Chronotype and sleep quality as a subphenotype in association studies of clock genes in mood disorders
Bibliographic record
Abstract
Genetic background and clinical picture of mood disorders (MD) are complex and may depend on many genes and their potential interactions as well as environmental factors. Therefore, clinical variations, or endophenotypes, were suggested for association studies. The aim of the study was to investigate association between the chronotype (CH) and quality of sleep characteristics with polymorphisms CLOCK, ARNTL, TIMELESS and PER3 genes in MD. We included a total sample of 111 inpatients and 126 healthy controls. To assess CH we applied Morningness-Eveningness Questionnaire (MEQ). Additionally, we defined the quality and patterns of sleep using The Pittsburgh Sleep Quality Index (PSQI) and Epworth Sleepiness Scale (ESS). We applied Kruskal-Wallis test to determine associations. The main positive findings refer to associations between selected polymorphisms and: 1) chronotype with the ARNTL gene (rs11824092 and rs1481892) and the CLOCK (rs1268271) 2) sleep duration with the CLOCK gene (rs3805148) and the TIM gene (rs2291739) 3) daytime dysfunction with the PER3 gene (rs228727, rs228642, rs10864315) 4) subjective sleep quality with the ARNTL gene (rs11824092, rs1982350) 5) sleep disturbances with the ARNTL gene (rs11600996) We also found the significant epistatic interactions between polymorphism of the PER3 gene (rs2640909) & the CLOCK gene (rs11932595) and following sleep quality variables: sleep duration, habitual sleep efficiency and subjective sleep quality. The present study suggests a putative role of the analyzed clock genes polymorphisms in chronotype in the control group and in sleep quality disturbances in the course of MD. The results indicate that PSQI variables can be used to refine phenotype in association studies of clock genes in MD.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".