Nature Communications (Jul 2016)
An exome array study of the plasma metabolome
- Eugene P. Rhee,
- Qiong Yang,
- Bing Yu,
- Xuan Liu,
- Susan Cheng,
- Amy Deik,
- Kerry A. Pierce,
- Kevin Bullock,
- Jennifer E. Ho,
- Daniel Levy,
- Jose C. Florez,
- Sek Kathiresan,
- Martin G. Larson,
- Ramachandran S. Vasan,
- Clary B. Clish,
- Thomas J. Wang,
- Eric Boerwinkle,
- Christopher J. O’Donnell,
- Robert E. Gerszten
Affiliations
- Eugene P. Rhee
- Nephrology Division, Massachusetts General Hospital
- Qiong Yang
- Department of Biostatistics, Boston University School of Public Health
- Bing Yu
- Human Genetics Center, University of Texas Health Science Center at Houston
- Xuan Liu
- Department of Biostatistics, Boston University School of Public Health
- Susan Cheng
- National Heart, Lung and Blood Institute’s Framingham Heart Study
- Amy Deik
- Metabolite Profiling, Broad Institute of MIT and Harvard
- Kerry A. Pierce
- Metabolite Profiling, Broad Institute of MIT and Harvard
- Kevin Bullock
- Metabolite Profiling, Broad Institute of MIT and Harvard
- Jennifer E. Ho
- Cardiology Division, Massachusetts General Hospital
- Daniel Levy
- National Heart, Lung and Blood Institute’s Framingham Heart Study
- Jose C. Florez
- Diabetes Research Center, Massachusetts General Hospital
- Sek Kathiresan
- Cardiology Division, Massachusetts General Hospital
- Martin G. Larson
- Department of Biostatistics, Boston University School of Public Health
- Ramachandran S. Vasan
- National Heart, Lung and Blood Institute’s Framingham Heart Study
- Clary B. Clish
- Metabolite Profiling, Broad Institute of MIT and Harvard
- Thomas J. Wang
- Division of Cardiovascular Medicine, Vanderbilt University Medical Center
- Eric Boerwinkle
- Human Genetics Center, University of Texas Health Science Center at Houston
- Christopher J. O’Donnell
- National Heart, Lung and Blood Institute’s Framingham Heart Study
- Robert E. Gerszten
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center
- DOI
- https://doi.org/10.1038/ncomms12360
- Journal volume & issue
-
Vol. 7,
no. 1
pp. 1 – 7
Abstract
Several GWAS have identified many common variants associated with blood metabolites. Here, the authors use an exome array to identify low frequency, potentially functional variants that impact human metabolism.
