ABSTRACT
Delayed sleep phase disorder and advanced sleep phase disorder cause disruption of the circadian clock and present with extreme morning/evening chronotype with unclear role of the genetic etiology, especially for delayed sleep phase disorder. To assess if genotyping can aid in clinical diagnosis, we examined the presence of genetic variants in circadian clock genes previously linked to both sleep disorders in Slovenian patient cohort. Based on Morning-evening questionnaire, we found 15 patients with extreme chronotypes, 13 evening and 2 morning, and 28 controls. Sanger sequencing was used to determine the presence of carefully selected candidate SNPs in regions of the CSNK1D, PER2/3 and CRY1 genes. In a patient with an extreme morning chronotype and a family history of circadian sleep disorder we identified two heterozygous missense variants in PER3 gene, c.1243C>G (NM_001377275.1 (p.Pro415Ala)) and c.1250A>G (NM_001377275.1 (p.His417Arg)). The variants were significantly linked to Advanced sleep phase disorder and were also found in proband’s father with extreme morningness. Additionally, a rare SNP was found in PER2 gene in a patient with clinical picture of Delayed sleep phase disorder. The novel variant in PER2 (NM_022817.3):c.1901–218 G>T was found in proband’s parent with eveningness, indicating an autosomal dominant inheritance. We identified a family with autosomal dominant inheritance of two PER3 heterozygous variants that can be linked to Advanced sleep phase disorder. We revealed also a rare hereditary form of Delayed sleep phase disorder with a new PER2 variant with autosomal dominant inheritance, shedding the light into the genetic causality.
Introduction
Sleep phase disorders or circadian rhythm sleep disorders are defined as disorders where the structure and duration of sleep are usually not disrupted, but there is a change in the starting point of sleep, which begins a few hours earlier or later than expected and desired. The sleep phase is not in sync with other endogenous rhythms, i.e., there is a disruption of the circadian rhythms. The circadian clock is an internal time-keeping system that regulates a variety of physiological processes through approximately 24 h circadian rhythms in gene expression, which are translated into oscillation in metabolism and overall behavior (Kovac et al. Citation2019; Zmrzljak and Rozman Citation2012). In humans, the principal oscillator, the suprachiasmatic nucleus, is located in the hypothalamus. The nucleus acts as an autonomous timing mechanism, but is susceptible to extrinsic factors such as light (Hastings et al. Citation2018). On a molecular level, the circadian clock is a system of transcriptional translational feedback loops. In addition to the central clock, there are several peripheral oscillators intricately tuning human physiology to time of day (Hastings et al. Citation2018; Hirano et al. Citation2016; Ko and Takahashi Citation2006).The most prominent behavior under circadian control is the sleep wake cycle.
Circadian or sleep phase disorders can be caused by either intrinsic disruption of the rhythms or can be extrinsic i.e. behavioral (Hastings et al. Citation2018). They present as extreme morningness or eveningness and are normally manifested by daily fatigue and other symptoms resulting from lack of sleep, such as mood disorders and cognitive decline. These are rare disorders whose etiology is unclear, but the genetic component has been considered. Several links have been found between diurnal preference or circadian clock disruption and genetic variants, especially in large population studies (Hu et al. Citation2016; Jones et al. Citation2019; Lane et al. Citation2016).
Among the sleep phase disorders are the Delayed Sleep Phase Disorder (DSPD) and the Advanced Sleep Phase Disorder (ASPD). Both have been previously linked to circadian clock gene variants, especially the rarer, ASPD, with variants in CRY2, PER2, PER3 and CSNK1D genes () (Brennan et al. Citation2013; Carpen et al. Citation2005; Ojeda et al. Citation2013; Toh et al. Citation2001; Zhang et al. Citation2016). The more common DSPD may also have a genetic component, which remains less clear (Hohjoh et al. Citation2003; Patke et al. Citation2017). While the estimated prevalence of DSPD varies, it is believed to be more common in adolescents (Crowley et al. Citation2007; Micic et al. Citation2016; Paine et al. Citation2014). DSPD is defined as a permanent (lasting more than 6 months) shift of the time of onset of sleep, which is often delayed in the early morning hours (3.00 and later) (Zisapel Citation2001). When an individual does not adjust to the social schedule, wake up time is pushed into the late morning hours/early afternoon. When adapting to a social schedule, social “jetlag” occurs because of the lack of sleep (Roenneberg et al. Citation2019). Delayed sleep is clinically difficult to distinguish from behavioral sleep disorders or poor sleep hygiene. The main difference is that an individual with a real sleep disorder can in no way move the point of sleep to the early evening hours, but this effort is difficult to objectify. With ASPD, onset of sleep is set to earlier hours than desired and wake up point is earlier than desired as well.
