Abstract 18668: Integration of Proteomic and Metabolomic Plasma Profiles in a Community-Based Cohort
Introduction: Circulating proteins and metabolites play key roles as markers and effectors of cardiometabolic diseases. We hypothesized that integrating these data sets may identify novel circulating protein-metabolite associations and provide new insight into molecular pathways that underlie cardiometabolic and vascular disease.
Methods: Aptamer-based proteomic profiling of 1,129 analytes in plasma samples from 923 Framingham Heart Study Offspring participants (mean age 56 +/- 12 years, 52% women) was performed using the Somascan platform. Targeted metabolomic profiling of 217 analytes was performed by liquid chromatography tandem mass spectrometry, as previously reported. Pearson correlations between log-transformed protein and metabolite concentrations were assessed using PROC CORR in SAS, adjusting for age, sex, and the homeostatic model assessment.
Results: We identified over 5,000 unadjusted protein-metabolite associations with high levels of significance (Bonferroni-corrected threshold P-value < 2x10-7). Our analysis identified protein-metabolite relationships known to define key biological pathways. For example, Apolipoprotein E (ApoE) was most highly associated with triacylglyerols (TAGs) of varying fatty acid chain length and degrees of saturation, the most significant of which was a TAG with 50 carbons and 4 double bonds (P=5x10-48). Similarly, thyroid stimulating hormone was most strongly negatively associated with thyroxine (P-value 4x10-18). By contrast, we identified hundreds of novel correlations between plasma levels of metabolites and key cardiometabolic proteins such as Apo E (for example, with the branched chain amino acids valine, P=2x10-11; leucine, P=7x10-10; and isoleucine, P=1x10-9), PCSK9 (with 3-aminoisobutyric acid, P=7x10-11), and adiponectin (with 2-aminoadipic acid, P=1x10-26). These associations remained highly significant when adjusted for age, sex, and insulin resistance.
Conclusions: The integration of protein and metabolite profiling data sets from large community-based cohorts can be used to identify novel protein-metabolite associations. These associations may offer new tools to elucidate the molecular pathways that underlie cardiometabolic and vascular disease.
Author Disclosures: M.D. Benson: None. D. Shen: None. J. Morningstar: None. M.J. Keyes: None. D. Ngo: None. J. O’Sullivan: None. X. Shi: None. L. Farrell: None. S. Sinha: None. R.S. Vasan: None. T.J. Wang: None. R.E. Gerszten: None.
- © 2016 by American Heart Association, Inc.