Title |
An exome array study of the plasma metabolome
|
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Published in |
Nature Communications, July 2016
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DOI | 10.1038/ncomms12360 |
Pubmed ID | |
Authors |
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 |
Abstract |
The study of rare variants may enhance our understanding of the genetic determinants of the metabolome. Here, we analyze the association between 217 plasma metabolites and exome variants on the Illumina HumanExome Beadchip in 2,076 participants in the Framingham Heart Study, with replication in 1,528 participants of the Atherosclerosis Risk in Communities Study. We identify an association between GMPS and xanthosine using single variant analysis and associations between HAL and histidine, PAH and phenylalanine, and UPB1 and ureidopropionate using gene-based tests (P<5 × 10(-8) in meta-analysis), highlighting novel coding variants that may underlie inborn errors of metabolism. Further, we show how an examination of variants across the spectrum of allele frequency highlights independent association signals at select loci and generates a more integrated view of metabolite heritability. These studies build on prior metabolomics genome wide association studies to provide a more complete picture of the genetic architecture of the plasma metabolome. |
X Demographics
Geographical breakdown
Country | Count | As % |
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United States | 5 | 100% |
Demographic breakdown
Type | Count | As % |
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Scientists | 3 | 60% |
Members of the public | 2 | 40% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Spain | 1 | <1% |
Qatar | 1 | <1% |
Unknown | 101 | 98% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 29 | 28% |
Student > Ph. D. Student | 10 | 10% |
Professor > Associate Professor | 9 | 9% |
Professor | 8 | 8% |
Other | 8 | 8% |
Other | 23 | 22% |
Unknown | 16 | 16% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 23 | 22% |
Agricultural and Biological Sciences | 20 | 19% |
Medicine and Dentistry | 12 | 12% |
Neuroscience | 4 | 4% |
Chemistry | 4 | 4% |
Other | 17 | 17% |
Unknown | 23 | 22% |