Table 1. Overview of circadian sleep phase disorders with genetic etiology according to the OMIM catalog of human genes and genetic diseases with causative genes and loci, inheritance patterns, and clinical picture. FASPS 1,2,3 – Familial advanced sleep phase syndrome 1,2,3. DSPD – Delayed sleep phase disorder.
Our aim was to examine the presence of genetic variants previously linked to either ASPD or DSPD in the population of Slovene patients diagnosed with a familial circadian sleep disorder. We aimed to evaluate whether the genetic etiology is prevalent enough for genotyping to have a place when treating a patient with circadian sleep disorder.
The research was approved by the Commission of the Republic of Slovenia for Medical Ethics, no. 0120–587/2019/4. All participant of the study signed an informed consent.
Materials and methods
Selection of variants for genotyping
DNA variants associated with circadian sleep disorders were searched in the PubMed database. The search keywords were Sleep wake disorders/genetics. After reviewing the literature, we identified 28 variants in eight core clock or circadian-regulated genes associated with sleep disorders (Table S1). We chose variants with a clear association with the clinical picture of circadian sleep disorders in which a family pattern of inheritance was demonstrated shown in . Data on versions obtained in the literature were supplemented with data collected in the NCBI dbSNP databases (Sayers et al. Citation2020) and Ensembl (Cunningham et al. Citation2022). We used a web search engine and a tool to analyze the effects of human inherited variants VarSome (Kopanos et al. Citation2019). With the help of these, we supplemented the data on the region of the gene where the variant is located and a possible change in the sequence of the coding protein. For genotyping, we selected regions that include the nonsynonymous variants in CRY1, PER2, PER3 and CSNK1D genes.
Table 2. Chosen variants for genotyping of hereditary circadian clock disorders. Variants are managed in the ClinVar database as clearly correlating with the advanced or delayed sleep phase disorder (Landrum et al. Citation2018). RS ID – identification number assigned by the dbSNP database nt – nucleotide; AA amino acid chr. chromosome; Corr – correlation.
Selection of patients
As part of a retrospective study, we examined the presence of hereditary variants in selected circadian genes in the population of patients diagnosed with Disorders of the sleep-wake schedule (diagnosis G47.2, ICD − 10) treated at the Sleep center of the Clinical Institute of Clinical Neurophysiology from 2001 to September 2020. We found 73 patients diagnosed with delayed sleep phase and 5 with advanced sleep phase that were sent an invitation to participate with Morning-evening questionnaire (MEQ) (Horne and Ostberg Citation1976; Treven Pišljar et al. Citation2019) and Munich questionnaire (Roenneberg et al. Citation2003; Santisteban et al. Citation2018). In addition, we also invited patients who met the inclusion criteria during their treatment in the Sleep center of the Institute of Clinical Neurophysiology, University Medical Centre Ljubljana. 15 patients were included in the study, 13 with a diagnosis of delayed sleep phase and 2 with advanced sleep phase, together with 28 controls ().
Figure 1. From 78 participants with sleep problems, we finally included 15 patients, 13 with a diagnosis of delayed sleep phase and 2 with sleep advance. We also selected the control population from the volunteers who were, based on the MEQ questionnaire, proven to have a normal chronotype – altogether 28 controls. Created using Biorender.
Criteria for inclusion in a group of patients were extreme chronotype, assessed with MEQ, family history of circadian sleep disorder and age over 20 y.
