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Metabolomic and microbiome profiling reveals personalized risk factors for coronary artery disease

Item Type:Article
Title:Metabolomic and microbiome profiling reveals personalized risk factors for coronary artery disease
Creators Name:Talmor-Barkan, Y. and Bar, N. and Shaul, A.A. and Shahaf, N. and Godneva, A. and Bussi, Y. and Lotan-Pompan, M. and Weinberger, A. and Shechter, A. and Chezar-Azerrad, C. and Arow, Z. and Hammer, Y. and Chechi, K. and Forslund, S.K. and Fromentin, S. and Dumas, M.E. and Ehrlich, S.D. and Pedersen, O. and Kornowski, R. and Segal, E.
Abstract:Complex diseases, such as coronary artery disease (CAD), are often multifactorial, caused by multiple underlying pathological mechanisms. Here, to study the multifactorial nature of CAD, we performed comprehensive clinical and multi-omic profiling, including serum metabolomics and gut microbiome data, for 199 patients with acute coronary syndrome (ACS) recruited from two major Israeli hospitals, and validated these results in a geographically distinct cohort. ACS patients had distinct serum metabolome and gut microbial signatures as compared with control individuals, and were depleted in a previously unknown bacterial species of the Clostridiaceae family. This bacterial species was associated with levels of multiple circulating metabolites in control individuals, several of which have previously been linked to an increased risk of CAD. Metabolic deviations in ACS patients were found to be person specific with respect to their potential genetic or environmental origin, and to correlate with clinical parameters and cardiovascular outcomes. Moreover, metabolic aberrations in ACS patients linked to microbiome and diet were also observed to a lesser extent in control individuals with metabolic impairment, suggesting the involvement of these aberrations in earlier dysmetabolic phases preceding clinically overt CAD. Finally, a metabolomics-based model of body mass index (BMI) trained on the non-ACS cohort predicted higher-than-actual BMI when applied to ACS patients, and the excess BMI predictions independently correlated with both diabetes mellitus (DM) and CAD severity, as defined by the number of vessels involved. These results highlight the utility of the serum metabolome in understanding the basis of risk-factor heterogeneity in CAD.
Keywords:Acute Coronary Syndrome, Bacteria, Coronary Artery Disease, Metabolomics, Metabolome, Microbiota, Risk Factors
Source:Nature Medicine
Publisher:Nature Publishing Group
Page Range:295-302
Date:February 2022
Official Publication:https://doi.org/10.1038/s41591-022-01686-6
PubMed:View item in PubMed

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