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

Sarah E. Graham, Jonas B. Nielsen, Matthew Zawistowski, Wei Zhou, Lars G. Fritsche, Maiken E. Gabrielsen, Anne Heidi Skogholt, Ida Surakka, Whitney E. Hornsby, Damian Fermin, Daniel B. Larach, Sachin Kheterpal, Chad M. Brummett, Seunggeun Lee, Hyun Min Kang, Goncalo R. Abecasis, Solfrid Romundstad, Stein Hallan, Matthew G. Sampson, Kristian Hveem () and Cristen J. Willer ()
Additional contact information
Sarah E. Graham: University of Michigan
Jonas B. Nielsen: University of Michigan
Matthew Zawistowski: University of Michigan
Wei Zhou: University of Michigan
Lars G. Fritsche: University of Michigan
Maiken E. Gabrielsen: Norwegian University of Science and Technology
Anne Heidi Skogholt: Norwegian University of Science and Technology
Ida Surakka: University of Michigan
Whitney E. Hornsby: University of Michigan
Damian Fermin: University of Michigan
Daniel B. Larach: University of Michigan
Sachin Kheterpal: University of Michigan
Chad M. Brummett: University of Michigan
Seunggeun Lee: University of Michigan
Hyun Min Kang: University of Michigan
Goncalo R. Abecasis: University of Michigan
Solfrid Romundstad: Norwegian University of Science and Technology
Stein Hallan: Norwegian University of Science and Technology
Matthew G. Sampson: University of Michigan
Kristian Hveem: Norwegian University of Science and Technology
Cristen J. Willer: University of Michigan

Nature Communications, 2019, vol. 10, issue 1, 1-9

Abstract: 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.

Date: 2019
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DOI: 10.1038/s41467-019-09861-z

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