Criteria for inclusion in the control group were age over 20 y, absence of classification in one of the extreme chronotypes assessed by the MEQ, and absence of a family history of circadian sleep disorders. Controls were invited to participate in the study mainly via mailing lists and consisted mostly of health professionals and students.
To assess the chronotype, we primarily used the MEQ questionnaire, which according to the number of points divided the subjects into one of five groups: extreme evening type (16–46 points), moderate evening type (47–52 points), intermediate type (53–64 points), moderate morning type (65–69 points) and extreme morning type (70–86 points). We additionally used the Munich Questionnaire in which an estimate of the chronotype is obtained in the form of the midpoint of sleep corrected for the sleep debt generated during the week (MSFsc). As the point cannot be calculated if the subject is using an alarm clock, the questionnaire was not the original criterion, as it could not be calculated for all participants.
Additionally, the rhythm of wakefulness and sleep was monitored in some subjects for 14 d with an actimeter (Actiwatch spectrum Pro, Philips Respironics, Murrysville, PA, USA), results represented in Figures S1 and S2.
Statistical analyses
To compare the averages of the calculated points collected with the validated MEQ (Treven Pišljar et al. Citation2019) and mid sleep time, with which we evaluated the chronotype between patients and controls, we used the one-way ANOVA using multiple comparisons to the control group. For statistical significance pvalue < 0.05 was considered. For averages, the standard deviation (SD) was given in parentheses.
Blood collection, isolation of DNA, and PCR amplification
Venous blood (6 ml) was collected in an EDTA tube, which was anonymously encrypted and stored at −80°C until DNA isolation. Genomic DNA was obtained by standard procedures using commercial kit (DNA Isolation Kit for Mammalian Blood, Roche Diagnostic Co., Indianapolis, IN, USA) and stored at + 4°C. Commercially available (Thermo Fisher Scientific, Inc., Waltham, MA, USA) starting oligonucleotides covering the regions with selected variants in the CSNK1D, PER3, CRY1 and PER2 genes were used to amplify the segments ().
Table 3. Amplified regions of the selected circadian clock genes.
PCR amplification was done on SimpliAmp Thermal Cycler using AmpliTaq Gold™ 360 Master Mix (both Thermo Fisher Scientific, Inc., Waltham, MA, USA) started with denaturation at 95°C for 10 min, followed by annealing for 30 s at 58.2°C for PER2 and PER3, at 62.1°C for CRY1 and 59.9°C for CSNK1D, with extension at 72°C for 1 min. After 30 cycles the reaction was stopped and the reaction products cleaned by Monarch® PCR & DNA Cleanup Kit (T1030, New England Biolabs, Ipswich, MA, USA).
Sanger sequencing and data analysis
The purified PCR products were prepared according to the Sample Submission Guide from Eurofins genomics LightRun Tube service (Eurofins Genomics Sequencing GmbH Köln, Germany), where Sanger sequencing was performed. Data analysis started in the Chromas software (Chromas 2.6. 6, Technelysium Pty Ltd, Australia), where we reviewed the entire sequence and looked for possible heterozygous variants that show up as a double peak. The determined variant sequences are presented in Supplementary Figure S3. Additionally, we used the Basic local alignment search tool (BLAST) to compare the obtained sequence with the reference sequences (RefSeq) in the human genome, thus checking whether we had multiplied the corresponding regions in the target genes (Altschul et al. Citation1990; Boratyn et al. Citation2012). The strength of the relationship between the presence of individual variants and the circadian clock disturbance was evaluated by calculating the odds ratios.
Results
Characteristics of the patients and determination of the chronotypes
After considering the inclusion criteria, we included 15 patients of which 13 presented with a clinical picture of extreme evening chronotype (DSPS) and 2 with extreme morning chronotype (ASPS). The control group included 28 individuals who did not have either of the two extreme chronotypes ().
