Sex-specific and pleiotropic effects underlying kidney function identified from GWAS meta-analysis.
Sarah E GrahamJonas Bille NielsenMatthew ZawistowskiWei ZhouLars G FritscheMaiken E GabrielsenAnne Heidi SkogholtIda SurakkaWhitney E HornsbyDamian FerminDaniel B LarachSachin KheterpalChad M BrummettSeunggeun LeeHyun Min KangGoncalo R AbecasisSolfrid RomundstadStein HallanMatthew Gordon SampsonKristian HveemCristen J WillerPublished in: Nature communications (2019)
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.
Keyphrases
- meta analyses
- chronic kidney disease
- systematic review
- small cell lung cancer
- epidermal growth factor receptor
- end stage renal disease
- tyrosine kinase
- genome wide
- healthcare
- risk factors
- public health
- mental health
- randomized controlled trial
- copy number
- type diabetes
- case control
- dna methylation
- electronic health record
- polycystic ovary syndrome
- emergency department
- quality improvement
- pregnant women
- pregnancy outcomes
- risk assessment
- peritoneal dialysis
- metabolic syndrome
- climate change
- single cell
- artificial intelligence
- deep learning
- breast cancer risk
- loop mediated isothermal amplification