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.
Highlights
The study of rare variants may enhance our understanding of the genetic determinants of the metabolome
This study identified 31 common variants associated with 64 plasma metabolites, and leveraging the family-based structure and rich cardiometabolic phenotyping in Framingham Heart Study (FHS), outlined the relative contribution of heritable, environmental and clinical factors to plasma metabolite levels
This finding complements the association between GMPR, which encodes the enzyme responsible for the deamination of guanosine monophosphate (GMP), and xanthosine identified in our prior GWAS5
Summary
The study of rare variants may enhance our understanding of the genetic determinants of the metabolome. 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. We isolate independent signals at genes highlighted in our prior common variant study and shed light on how variants contribute to metabolite heritability as a function of allele frequency
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