Person:

Ho, Jennifer

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.

Objective: Metabolic syndrome (MetS) can lead to myocardial fibrosis, diastolic dysfunction and eventual heart failure. We evaluated alterations in myocardial microstructure in people with MetS using a novel algorithm to characterize ultrasonic signal intensity variation. Methods: Among 254 participants without existing cardiovascular disease (mean age 42 ± 11 years, 75% women), there were 162 with MetS, 47 with obesity without MetS, and 45 non-obese controls. Standard echocardiography was performed, and a novel validated computational algorithm was used to investigate myocardial microstructure based on sonographic signal intensity and distribution. We examined the signal intensity coefficient (SIC, left ventricular microstructure). Results: The SIC was significantly higher in people with MetS compared with people with (P<0.001) and without obesity (P=0.04), even after adjustment for age, sex, body mass index, hypertension, diabetes mellitus and triglyceride to HDL cholesterol (TG/HDL) ratio (P<0.05 for all). Clinical correlates of SIC included TG concentrations (r=0.21, P=0.0007) and the TG/HDL ratio (r=0.2, P=0.001). Conclusions: Our findings suggest that preclinical MetS and dyslipidemia in particular, are associated with altered myocardial signal intensity variation. Future studies are needed to determine whether the SIC may help detect subclinical disease in people with metabolic disease, with the ultimate goal of targeting preventive efforts.