Nature Communications (Jul 2021)
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,
- VA Million Veteran Program,
- 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,
- Thomas W. Winkler
Affiliations
- Kira J. Stanzick
- Department of Genetic Epidemiology, University of Regensburg
- Yong Li
- Institute of Genetic Epidemiology, Department of Biometry, Epidemiology and Medical Bioinformatics, Faculty of Medicine and Medical Center–University of Freiburg
- Pascal Schlosser
- Institute of Genetic Epidemiology, Department of Biometry, Epidemiology and Medical Bioinformatics, Faculty of Medicine and Medical Center–University of Freiburg
- Mathias Gorski
- Department of Genetic Epidemiology, University of Regensburg
- Matthias Wuttke
- Institute of Genetic Epidemiology, Department of Biometry, Epidemiology and Medical Bioinformatics, Faculty of Medicine and Medical Center–University of Freiburg
- Laurent F. Thomas
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health, NTNU, Norwegian University of Science and Technology
- Humaira Rasheed
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health, NTNU, Norwegian University of Science and Technology
- Bryce X. Rowan
- Department of Biostatistics, Vanderbilt University Medical Center
- Sarah E. Graham
- Department of Internal Medicine, Division of Cardiology, University of Michigan
- Brett R. Vanderweff
- Department of Biostatistics, University of Michigan School of Public Health
- Snehal B. Patil
- Department of Biostatistics, University of Michigan School of Public Health
- VA Million Veteran Program
- Cassiane Robinson-Cohen
- Department of Veteran’s Affairs, Tennessee Valley Healthcare System (626)/Vanderbilt University
- John M. Gaziano
- Massachusetts Area Veterans Epidemiology Research and Information Center (MAVERIC), VA Cooperative Studies Program, VA Boston Healthcare System
- Christopher J. O’Donnell
- VA Cooperative Studies Program, VA Boston Healthcare System
- Cristen J. Willer
- Department of Internal Medicine, Division of Cardiology, University of Michigan
- Stein Hallan
- Department of Clinical and Molecular Medicine, NTNU, Norwegian University of Science and Technology
- Bjørn Olav Åsvold
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health, NTNU, Norwegian University of Science and Technology
- Andre Gessner
- Institute of Clinical Microbiology and Hygiene, University Hospital Regensburg
- Adriana M. Hung
- Department of Veteran’s Affairs, Tennessee Valley Healthcare System (626)/Vanderbilt University
- Cristian Pattaro
- Eurac Research, Institute for Biomedicine (affiliated with the University of Lübeck)
- Anna Köttgen
- Institute of Genetic Epidemiology, Department of Biometry, Epidemiology and Medical Bioinformatics, Faculty of Medicine and Medical Center–University of Freiburg
- Klaus J. Stark
- Department of Genetic Epidemiology, University of Regensburg
- Iris M. Heid
- Department of Genetic Epidemiology, University of Regensburg
- Thomas W. Winkler
- Department of Genetic Epidemiology, University of Regensburg
- DOI
- https://doi.org/10.1038/s41467-021-24491-0
- Journal volume & issue
-
Vol. 12,
no. 1
pp. 1 – 17
Abstract
Identifying causal variants and genes in genome-wide association studies remains a challenge, an issue that is ameliorated with larger sample sizes. Here the authors meta-analyze kidney function genome-wide association studies to identify new loci and fine-map loci to home in on variants and genes involved in kidney function.
