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Predicting longevity using metabolomics: a novel tool for precision lifestyle medicine?

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Strategies to measure metabolomics data in large cohorts capture not only genetic information, but also lifestyle habits and clinical outcomes, which could contribute to the identification of genetic and lifestyle biomarkers. Such an approach might pave the way for the development of personalized lifestyle medicine.

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Fig. 1: Use of lifestyle and metabolomics markers for precision lifestyle medicine.

References

  1. Deelen, J. et al. A metabolic profile of all-cause mortality risk identified in an observational study of 44,168 individuals. Nat. Commun. 10, 3346 (2019).

    Article  Google Scholar 

  2. Després, J. P. et al. Abdominal obesity and the metabolic syndrome: contribution to global cardiometabolic risk. Arterioscler. Thromb. Vasc. Biol. 28, 1039–1049 (2008).

    Article  Google Scholar 

  3. Nordestgaard, B. G. & Varbo, A. Triglycerides and cardiovascular disease. Lancet 384, 626–635 (2014).

    Article  CAS  Google Scholar 

  4. Adiels, M. et al. Overproduction of very low-density lipoproteins is the hallmark of the dyslipidemia in the metabolic syndrome. Arterioscler. Thromb. Vasc. Biol. 28, 1225–1236 (2008).

    Article  CAS  Google Scholar 

  5. Mozaffarian, D. et al. Interplay between different polyunsaturated fatty acids and risk of coronary heart disease in men. Circulation 111, 157–164 (2005).

    Article  CAS  Google Scholar 

  6. Lemieux, I. et al. Elevated C-reactive protein: another component of the atherothrombotic profile of abdominal obesity. Arterioscler. Thromb. Vasc. Biol. 21, 961–967 (2001).

    Article  CAS  Google Scholar 

  7. Khera, A. V., Emdin, C. A. & Kathiresan, S. Genetic risk, lifestyle, and coronary artery disease. N. Engl. J. Med. 376, 1194–1195 (2017).

    PubMed  Google Scholar 

  8. Ross, R. et al. Importance of assessing cardiorespiratory fitness in clinical practice: a case for fitness as a clinical vital sign: a scientific statement from the American Heart Association. Circulation 134, e653–e699 (2016).

    Article  Google Scholar 

  9. Kujala, U. M. et al. Associations of aerobic fitness and maximal muscular strength with metabolites in young men. JAMA Netw. Open 2, e198265 (2019).

    Article  Google Scholar 

  10. Ma, J., Rosas, L. G. & Lv, N. Precision lifestyle medicine: a new frontier in the science of behavior change and population health. Am. J. Prev. Med. 50, 395–397 (2016).

    Article  Google Scholar 

Download references

Acknowledgements

The author has received research funding from the Canadian Institutes of Health Research and the Foundation of the Québec Heart and Lung Institute.

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Correspondence to Jean-Pierre Després.

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Després, JP. Predicting longevity using metabolomics: a novel tool for precision lifestyle medicine?. Nat Rev Cardiol 17, 67–68 (2020). https://doi.org/10.1038/s41569-019-0310-2

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