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

Yeela Talmor-Barkan, Noam Bar, Aviv A. Shaul, Nir Shahaf, Anastasia Godneva, Yuval Bussi, Maya Lotan-Pompan, Adina Weinberger, Alon Shechter, Chava Chezar-Azerrad, Ziad Arow, Yoav Hammer, Kanta Chechi, Sofia K. Forslund, Sebastien Fromentin, Marc Emmanuel Dumas, S. Dusko Ehrlich, Oluf Pedersen, Ran Kornowski, Eran Segal*

*Corresponding author af dette arbejde

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

86 Citationer (Scopus)

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.

OriginalsprogEngelsk
TidsskriftNature Medicine
Vol/bind28
Udgave nummer2
Sider (fra-til)295-302
Antal sider8
ISSN1078-8956
DOI
StatusUdgivet - 2022

Bibliografisk note

Funding Information:
We thank past and present members of the Segal group and the Cardiology Department at Rabin Medical Center for useful discussions. Y.T.-B. received a research grant from the Tel Aviv University Faculty Funds, and from the Gassner Fund for Medical Research. N.B. received a PhD scholarship for Data Science from the Israeli Council for Higher Education (CHE) via the Weizmann Data Science Research Center and is supported by a research grant from the Estate of Tully and Michele Plesser. E.S. is supported by the Crown Human Genome Center, by D. L. Schwarz, J. N. Halpern and L. Steinberg, and by grants funded by the European Research Council and the Israel Science Foundation. M.-E.D. is supported by the NIHR Imperial Biomedical Research Centre, and by grants from the French National Research Agency (ANR-10-LABX-46 [European Genomics Institute for Diabetes]), from the National Center for Precision Diabetic Medici?e ? PreciDIAB, which is jointly supported by the French National Agency for Research (ANR-18-IBHU-0001), by the European Union (FEDER), by the Hauts-de-France Regional Council (Agreement 20001891/NP0025517), by the European Metropolis of Lille (MEL, Agreement 2019_ESR_11) and Isite ULNE (R-002-20-TALENT-DUMAS), also jointly funded by ANR (ANR-16-IDEX-0004-ULNE), the Hauts-de-France Regional Council (20002845) and by the European Metropolis of Lille (MEL). K.C. is supported by Medical Research Council (MRC) Skills Development Fellowship (grant number MR/S020039/1) and Wellcome Trust funded Institutional Strategic Support Fellowship (grant number 204834/Z/16/Z).

Publisher Copyright:
© 2022, The Author(s), under exclusive licence to Springer Nature America, Inc.

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