Abstract

Depressive disorders have increased in global prevalence, making improved management of these disorders a public health priority. Prior research has linked circadian clock genes to depression, either through direct interactions with mood-related pathways in the brain or by modulating the phase of circadian rhythms. Using machine learning and statistical techniques, we explored associations between 157,347 SNP variants from 51 circadian-related genes and depression scores from the Patient Health Questionnaire 9 (PHQ-9) in 99,939 UK Biobank participants. Our results highlight multiple pathways linking the circadian system to mood, including metabolic, monoamine, immune, and stress-related pathways. Notably, genes regulating glucose metabolism and inflammation (GSK3B, LEP, RORA, and NOCT) were prominent factors in females, in addition to DELEC1 and USP46, two genes of unknown function. In contrast, FBXL3 and DRD4 emerged as significant risk factors for male depression. We also found epistatic interactions involving RORA, NFIL3, and ZBTB20 as either risk or protective factors for depression, underscoring the importance of transcription factors (ZBTB20, NFIL3) and hormone receptors (RORA) in depression etiology. Understanding the complex, sex-specific links between circadian genes and mood disorders will facilitate the development of therapeutic interventions and enhance the efficacy of multi-target treatments for depression.

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