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

Research output: Contribution to journal › Journal article › Research › peer-review

Standard

Metabolomic and microbiome profiling reveals personalized risk factors for coronary artery disease. / Talmor-Barkan, Yeela; Bar, Noam; Shaul, Aviv A.; Shahaf, Nir; Godneva, Anastasia; Bussi, Yuval; Lotan-Pompan, Maya; Weinberger, Adina; Shechter, Alon; Chezar-Azerrad, Chava; Arow, Ziad; Hammer, Yoav; Chechi, Kanta; Forslund, Sofia K.; Fromentin, Sebastien; Dumas, Marc Emmanuel; Ehrlich, S. Dusko; Pedersen, Oluf; Kornowski, Ran; Segal, Eran.

In: Nature Medicine, Vol. 28, No. 2, 2022, p. 295-302.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Talmor-Barkan, Y, Bar, N, Shaul, AA, Shahaf, N, Godneva, A, Bussi, Y, Lotan-Pompan, M, Weinberger, A, Shechter, A, Chezar-Azerrad, C, Arow, Z, Hammer, Y, Chechi, K, Forslund, SK, Fromentin, S, Dumas, ME, Ehrlich, SD, Pedersen, O, Kornowski, R & Segal, E 2022, 'Metabolomic and microbiome profiling reveals personalized risk factors for coronary artery disease', Nature Medicine, vol. 28, no. 2, pp. 295-302. https://doi.org/10.1038/s41591-022-01686-6

APA

Talmor-Barkan, Y., Bar, N., Shaul, A. A., Shahaf, N., Godneva, A., Bussi, Y., Lotan-Pompan, M., Weinberger, A., Shechter, A., Chezar-Azerrad, C., Arow, Z., Hammer, Y., Chechi, K., Forslund, S. K., Fromentin, S., Dumas, M. E., Ehrlich, S. D., Pedersen, O., Kornowski, R., & Segal, E. (2022). Metabolomic and microbiome profiling reveals personalized risk factors for coronary artery disease. Nature Medicine, 28(2), 295-302. https://doi.org/10.1038/s41591-022-01686-6

Vancouver

Talmor-Barkan Y, Bar N, Shaul AA, Shahaf N, Godneva A, Bussi Y et al. Metabolomic and microbiome profiling reveals personalized risk factors for coronary artery disease. Nature Medicine. 2022;28(2):295-302. https://doi.org/10.1038/s41591-022-01686-6

Author

Talmor-Barkan, Yeela ; Bar, Noam ; Shaul, Aviv A. ; Shahaf, Nir ; Godneva, Anastasia ; Bussi, Yuval ; Lotan-Pompan, Maya ; Weinberger, Adina ; Shechter, Alon ; Chezar-Azerrad, Chava ; Arow, Ziad ; Hammer, Yoav ; Chechi, Kanta ; Forslund, Sofia K. ; Fromentin, Sebastien ; Dumas, Marc Emmanuel ; Ehrlich, S. Dusko ; Pedersen, Oluf ; Kornowski, Ran ; Segal, Eran. / Metabolomic and microbiome profiling reveals personalized risk factors for coronary artery disease. In: Nature Medicine. 2022 ; Vol. 28, No. 2. pp. 295-302.

Bibtex

@article{15cff1069c914c7fbdbd8984fa5c9732,
title = "Metabolomic and microbiome profiling reveals personalized risk factors for coronary artery disease",
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.",
author = "Yeela Talmor-Barkan and Noam Bar and Shaul, {Aviv A.} and Nir Shahaf and Anastasia Godneva and Yuval Bussi and Maya Lotan-Pompan and Adina Weinberger and Alon Shechter and Chava Chezar-Azerrad and Ziad Arow and Yoav Hammer and Kanta Chechi and Forslund, {Sofia K.} and Sebastien Fromentin and Dumas, {Marc Emmanuel} and Ehrlich, {S. Dusko} and Oluf Pedersen and Ran Kornowski and Eran Segal",
note = "Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive licence to Springer Nature America, Inc.",
year = "2022",
doi = "10.1038/s41591-022-01686-6",
language = "English",
volume = "28",
pages = "295--302",
journal = "Nature Medicine",
issn = "1078-8956",
publisher = "nature publishing group",
number = "2",

}

RIS

TY - JOUR

T1 - Metabolomic and microbiome profiling reveals personalized risk factors for coronary artery disease

AU - Talmor-Barkan, Yeela

AU - Bar, Noam

AU - Shaul, Aviv A.

AU - Shahaf, Nir

AU - Godneva, Anastasia

AU - Bussi, Yuval

AU - Lotan-Pompan, Maya

AU - Weinberger, Adina

AU - Shechter, Alon

AU - Chezar-Azerrad, Chava

AU - Arow, Ziad

AU - Hammer, Yoav

AU - Chechi, Kanta

AU - Forslund, Sofia K.

AU - Fromentin, Sebastien

AU - Dumas, Marc Emmanuel

AU - Ehrlich, S. Dusko

AU - Pedersen, Oluf

AU - Kornowski, Ran

AU - Segal, Eran

N1 - Publisher Copyright: © 2022, The Author(s), under exclusive licence to Springer Nature America, Inc.

PY - 2022

Y1 - 2022

N2 - 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.

AB - 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.

U2 - 10.1038/s41591-022-01686-6

DO - 10.1038/s41591-022-01686-6

M3 - Journal article

C2 - 35177859

AN - SCOPUS:85124760873

VL - 28

SP - 295

EP - 302

JO - Nature Medicine

JF - Nature Medicine

SN - 1078-8956

IS - 2

ER -

ID: 299198560