Table 4. Demographic data of subjects included in the study. MEQ results: scores range from 16–86. Scores of 41 and below indicate “evening types.” Scores of 59 and above indicate “morning types.” Scores between 42–58 indicate “intermediate types.” SD – standard deviation. *MSFsc can only be calculated if the subject does not use an alarm clock to wake up on days off. In the case of controls, we were able to calculate MSFsc for 22 out of 28 controls.
The mean age in both the extreme evening chronotype group (range 23–53 y) and the control group (range 23–60 y) was 30 years. The One way ANOVA showed a statistically significant difference in MEQ score between both groups compared to control. The mean value of MEQ points, namely the average of MEQ points in the control group was 55.6 (±6.2) and in the group of patients with extreme evening chronotype, DSPS 35.5 (±5.2), and the difference between the averages was 20.1 (95% confidence interval (CI) 15.5–24.7, p < 0.0001). Patients with ASPS scored 72 and 82 points in MEQ, mean 77.0 (±7.1) and the difference between the averages was 21.4 (95%, CI 11.3–31.5, p < 0.0001) (). In the control group (data were known for 22/28 controls, )), the clock time indicating the midpoint of sleep corrected for a sleep length of 2.9 h (±0.8) was found, in the DSPS group of 6.4 h (±2.0) and in two patients with an ASPS the clock time indicating the midpoint of sleep was 0.5 and 2.75 hours, mean 1.6 h (±1.6). Statistically significant difference in the the clock time indicating the midpoint of sleep adjusted for sleep length was found between the control group and the DSPS (mean difference 3.7 h, 95% CI 2.4–4.6, p < 0.0001), while we did not find statistically significant difference between the control group and ASPS group (difference of 1.3 h on average (95% CI 1.1–3.7, p = 0.37)) ().
Figure 2. MEQ score (a) - differences in the number of points in the MEQ between the control group (n = 28) and the group of patients with an extreme evening chronotype – DSPD (n = 13) and extreme morning chronotype – ASPS (n = 2). Munich questionnaire chronotype (MSFsc) (b) for control group (n = 22) and both extreme chronotypes ASPD (n = 2) and DSPD (n = 13). Data are represented as mean ± standard deviation. For statistical testing, one-way ANOVA was used with following statistical significances, ****p < 0.0001.
Genotype analysis in selected gene regions in patients and in controls
Statistical evaluation of the relationship between the presence of clinical picture of sleep advance or sleep delay, and the presence of variants in selected genes shown in . We demonstrated a statistically significant association of c.1250A> G in the PER3 gene and the clinical picture of sleep phase advance with extreme morning chronotype.
Table 5. Relationship between the presence of extreme morning chronotype and the presence of variants in selected genes.
Table 6. Relationship between the presence of extreme evening chronotype and the presence of variants in selected genes.
Genotyping of family members
We collected detailed family history from both subjects where variants were found. We managed to genotype one additional affected family member in each family. Both variants in the PER3 gene (rs150812083 and rs139315125) were found in the father of the proband, who also clinically presented with extreme morning chronotype ().
Figure 3. (a) genetic pedigree of the family in which PER2 variant was detected: c.1901-218 G > T, dark-colored are genotyped family members who presented with DSPD. (b) Genetic pedigree of the family in which variants (c.1243C > G and c.1250A > G) in the PER3 gene were detected, dark colored are genotyped members with a clinical picture of extreme morning chronotype. Created using Biorender.
The novel variant in PER2: c.1901-218 G> T (rs1029124354) was also found in the parent of the proband. The parent clinically presented with eveningness, MEQ score showed mild eveningness ().
Discussion
Sleep phase disorders are an important topic of sleep research since they greatly affect the life quality of subjects. It is important to establish etiology to provide the most accurate diagnosis and guide the patients through the best possibilities of treatment. Due to the multifactorial nature, both genetic and environmental factors may lead to the disease phenotype which are both difficult to determine in the clinical practice. An example is the delayed sleep phase disorder that primarily affects adolescents and is significantly influencing their quality of life (Příhodová et al. Citation2022).
