Discovery and prioritization of variants and genes for kidney function in >1.2 million individuals

Kira J. Stanzick, Yong Li, Pascal Schlosser, Mathias Gorski, Matthias Wuttke, Laurent F. Thomas, Humaira Rasheed, Bryce X. Rowan, Sarah E. Graham, Brett R. Vanderweff, Snehal B. Patil, Cassiane Robinson-Cohen, John M. Gaziano, Christopher J. O’Donnell, Cristen J. Willer, Stein Hallan, Bjørn Olav Åsvold, Andre Gessner, Adriana M. Hung, Cristian Pattaro, Anna Köttgen, Klaus J. Stark, Iris M. Heid and Thomas W. Winkler ()
Additional contact information
Kira J. Stanzick: University of Regensburg
Yong Li: Faculty of Medicine and Medical Center–University of Freiburg
Pascal Schlosser: Faculty of Medicine and Medical Center–University of Freiburg
Mathias Gorski: University of Regensburg
Matthias Wuttke: Faculty of Medicine and Medical Center–University of Freiburg
Laurent F. Thomas: Norwegian University of Science and Technology
Humaira Rasheed: Norwegian University of Science and Technology
Bryce X. Rowan: Vanderbilt University Medical Center
Sarah E. Graham: University of Michigan
Brett R. Vanderweff: University of Michigan School of Public Health
Snehal B. Patil: University of Michigan School of Public Health
Cassiane Robinson-Cohen: Tennessee Valley Healthcare System (626)/Vanderbilt University
John M. Gaziano: VA Boston Healthcare System
Christopher J. O’Donnell: VA Boston Healthcare System
Cristen J. Willer: University of Michigan
Stein Hallan: Norwegian University of Science and Technology
Bjørn Olav Åsvold: Norwegian University of Science and Technology
Andre Gessner: University Hospital Regensburg
Adriana M. Hung: Tennessee Valley Healthcare System (626)/Vanderbilt University
Cristian Pattaro: Institute for Biomedicine (affiliated with the University of Lübeck)
Anna Köttgen: Faculty of Medicine and Medical Center–University of Freiburg
Klaus J. Stark: University of Regensburg
Iris M. Heid: University of Regensburg
Thomas W. Winkler: University of Regensburg

Nature Communications, 2021, vol. 12, issue 1, 1-17

Abstract: Abstract Genes underneath signals from genome-wide association studies (GWAS) for kidney function are promising targets for functional studies, but prioritizing variants and genes is challenging. By GWAS meta-analysis for creatinine-based estimated glomerular filtration rate (eGFR) from the Chronic Kidney Disease Genetics Consortium and UK Biobank (n = 1,201,909), we expand the number of eGFRcrea loci (424 loci, 201 novel; 9.8% eGFRcrea variance explained by 634 independent signal variants). Our increased sample size in fine-mapping (n = 1,004,040, European) more than doubles the number of signals with resolved fine-mapping (99% credible sets down to 1 variant for 44 signals, ≤5 variants for 138 signals). Cystatin-based eGFR and/or blood urea nitrogen association support 348 loci (n = 460,826 and 852,678, respectively). Our customizable tool for Gene PrioritiSation reveals 23 compelling genes including mechanistic insights and enables navigation through genes and variants likely relevant for kidney function in human to help select targets for experimental follow-up.

Date: 2021
References: Add references at CitEc
Citations: View citations in EconPapers (10)

Downloads: (external link)
https://www.nature.com/articles/s41467-021-24491-0 Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-24491-0

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/s41467-021-24491-0

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().