| Eating at Night, yes | 0.03 | 0.05 | -0.07 | 0.14 | 30,305 | 15,136 |
| Circular Regresyon Analysis *p < 0.05 | ||||||
| Further Distributional Parameters | ||||||
| Estimate | Estimate Error | l-95% CI | u-95% CI | Bulk ESS | Tail ESS | |
| Kappa | 8.66 | 0.94 | 6.90 | 10.56 | 5972 | 3088 |
Discussion
This study aims to investigate chronotype expressions in schizophrenia patients and their unaffected siblings, who constitute a familial/genetic vulnerability group, in comparison to healthy controls. In particular, it was investigated whether chronotype is a risk factor for schizophrenia and whether it can be considered as a marker independent of symptoms. The midpoint of sleep, which has a strong relationship with physiological indicators, was used as the basis for determining the chronotype, and it was found that the sleep midpoint means of the patient, sibling and control groups were similar. However, additional analyses performed to evaluate the differences in sleep characteristics revealed that the sleep midpoint distribution of the patients with schizophrenia differed from that of the healthy controls. In addition, it was observed that the siblings of the patients were in a position between the patients and the controls in this respect. These findings suggest that schizophrenia patients have sleep-related regulation difficulties and that this dysregulation may have existed before the onset of the disease. In particular, the fact that these sleep pattern differences were present before the onset of the disease and were also seen at a mild level in siblings who had not developed the disease suggests that these changes are not only associated with positive symptoms, but may instead be a biological feature that indicates a predisposition to schizophrenia. Because genetic/familial risk is not the same as clinical high risk for psychosis, which indicates a high risk of transition to psychosis, it is important for future studies to evaluate sibling groups according to clinical high-risk criteria for psychosis and to examine the chronotype characteristics of the high-risk group.
Our study is important because it is one of the rare studies examining whether chronotype characteristics are a potential risk marker in the development of schizophrenia. According to our hypothesis, it was expected that evening chronotype would be more common in patients and a distribution characteristic between patients and healthy controls would be observed among siblings. But the findings obtained do not support this expectation. In our sample, it was observed that the morning chronotype was higher in the patient group than in the control group, although this difference was not statistically significant. Similarly, our hypothesis that the patients have more evening chronotype could not be confirmed. One possible reason for this situation may be that some of the patients included in the study were inpatients and that in addition to taking medication in the inpatient clinic, their morning wake-up times were regularly monitored [12]. However, in the retrospective evaluation of the pre-treatment period, it was seen that the tendency to be morningness continued in the patients, and even the chronotype difference in this direction of morningness in the pre-disease period was significant, and it was seen that the siblings were between the patients and the controls in this respect. In the clinic where the study was conducted, the length of stay rarely exceeds 1 month. When the mean mid-sleep point of our patient group before diagnosis and in the last month was examined, the mean mid-sleep point in the last month was calculated as 04:32 while it was 4:02 before diagnosis. These suggest that the biased assessment of morningness originating from hospitalized patients is not that likely. After adolescence, morningness scores increase significantly with age [30–33]. In this context, it is possible that the average age in our sample was in adulthood and contributed to morningness in the patient group. Indeed, in the regression analysis, it was determined that age increased the tendency to be morningness by shifting the midpoint of sleep forward (phase advance).
Although the results are inconsistent [8–13], the general tendency in the literature is to accept that evening chronotype is more common in schizophrenia [8–10, 15]. In our sample, it was observed that the evening chronotype was extremely low, and only one patient had an evening chronotype preference in the last month. In this respect, no data was obtained to support the literature on this subject in this study. It is thought that further studies are needed to clarify the issue.
Another notable finding in this study is that the sleep midpoint values (minimum-maximum range) in schizophrenia patients showed a wider distribution compared to the sibling and control groups. This suggests that the circadian rhythm in the patients could not be sufficiently regulated. Considering the sleep midpoint distribution characteristics, the data were examined with circular analysis methods; rose diagrams revealed that the patients’ sleep midpoint radian values exhibited a wider and irregular distribution. Although the radian value means were found to be similar, it was determined in the variance comparisons that there was a difference between the sleep midpoint radian variances of the three groups.