In our study we focused on the familial sleep phase disorders with a hereditary component. Using the MEQ we successfully selected 15 patients with extreme evening or morning phenotypes. As expected, eveningness is much more common compared to morningness, in our cohort 13/15 and 2/15, respectively. The second important step was to carefully select regions of genes for genotyping where the variants have already been linked to sleep phase disorders. We focused on the core clock circadian genes or their immediate output genes, since misalignment of the circadian clock represents a major cause for shifting the circadian phase also in animal models (Arble et al. Citation2010).
We identified two variants in the PER3 gene. PER3 encodes the period circadian protein homolog 3 protein in humans (Shearman et al. Citation1997). While PER1 and PER2 represent repressors of the core circadian clock and knockout mice with nonfunctional Per1 and Per2 genes remain arrhythmic (Bae et al. Citation2001) the exact role of PER3 remains unexplored. In addition to sleep phase disorders, variants of PER3 were linked previously to triglyceride levels during the pregnancy in association with preterm birth (Kovac et al. Citation2019), bipolar disorder (Brasil Rocha et al. Citation2017), Alzheimer’s disease (Lozano-Tovar et al. Citation2023) and extreme obesity (Azevedo et al. Citation2021), many of these pathologies having association with circadian rhythms.
In our cohort we identified two missense variant PER3:c.1243C>G and PER3:c.1250A>G, inherited as a haplotype and predicted to be pathogenic in causation of Familial Advanced Sleep phase disorder (Agarwala et al. Citation2016). The variants both have an estimated frequency of less than 0.01 (Cunningham et al. Citation2022). We demonstrated a statistically significant association between the clinical picture and the presence of both PER3 variants, confirming the hypothesis that some extreme chronotypes can be inherited. The missense mutation c.1243C> G is located at position 1 of codon 12 and causes the exchange of amino acid proline for alanine of the coded protein (p. Pro415Ala). In the NCBI database, the version is managed under the identification number rs150812083. The missense variant c.1250A> G causes the exchange of amino acid histidine for arginine (p. His417Arg) and is registered in the NCBI database under identification number rs139315125. The variants are managed as pathogenic in the database of clinically relevant variants of ClinVar and are associated with the clinical picture of familial ASPD (Zhang et al. Citation2016).
In addition to explaining the etiologies of the rare familial ASPD PER3 is also interesting because the role of the gene is not yet fully known. The group who originally linked the variants with clinical picture of ASPD also demonstrated that the presence of variants destabilizes the PER3 protein and thus impairs its function. The haplotype has a reduced ability to stabilize PER1 and PER2 in PER3-P415A/H417R transgenic mice, thus shortening the circadian cycle length, clinically presenting with ASPD (Zhang et al. Citation2016), which was also the case with our two affected subjects. The clinical picture of ASPD therefore probably presents due to reduced stability of the PER3 protein, resulting in reduced stability and lower concentration of the PER1/PER2 complex, which is a part of the negative core clock feedback loop. Decreased negative loop function of the circadian clock results in a faster start of a new cycle and shortening of the circadian period, which manifests itself as ASPD.
The PER3 haplotype variants were also associated with a seasonal mood trait (Zhang et al. Citation2016), but we were not able to confirm this in our proband. Experiments on hPER3-P415A/H417R-Tg mice confirmed the suspicion of a link between the variants and mood disorders, as lethargic and depressive behavior of transgenic mice was recorded, especially during shortened photoperiods (simulated wintertime with shorter days). The affected proband in our study anamnestically has a deterioration of the clinical picture in the summer, i.e. during a longer photoperiod. It should be noted that in our patient, seasonal mood disorder was assessed only by anamnesis. In addition, our subject did not have a clinical picture of mood disorders (assessed by the Beck’s Depression Inventory) which is consistent with the findings which linked the morning chronotype with a lower incidence of mood and mental health disorders (Jones et al. Citation2019).
