Nature Communications (Apr 2019)
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,
- Cristen J. Willer
Affiliations
- Sarah E. Graham
- Department of Internal Medicine: Cardiology, University of Michigan
- Jonas B. Nielsen
- Department of Internal Medicine: Cardiology, University of Michigan
- Matthew Zawistowski
- Department of Biostatistics: Center for Statistical Genetics, University of Michigan
- Wei Zhou
- Department of Computational Medicine and Bioinformatics, University of Michigan
- Lars G. Fritsche
- Department of Biostatistics: Center for Statistical Genetics, University of Michigan
- Maiken E. Gabrielsen
- K.G. Jebsen Center for Genetic Epidemiology, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology
- Anne Heidi Skogholt
- K.G. Jebsen Center for Genetic Epidemiology, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology
- Ida Surakka
- Department of Internal Medicine: Cardiology, University of Michigan
- Whitney E. Hornsby
- Department of Internal Medicine: Cardiology, University of Michigan
- Damian Fermin
- Department of Pediatrics: Pediatric Nephrology, University of Michigan
- Daniel B. Larach
- Department of Anesthesiology, University of Michigan
- Sachin Kheterpal
- Department of Anesthesiology, University of Michigan
- Chad M. Brummett
- Department of Anesthesiology, University of Michigan
- Seunggeun Lee
- Department of Biostatistics: Center for Statistical Genetics, University of Michigan
- Hyun Min Kang
- Department of Biostatistics: Center for Statistical Genetics, University of Michigan
- Goncalo R. Abecasis
- Department of Biostatistics: Center for Statistical Genetics, University of Michigan
- Solfrid Romundstad
- Department of Clinical and Molecular Medicine, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology
- Stein Hallan
- Department of Clinical and Molecular Medicine, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology
- Matthew G. Sampson
- Department of Pediatrics: Pediatric Nephrology, University of Michigan
- Kristian Hveem
- K.G. Jebsen Center for Genetic Epidemiology, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology
- Cristen J. Willer
- Department of Internal Medicine: Cardiology, University of Michigan
- DOI
- https://doi.org/10.1038/s41467-019-09861-z
- Journal volume & issue
-
Vol. 10,
no. 1
pp. 1 – 9
Abstract
Estimated glomerular filtration rate (eGFR) is a measure of kidney function and used to characterize chronic kidney disease. Here, Graham et al. identify 53 novel loci for eGFR in a GWAS meta-analysis, a subset of which are associated with other common diseases, such as diabetes and hypertension, based on PheWAS.
