Recent advances in applying metabolomics to uncover dietary impact on cardiometabolic health

Naixin Zhang*, Bjørn Lundbergh, Marta Guasch-Ferré

*Corresponding author for this work

Research output: Contribution to journalReviewResearchpeer-review

Abstract

Purpose of review Cardiometabolic diseases are a major global health concern, with diet playing a crucial role in their prevention and management. Recent advancements in the identification of metabolic signatures related to dietary patterns offer a more objective assessment of individualized dietary exposure and provide deeper insights into diet-disease associations. Recent findings Recent studies have shown that distinct metabolic signatures are associated with the adherence to various dietary patterns. These signatures show even stronger associations with cardiometabolic disease incidence, independent of traditional risk factors and self-reported adherence to such dietary patterns. Emerging dietary approaches, such as sustainable diets, health outcome-focused diets, and population data-driven dietary patterns, also hold promise for improving cardiometabolic health. Additionally, metabolic signatures could offer insights into diet-disease associations in underrepresented populations, addressing genetic and lifestyle differences. Summary Application of metabolomics provides a more precise understanding of how dietary patterns influence cardiometabolic health. Although the number of studies remains limited, and current evidence is inconsistent, the approach has significant potential for improving clinical and public health strategies. Future research should prioritize prospective studies and address population- and outcome-specific dietary needs to enable targeted interventions that optimize cardiometabolic health.

Original languageEnglish
JournalCurrent Opinion in Lipidology
Volume36
Issue number1
Number of pages7
ISSN0957-9672
DOIs
Publication statusPublished - 2025

Bibliographical note

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Keywords

  • cardiometabolic risk
  • dietary patterns
  • metabolic signatures
  • metabolomics

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