Abstract 15265: Exome-wide Association Study of the Human Metabolome in a Community-based Cohort
Introduction: Because metabolites are hypothesized to play key roles as markers and effectors of cardio-metabolic diseases, recent studies have sought to annotate the genetic determinants of circulating metabolite levels. We hypothesize that the study of low frequency and rare variants of potential functional significance will refine our understanding of the genetic determinants of human metabolism.
Methods: We analyzed the association between 217 plasma metabolites and exome variants captured on the Illumina HumanExome Beadchip in 2,076 Framingham Heart Study (FHS) participants. Of the >240,000 variants on the exome array, we restricted our analysis to the subset of 92,633 variants that were polymorphic and nonsynonymous, nonsense, or located in a splice site. We performed association analyses that relate each single variant to each metabolite, as well as gene-based burden tests that evaluate the aggregate effects of all variants within a gene. Statistical analyses accounted for number of SNPs or genes (for burden tests).
Results: We identified a total of 15 gene-metabolite associations, nine from single variant analysis (gene: metabolite): CTH (Cystathionine); BPIFA2 (Betaine); OR1F1 (Creatinine); TCF19 (Glycerol); GMPS (Xanthosine); SIGLEC6 (Creatine); ANKUB1 (Carnosine); KIAA1751 (Serotonin); MAP1A (TAG 58:6). (Bonferroni-adjusted significance threshold of P < 5.4 x 10-7 for all). All but the ANKUB1findings are attributable to rare variants with MAF 0.01 or less. We identified six additional associations from burden tests, including three at established human disease loci: HAL (histidine); PAH (phenylalananine); UPB1 (ureidopropionate); TG (indole propionate); CDH5 (SM 22:1); PHLDB1 (LPE 18:0) (Bonferroni-adjusted significance threshold of P < 3.9 x10-6 for all).
Conclusion: Our findings highlight genes with a direct biochemical relationship with the given metabolite as well as unanticipated genetic effectors of select metabolites. We show how an examination of variants across the spectrum of allele frequency is able to identify independent association signals at select loci as well as generate a more integrated view of genetic determinants of metabolites.
Author Disclosures: E. Rhee: None. Q. Yang: None. X. Liu: None. J. Ho: None. S. Cheng: None. C. Clish: None. D. Levy: None. V. Ramachandran: None. T. Wang: Research Grant; Modest; Diasorin. Consultant/Advisory Board; Modest; Critical Diagnostics, Pfizer. Other; Modest; The MGH has applied for a patent related to the use of microRNA antagonists to increase ANP production to treat hypertension and heart failure, and the author may be entitled to royalties, The MGH has applied patents related to the use of metabolomic biomarkers for cardiometabolic disease.. C. O’Donnell: None. R. Gerszten: None.
This research has received full or partial funding support from the American Heart Association.
- © 2014 by American Heart Association, Inc.