medRxivGenetic & Genomic MedicinePreprint
Rare Coding Variants Reveal Distinct Genetic Architectures Across Multidimensional Sleep Phenotypes
Yingzhe ZhangiD, Wenhan LuiD, Lovemore KunorozvaiD, Samuel E. JonesiD, Matthew MaheriD, Jesse Tyler Valliere, Andrew R. WoodiD, Michael N. WeedoniD, Justin D. TubbsiD, Konrad J. KarczewskiiD, Tian GeiD, Henning W. TiemeieriD, Jacqueline M. LaneiD, Richa SaxenaiD, Hanna Maria OllilaiD, Chia‐Yen CheniD
Abstract
Sleep and circadian traits have been widely studied using common variants, but the contribution of rare coding variation remains unclear. We analyzed rare coding variants in 397,065 whole-exome sequenced UK Biobank participants across 36 sleep phenotypes from self-report, diagnoses, sleep medication use and accelerometry, and meta-analyzed results with 171,536 whole-genome sequenced All of Us participants of diverse ancestries, with replication in the Mass General Brigham Biobank (N = 31,275). We identified 260 genes associated with sleep phenotypes, including novel associations with sleep medication use in 29 genes and 24 out of 29 have not previously been reported with any sleep phenotypes. We observed modest but significant rare variant heritability and strong genetic correlations between sleep medication use, insomnia and fatigue. Temporal gene expression trajectory analyses indicate that genes associated with self-reported sleep traits show constant high prenatal expression, whereas genes linked to sleep medication phenotypes exhibit peak expression in the late prenatal period. These findings highlight distinct biological mechanisms captured by different measurement sources of sleep phenotypes and reveal rare-variant-informed targets for therapeutic discovery.
- organism: human
- assay: whole-exome sequencing
- assay: whole-genome sequencing
- research focus: GWAS / association mapping
- approach: statistical model
- Citations
- 0
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