On the other hand, when the patients’ midpoints of sleep in the premorbid period were compared, the radian value averages of the groups were found to be similar; a difference close to significance was detected between the patient and control groups. However, when the sleep midpoint variances before the illness were compared, it was observed that while the patient and sibling groups were similar, both groups were different from the control group. These findings suggest that there is an irregularity in the midpoints of sleep in schizophrenia patients, and therefore in their chronotypes and circadian rhythms. Perhaps one of the reasons why conflicting results can be reported in chronotype studies in schizophrenia patients can be interpreted as a reflection of this circadian irregularity [8–10, 12, 13]. In addition, studies on how sleep midpoint variability is at the individual level in schizophrenia patients can provide a new direction to the discussions on this subject. Observing the variability or irregularity in sleep midpoint among individuals in the patient group will be important in terms of revealing the difficulties these individuals experience in regulating their circadian rhythm.
One of the reasons underlying the variability in sleep midpoints, which is evident in patients but relatively greater in siblings than in controls, that is, the difficulty in regulating circadian rhythms, may be a shared genetic predisposition [34]. Another reason may be that the siblings accompanying the patients in the study had similar environmental conditions to the patients. Considering that some siblings were caregivers of the patients, the similarity of current environmental conditions may also explain their similar difficulties in circadian rhythms due to being affected by similar zeitgebers [35].
It is interesting whether these genetic and environmental factors that may affect circadian rhythm also pose a risk for psychosis. It is being investigated whether circadian rhythm changes are a feature of psychosis, and in particular schizophrenia, and whether circadian rhythm disorders contribute to the etiology [36, 37]. If so, it is important to conduct studies with siblings who share a common genetic risk, as in our study, to investigate this issue.
While it was expected that sleep midpoint/chronotype would be affected by symptoms severity of depression and psychosis, in this sample symptom severity did not significantly affect sleep midpoint. This may be due to the sample size and the inclusion of clinically stable patients for the patient group, which may have diminished the effect of symptom severity.
In regression analysis, it was determined that age caused phase advancement; daily screen time, daily coffee consumption and evening cigarette consumption had phase delaying effects. It is known that smoking, excessive caffeine consumption and long screen exposure time have negative effects on sleep patterns in healthy individuals [38, 39]. In schizophrenia patients, who we see having difficulty regulating their sleep rhythm, behaviors such as evening cigarette smoking and caffeine consumption may function as compensatory zeitgebers to cope with sleep rhythm irregularity. The phase delay observed in the current values of the midpoints of sleep in the patient group compared to the premorbid values may have been due to factors such as smoking, tea/coffee consumption, and screen exposure, in addition to the medications used.
It is possible that there are common neurobiological irregularities in the development of both circadian dysregulation and schizophrenia. Dopamine, the most important neurotransmitter in the pathogenesis of schizophrenia, is itself circadian regulated and acts as a powerful wake-promoting neurotransmitter in the regulation of sleep and the sleep/wake cycle, and there is evidence that it interacts directly with other neurotransmitter systems involved in the regulation of sleep and the circadian clock, including adenosine and glutamate via NMDA receptors [40]. In addition, circadian disruption in patients with schizophrenia may be due to abnormal synaptic networks and connectivity within the brain that characterize schizophrenia [41] or to a deficiency in clock gene expression. The fact that certain mutations in “clock” genes, which are involved in both circadian rhythm and brain maturation and differentiation, are associated with a higher risk of schizophrenia [42–46] and that the Melatonin 1 receptor gene polymorphism [47] is associated with schizophrenia also supports this claim.
