Key result
Dysregulated metabolic pathways drive cardiovascular disease, revealing novel precision therapeutic and biomarker targets.
Why the study?
Metabolic dysfunction is increasingly recognized as a central driver of cardiovascular disease pathophysiology, creating a need to synthesize established clinical evidence and emerging experimental findings to guide therapeutic and biomarker innovation.
This narrative review synthesizes clinical and experimental evidence on how dysregulated lipid, glucose, amino acid, mitochondrial, and immunometabolic pathways drive cardiovascular disease, highlighting emerging metabolomic biomarkers and targeted therapeutic strategies.
Metabolic targets beyond lipids/glucose remain experimental; leaves open longitudinal multi-omics trials before precision therapy adoption.
Cardiovascular disease (CVD) remains the leading cause of death worldwide, and metabolic dysfunction is increasingly recognized as an important component of its pathophysiology. Clinical evidence supports a role for dysregulated lipid and glucose metabolism in atherosclerosis, heart failure, and cardiometabolic disease, while alterations in amino acid metabolism, mitochondrial energetics, redox signaling, and immunometabolic pathways are supported by growing experimental and observational evidence. Advances in metabolomics, systems biology, and multi-omics approaches have further identified metabolic signatures associated with cardiovascular phenotypes and have provided new insights into pathways regulating endothelial function, vascular inflammation, oxidative stress, and cardiac remodeling. This review synthesizes established clinical evidence and emerging experimental findings on metabolic mechanisms in CVD, with particular emphasis on their potential therapeutic and biomarker implications. We discuss current and investigational strategies targeting lipid and glucose metabolism, mitochondrial dysfunction, oxidative stress, and immunometabolic signaling, while distinguishing clinically validated approaches from those that remain primarily preclinical or hypothesis-generating. Key translational challenges include the complexity and tissue specificity of metabolic networks, limitations of existing experimental models, potential safety liabilities, and the need for longitudinal studies integrating metabolic and clinical phenotypes. Finally, we examine how metabolomics, AI, organ-on-chip models, and systems-level approaches could improve target identification, patient stratification, and therapeutic development. These advances provide a framework for translating mechanistic insights into metabolism-informed cardiovascular therapies and biomarkers, while highlighting the evidence gaps that must be addressed before broader clinical implementation.
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Kansakar et al. (2026) conducted a review in Cardiovascular disease. Metabolism-targeted cardiovascular therapies was evaluated. Metabolic pathways including lipid, glucose, amino acid, and mitochondrial energetics drive cardiovascular disease and offer targets for precision therapy and biomarker discovery.
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