Most genetic variants associated with complex traits are hypothesized to regulate gene expression. To understand the genetics underlying gene expression variability, we characterized 14,324 RNA-sequencing samples from the Trans-Omics for Precision Medicine program and performed expression and splicing quantitative trait locus (e/sQTL) analyses in six tissues and cell types, including whole blood (n = 6454) and lung (n = 1291). We detected tens of thousands of secondary cis-e/sQTLs, showing that secondary cis-e/sQTL discovery remains unsaturated. We fine-mapped UK Biobank-derived genome-wide association study (GWAS) signals from 164 traits and identified e/sQTL colocalizations for 10,611 GWAS signals, including 7096 that colocalize with secondary e/sQTLs. Our results suggest that even larger e/sQTL analyses will uncover additional secondary e/sQTLs, further benefiting GWAS interpretation.
Peter Orchard, T. Blackwell, L. Kachuri et al.· Science· 0 citations
STUDY OBJECTIVES
Since genome-wide association studies (GWAS) of sleep phenotypes have been conducted in differing populations and definitions of sleep phenotypes vary across studies, we investigated associations between several polygenic risk scores (PRSs) and potential sleep definitions among multiethnic cohorts.
METHODS
Using data from four cohorts (HCHS/SOL, ARIC, MESA, BHS, N = 16 895), we considered multiple definitions of short and long sleep, insomnia, and excessive daytime sleepiness (EDS). PRSs were developed based on summary statistics from GWAS in European ancestry individuals from the UK Biobank (UKB) and from GWAS conducted in a multiethnic population from the Million Veteran Program (MVP). Study-specific analyses estimated associations between sleep PRSs and corresponding sleep measures per 1 standard deviation increase in the PRS. Models were adjusted for age, sex, ancestral principal components, and center and race as appropriate. Results were meta-analyzed across studies.
RESULTS
PRSs based on European ancestry UKB GWAS had statistically significant associations with multiple definitions of the corresponding sleep phenotypes. Associations that were most consistent across studies included: short sleep PRS with ≤6 hours (OR = 1.23,p = 1.80x10-7,phet = 0.97); long sleep PRS with ≥9 hours (OR = 1.09,p = 6.76x10-4,phet = 0.77); insomnia PRS with the Women's Health Initiative Insomnia Rating Scale (WHIIRS) ≥10 or a subset of three questions ≥6 in ARIC (OR = 1.17,p = 5.51x10-10,phet = 0.69); and EDS PRS with Epworth Sleepiness Scale (ESS) ≥11 (OR = 1.23,p = 1.83x10-13,phet = 0.83). PRSs based on multi-ancestry MVP GWAS had weaker associations compared to those based on European ancestry only.
CONCLUSIONS
By evaluating several types of sleep PRSs and sleep phenotypes, we were able to highlight which sleep PRS performed well across diverse populations and which sleep definitions better captured genetic underpinnings.
A. Wyss, Michael Brown, Xiang Li et al.· Sleep· 0 citations
This study supports methylation risk scores as novel biomarkers of stress-related CHD and uncovers epigenetic regulation in monocytes as a potential underlying mechanism of stress-related CHD, highlighting biological pathways linking stress and disease and may promote personalized interventions in high-risk populations.
Sofia Benavides, Hazel Milla, Helena Palma-Gudiel et al.· medRxiv· 0 citations
