Sex-specific and pleiotropic effects underlying kidney function identified from GWAS meta-analysis

Abstract

Chronic Kidney Disease (CKD) is a growing health burden currently affecting 10-15% of adults worldwide. Estimated glomerular filtration rate (eGFR) as a marker of kidney function is commonly used to diagnose CKD. Previous genome-wide association study (GWAS) metaanalyses of CKD and eGFR or related phenotypes have identified a number of variants associated with kidney function, but these only explain a fraction of the variability in kidney phenotypes attributed to genetic components. To extend these studies, we analyzed data from the Nord-Trøndelag Health Study (HUNT), which is more densely imputed than previous studies, and performed a GWAS meta-analysis of eGFR with publicly available summary statistics, more than doubling the sample size of previous meta-analyses. We identified 147 loci (53 novel loci) associated with eGFR, including genes involved in transcriptional regulation, kidney development, cellular signaling, metabolism, and solute transport. Moreover, genes at these loci show enriched expression in urogenital tissues and highlight gene sets known to play a role in kidney function. In addition, sex-stratified analysis identified three regions (prioritized genes: PPM1J, MCL1, and SLC47A1) with more significant effects in women than men. Using genetic risk scores constructed from these eGFR meta-analysis results, we show that associated variants are generally predictive of CKD but improve detection only modestly compared with other known clinical risk factors. Collectively, these results yield additional insight into the genetic factors underlying kidney function and progression to CKD. Graham et al.

The role of gene expression on human sexual dimorphism: too early to call

“…Notwithstanding the prominent differences in traits observed between men and women, there is little known about the role of sex-specific genetic effects. Several sex-stratified GWASs identified sex-specific genetic variants on autosomal chromosomes, which highlights the fact that not all differences are located on the sex chromosomes [3][4][5][6][7][8][9][10]. Since many genetic variants exert their effect on complex traits through gene expression [17,18], sex differences in eQTL effects might underlie such sex-specific GWAS associations.…”

“…Despite the widespread nature of these sexual differences and their noteworthy implications for medical research and treatments, little is known about their underlying biology in complex traits. While the sex chromosomes play key roles in sexual dimorphism, GWAS have identified dozens of autosomal genetic variants showing sex-specific effects [3][4][5][6][7][8][9][10], suggesting that part of the phenotypic differences might be due to accumulation of genetic variants present in both sexes at the same frequency [11], but acting in a different manner in males and females.…”

Genetics of 38 blood and urine biomarkers in the UK Biobank

“…As such, understanding the genetic predisposition to particular phenotype measurements, and the factors that confound them, has implications for disease treatment. While the genetics of some biomarkers have been extensively studied, most notably lipids 1 , 2,3 , glycaemic traits [4][5][6] , and measurements of kidney function [7][8][9] , most biomarkers have only had limited measured genetic contribution.…”

Sexual differences in genetic architecture in UK Biobank

“…This, along with sex-biases observed in the human transcriptome [3][4][5][6][7][8][9][10] , the presence of a distinct hormone milieu in each sex, and differential environmental pressures arising from gender societal roles 1,11 , has led to an increased study of the potential importance of GxS interactions to understand the underlying biology of complex traits, including the estimation of disease risk. Previous studies have investigated differences in heritability between the sexes (h 2 ) [12][13][14] , departure of genetic correlations from 1 (rg) 12,[14][15][16][17][18] , and performed sex-stratified genome-wide association studies (GWAS) to directly assess differences in the effects of genetic variants between the sexes 6,[19][20][21][22][23][24][25][26] . These studies have however been limited with regards to the number of traits studied or statistical power.…”