There is much less known regarding the hereditary causes of the Delayed Sleep Phase Syndrome that has also a strong social cue and the delayed sleep cycles are frequent in the younger, adolescent population (Crowley et al. Citation2007; Micic et al. Citation2016; Paine et al. Citation2014). It is thus important to distinguish the subjects that do indeed have a genetic component of DSPS and not just a temporary phenotype due to the lifestyle or age group. We identified a novel variant in the sequenced region of the PER2 gene. PER2 has a major role in maintaining the circadian rhythms (Albrecht et al. Citation2007). It is not only a part of the core oscillator mechanism, but also a part of the input and output pathways of the clock.
We identified a novel PER2:c.1901-218 G>T intronic variant (rs1029124354) of unknown significance that is extremely rare with prevalence estimated at 0.000171 (Kopanos et al. Citation2019). Our data is the first to link this variant to a clinical presentation, DSPD. In silico predictions placed this variant as benign due to its position, however there is much to be said about the certainty of the insignificance of intronic variants (Ohno et al. Citation2018). The variant is located at site 972 of intron 16, so the effect on the protein product is unclear due to the distance from the excision site. The variant was found in a subject who presented with DSPD which we further defined using actimetry that also confirmed DSPD in the proband. The variant was also found in the parent of the proband, who presented with DSPD clinically but did not score as an extreme chronotype using MEQ, which showed mild eveningness. Interestingly, variants in PER2 have previously been linked also to ASPD (Toh et al. Citation2001). Further functional studies are necessary to validate the causality of the variant. In addition to genotyping family members with chronotype assessment, it would make sense to perform functional studies to elucidate the impact of the variant on PER2 protein function. Variants in PER2 were have so far been linked with ASPD, so it would be reasonable to assume they cause destabilization of PER2 proteins which results in reduced negative loop activity and thus pre-initiation of a new cycle. It would therefore be interesting to determine the mechanism of prolongation of the period at the molecular level.
We failed to find both CSNK1D variants, and neither the variant in the CRY1 gene (CRY1:c.1657 + 3A> G) that was previously linked to DSPD. Even though we were unable to link DSPD in our group of subjects to genetic etiology, this could be expected since ASPD has a much stronger link to genetic causes compared to DSPD (Chong et al. Citation2018; Jones et al. Citation2013) that is quite common in younger adults and is more commonly caused by environmental factors (Culnan et al. Citation2019). Our novel inherited intronic variant in the PER2 gene is thus of a great importance since it provides another potential link to the hereditary of DSPD.
In conclusion, by discovering two variants in the PER3 gene (c.1243C>G and c.1250A>G) and one in the PER2 gene (c.1901-218 G>T) we confirmed the hypothesis that the cause of some extreme chronotypes are hereditary variants of circadian genes. We suggest that genotyping of circadian genes be included in the treatment of patients with a suitable clinical picture. Given the extreme rarity of all detected variants, clinical follow-up of patients with variants and long-term evaluation of the variants’ involvement in potential additional health problems also seems reasonable. Such tracking, as well as the functional experiments of the discovered variant in PER2 gene, can significantly contribute to the knowledge of circadian rhythms, their disturbances as well as occurrence of diseases due to circadian disturbances.
To our knowledge we were the first to link the PER2: c.1901-218 G>T variant with a clinical presentation, discovering a novel cause for (susceptibility to) DSPD. We suggest additional sequencing of patients who present with DSPD and have positive family history for sleep phase disorders to acquire additional data and further elucidate the causality of the variant. Due to the relatively high frequency of the disorder this could present a clinically useful tool in explaining and managing the disorder, especially in cases of DSPD that are treatment refractory.
Author contributions
L.P., L.D.G., D.R, C.S. - Study design, L.P., C.S.- Lab work, L.P., L.D.G. - Sample collection, L.P., L.D.G., D.R. - Ethical permit registration, D.R. - Financing, D.R., L.D.G. - Supervision, L.P., L.D.G. - Patients collection, L.P., C.S., D.R. - Manuscript writing, D.R., L.D.G.- Manuscript revision.
Supplemental Material
Download PDF (1.9 MB)Acknowledgments
We thank Dani Mirnik M.D. for the help with Munich questionnaires.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Supplementary material
Supplemental data for this article can be accessed online at https://doi.org/10.1080/07420528.2024.2348016
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References
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