Sex-specific and pleiotropic effects underlying kidney function identified from GWAS meta-analysis
Sarah E Graham,
Jonas B Nielsen,
Lars G. Fritsche,
Maiken E Gabrielsen,
Anne Heidi Skogholt,
Chad M. Brummett,
Hyun Min Kang,
Gonçalo R. Abecasis,
Matthew G. Sampson,
Cristen J. Willer
Posted 19 Sep 2018
bioRxiv DOI: 10.1101/421552 (published DOI: 10.1038/s41467-019-09861-z)
Posted 19 Sep 2018
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) meta-analyses 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-Trondelag 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.
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