Shared genetic architecture between sleep traits and cardiometabolic diseases

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Authors: Yuan Zhang, Shijie Jian, Haiyan Ouyang, Yogesh Purushotham, Qiao Yu, Beisha Tang, Daniel J. Gottlieb, Tamar Sofer, Minhan Yi
Cited by: 2
References: 104

Abstract

BACKGROUND: Sleep traits, including sleep apnoea (SA), insomnia, daytime sleepiness, and snoring, frequently co-occur with cardiometabolic diseases (CMDs), with shared genetic factors suspected to underlie these associations. However, the contribution of shared genetic determinants to these associations is not fully understood. METHODS: We conducted a genome-wide pleiotropic association study applying sequential genetic methods to identify shared genetic variants, genes, pathways and causal associations between the four sleep traits and seven CMDs, including LDSC, high-definition likelihood analysis, colocalisation, gene-based tests, enrichment analysis and Mendelian randomisation. Next, validation of those pleiotropic variants was performed in individuals from the All of Us and MVP studies. FINDINGS: Among 28 pairs of sleep traits and CMDs, 25 showed significant genetic correlations. Pleiotropic analysis identified 754 independent SNPs (691 unique) and 102 colocalized loci (85 unique). Among these, 47 SNPs (44 unique) were validated as significantly associated with both traits in the pairs, and notably, rs429358 (19q13.32, APOE) demonstrated pleiotropic effects across SA, insomnia and type 2 diabetes (T2D). Forty-eight annotated genes were validated by gene-based tests. Shared genes were enriched in phenotypes related to mortality and growth. Pathway analysis highlighted Cushing syndrome, hormone secretion, and cGMP-PKG, Ras and calcium signalling pathways. After adjusting for glycaemic traits and blood pressure, genetically predicted T2D increased risk of SA, sleepiness, and snoring. Conversely, SA was positively associated with heart failure and T2D independently. INTERPRETATION: This study of sleep traits and CMDs reveals shared genetic determinants that may partially explain their epidemiologic association and suggests potential treatment targets. FUNDING: Described in Acknowledgements.

Fields of Study & Subjects

Genetic Associations and Epidemiology Genetics and Physical Performance Sleep and Wakefulness Research

Publication details

Journal / source
EBioMedicine
Publisher
Elsevier BV
Volume
126
Pages
106220–106220
Publication date
14 March 2026
Language
EN