Abstract
Aims Observational studies of diet in cardiometabolic-cardiovascular disease (CM-CVD) focus on self-reported consumption of food or dietary pattern, with limited information on individual metabolic responses to dietary intake linked to CM-CVD. Here, machine learning approaches were used to identify individual metabolic patterns related to diet and relation to long-term CM-CVD in early adulthood. ..................... Methods and results In 2259 White and Black adults (age 32.1 ± 3.6 years, 45% women, 44% Black) in the Coronary Artery Risk Development in Young Adults (CARDIA) study, multivariate models were employed to identify metabolite signatures of food group and composite dietary intake across 17 food groups, 2 nutrient groups, and healthy eating index-2015 (HEI2015) diet quality score. A broad array of metabolites associated with diet were uncovered, reflecting food-related components/catabolites (e.g. fish and long-chain unsaturated triacylglycerols), interactions with host features (microbiome), or pathways broadly implicated in CM-CVD (e.g. ceramide/sphingomyelin lipid metabolism). To integrate diet with metabolism, penalized machine learning models were used to define a metabolite signature linked to a putative CM-CVD-adverse diet (e.g. high in red/processed meat, refined grains), which was subsequently associated with long-term diabetes and CVD risk numerically more strongly than HEI2015 in CARDIA [e.g. diabetes: standardized hazard ratio (HR): 1.62, 95% confidence interval (CI): 1.32–1.97, P < 0.0001; CVD: HR: 1.55, 95% CI: 1.12–2.14, P = 0.008], with associations replicated for diabetes (P < 0.0001) in the Framingham Heart Study. Conclusion Metabolic signatures of diet are associated with long-term CM-CVD independent of lifestyle and traditional risk factors. Metabolomics improves precision to identify adverse consequences and pathways of diet-related CM-CVD.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 557-569 |
| Number of pages | 13 |
| Journal | European heart journal |
| Volume | 44 |
| Issue number | 7 |
| DOIs | |
| State | Published - Feb 14 2023 |
Bibliographical note
Funding Information:The authors wish to acknowledge the participants and research staff of the CARDIA and FHS studies, without whom this research would not be possible. This work was supported by grants from the National Institutes of Health (R01 HL136685 to R.V.S. and V.L.M.; K23-HL138260, R01-HL156975 to M.N., K01-HL127159 to K.M.) and the American Heart Association. The Coronary Artery Risk Development in Young Adults Study (CARDIA) is conducted and supported by the National Heart, Lung, and Blood Institute (NHLBI) in collaboration with the University of Alabama at Birmingham (HHSN268201800005I and HHSN268201800007I), Northwestern University (HHSN268201800003I), University of Minnesota (HHSN268201800006I), and Kaiser Foundation Research Institute (HHSN268201800004I). The Framingham Heart Study (FHS) acknowledges the support of Contracts NO1-HC-25195, HHSN268201500001I and 75N92019D00031 from the National Heart, Lung and Blood Institute and NIH grant R01DK080739 for this research. V.L.M. is supported by the Melvyn Rubenfire Professorship in Preventive Cardiology. M.N. is also supported by a Career Investment Award from the Department of Medicine, Boston University School of Medicine. R.S.V. is supported in part by the Evans Medical Foundation and the Jay and Louis Coffman Endowment from the Department of Medicine, Boston University School of Medicine. This manuscript has been reviewed by CARDIA for scientific content. The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute; the National Institutes of Health; or the U.S. Department of Health and Human Services.
Publisher Copyright:
© The Author(s) 2022. Published by Oxford University Press on behalf of European Society of Cardiology. All rights reserved.
Keywords
- CVD
- Diet
- Metabolism
- Metabolomics
- Nutrition
- Precision medicine
