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. We analyze eGFR data from the Nord-Trøndelag Health Study and Michigan Genomics Initiative and perform a GWAS meta-analysis with public summary statistics, more than doubling the sample size of previous meta-analyses. We identify 147 loci (53 novel) associated with eGFR, including genes involved in transcriptional regulation, kidney development, cellular signaling, metabolism, and solute transport. Additionally, sex-stratified analysis identifies one locus 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 with only modest improvements in detection compared with other known clinical risk factors. Collectively, these results yield additional insight into the genetic factors underlying kidney function and progression to CKD.

Fig. 1

Top gene sets prioritized from eGFR meta-analysis. DEPICT analysis of eGFR meta-analysis results identifies significant gene sets associated with kidney function and metabolic processes. The most significant gene sets are shown (p-value < 3.46 × 10⁻⁶, 0.05/14462 gene sets, out of 482 with FDR < 0.05), after collapsing highly overlapping gene sets. Overlap between gene sets is depicted by the width of connecting lines. *Denotes collapsed gene sets

Fig. 2

Pleiotropic associations of eGFR index variants. Index variants, given as chromosome:position on the left axis and prioritized gene on the right, from eGFR meta-analysis showing significant associations with at least one additional phenotype (16 variants with p-value < 5 × 10⁻⁸) in UK Biobank (N_max = 408,961). 127 variants were tested for association with 1400 phenotypes

Fig. 3

LocusZoom plots of region showing differential association between sexes. eGFR meta-analysis results in HUNT stratified by sex were filtered to identify regions significant in one sex (P < 5 × 10⁻⁸) but not significant (P > 0.05) in the other. Within each panel, we show regional results for eGFR association for variants near rs2440165, which is an eQTL for SLC47A1, in women (a) and men (b)