It is important to evaluate the findings of our study by taking into account some limitations. The first and most important limitation of the present study is the presence of significant differences between the patient and healthy control groups regarding sociodemographic characteristics, particularly age and gender, which may have had an impact on the results. Secondly, siblings of patients with schizophrenia were included in this study due to their familial/genetic risk, but detailed assessments were not made for the criteria of clinical high-risk for psychosis, such as schizotypal personality disorder, attenuated psychotic symptoms, brief intermittant psychotic symptoms, or functional decline. Thirdly, the sample size may not have been large enough to detect minor changes in chronotype distribution, and further studies are needed to generalize the findings of this cross-sectional and single-center study to all patients with schizophrenia. However, premorbid sleep midpoints were assessed retrospectively. The reliability of the results may not be high enough due to recall bias. However, this limitation was tried to be controlled by detailed and face-to-face interviews with both the patient and the caregiver. The complex effects of the drugs used in the treatment of schizophrenia patients or the fact that some of the patients were taken from the inpatient clinic, which is a relatively controlled environment, may make it difficult to interpret the results. There is a need for studies that control these difficulties with larger and more homogeneous samples, with subgroup analyses based on the treatments they use, with longitudinal and individual-level analyses.
Conclusion
In conclusion, it is noteworthy that the mid-sleep point variance is higher in the patient and sibling groups compared to healthy controls. Although it is not yet possible to fully elucidate the complex relationship between circadian rhythm irregularity and psychotic findings, our study is promising in this regard. Our data suggest that the circadian rhythm regulation problem seen in schizophrenia patients may be an independent phenomenon and that these patients should be evaluated with a different approach. On the other hand, longitudinal studies to be conducted to evaluate the high risk in the first-degree relatives of the patients (parent, child, sibling) will shed more light on this issue if circadian rhythm irregularities are also considered. In order to manage circadian rhythm irregularities in schizophrenia patients and risky individuals, instead of methods such as smoking or excessive tea and coffee consumption, encouraging healthy lifestyle changes and beside targeting psychotic symptoms in psychopharmacological treatments, developing circadian rhythm regulating approaches may be clinically beneficial.
Acknowledgements
We are grateful to all participants of the study.
Abbreviations
- DSM-5
Diagnostic and Statistical Manual of Mental Disorders, 5th Edition
- SCID-5
Structured Clinical Interview for DSM-5
- MCQ
Munich Chronotype Questionnaire
- MSFsc
Mean corrected midsleep on free days
- BPRS
Brief Psychiatric Rating Scale
- PHQ-9
Patient Health Questionnaire-9
- CSDS
Calgary Depression in Schizophrenia Scale
- SSRI
Selective Serotonin Reuptake Inhibitors
- SNRI
Serotonin Noradrenaline Reuptake Inhibitors
Author contributions
Author Contributions Author ÖG, GZK, MU, EKŞ, EG made contributions to the conception and design of the study and ÖG wrote the protocol. ÖG, GZK managed the literature searches and analyses. ÖG collected the data. GZK and MU undertook the statistical analysis, All authors contributed to interpretation of data; ÖG and GZK wrote the first draft of the manuscript. All authors contributed to and have approved the final manuscript. All of the author have approved the submitted version, and have agreed both to be personally accountable for the author’s own contributions and to ensure that questions related to the accuracy or integrity of any part of the work, even ones in which the author was not personally involved, are appropriately investigated, resolved, and the resolution documented in the literature.
Funding
This research did not receive any grant from any funding agency.
Data availability
The data of this study has not been uploaded to any electronic media before. It will be shared if the editor(s) or the referees request.
Declarations
Ethics approval and consent to participate
Ethics committee approval of the study was obtained from the Clinical Research Ethics Committee No. 1 of the Ankara Bilkent City Hospital (Number: E1-23-3762) on 12/07/2023. Written informed consent was obtained from all the participants and, when necessary, their legal guardians. The study was conducted in accordance with the Declaration of Helsinki.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data of this study has not been uploaded to any electronic media before. It will be shared if the editor(s) or the referees request.