Limited evidence for blood eQTLs in human sexual dimorphism.

Details

Ressource 1Download: 35953856_BIB_4AC82BE10423.pdf (1853.92 [Ko])
State: Public
Version: Final published version
License: CC BY 4.0
Serval ID
serval:BIB_4AC82BE10423
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Limited evidence for blood eQTLs in human sexual dimorphism.
Journal
Genome medicine
Author(s)
Porcu E., Claringbould A., Weihs A., Lepik K., Richardson T.G., Völker U., Santoni F.A., Teumer A., Franke L., Reymond A., Kutalik Z.
Working group(s)
BIOS Consortium
ISSN
1756-994X (Electronic)
ISSN-L
1756-994X
Publication state
Published
Issued date
11/08/2022
Peer-reviewed
Oui
Volume
14
Number
1
Pages
89
Language
english
Notes
Publication types: Journal Article
Publication Status: epublish
Abstract
The genetic underpinning of sexual dimorphism is very poorly understood. The prevalence of many diseases differs between men and women, which could be in part caused by sex-specific genetic effects. Nevertheless, only a few published genome-wide association studies (GWAS) were performed separately in each sex. The reported enrichment of expression quantitative trait loci (eQTLs) among GWAS-associated SNPs suggests a potential role of sex-specific eQTLs in the sex-specific genetic mechanism underlying complex traits.
To explore this scenario, we combined sex-specific whole blood RNA-seq eQTL data from 3447 European individuals included in BIOS Consortium and GWAS data from UK Biobank. Next, to test the presence of sex-biased causal effect of gene expression on complex traits, we performed sex-specific transcriptome-wide Mendelian randomization (TWMR) analyses on the two most sexually dimorphic traits, waist-to-hip ratio (WHR) and testosterone levels. Finally, we performed power analysis to calculate the GWAS sample size needed to observe sex-specific trait associations driven by sex-biased eQTLs.
Among 9 million SNP-gene pairs showing sex-combined associations, we found 18 genes with significant sex-biased cis-eQTLs (FDR 5%). Our phenome-wide association study of the 18 top sex-biased eQTLs on >700 traits unraveled that these eQTLs do not systematically translate into detectable sex-biased trait-associations. In addition, we observed that sex-specific causal effects of gene expression on complex traits are not driven by sex-specific eQTLs. Power analyses using real eQTL- and causal-effect sizes showed that millions of samples would be necessary to observe sex-biased trait associations that are fully driven by sex-biased cis-eQTLs. Compensatory effects may further hamper their detection.
Our results suggest that sex-specific eQTLs in whole blood do not translate to detectable sex-specific trait associations of complex diseases, and vice versa that the observed sex-specific trait associations cannot be explained by sex-specific eQTLs.
Keywords
Female, Genome-Wide Association Study/methods, Humans, Male, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Sex Characteristics, Transcriptome
Pubmed
Open Access
Yes
Create date
22/08/2022 12:58
Last modification date
23/11/2022 7:10
Usage data