Abstract
Chronic inflammation has long been recognized as a major risk factor for and a causal contributor to cardiovascular disease (CVD). However, advances in omics technologies and deepening insights into CVD pathogenesis have expanded our understanding of the underlying mechanisms. Inflammation is now seen not as an isolated cause, but as one of several biological responses to cumulative tissue damage over time. In this Review, we propose that inflammation initially functions as a resilience mechanism, acting to resolve molecular and cellular damage driven by environmental stressors and intrinsic age-related entropy. With ageing, however, this protective response can become dysregulated and maladaptive, promoting collateral pathological changes. We illustrate this theory through two examples, atherosclerosis and age-related impairment of tissue perfusion, and support these conceptual models using proteomic data from large population studies with cardiovascular outcomes. Our findings reaffirm the central role of inflammation in CVD pathophysiology, but also indicate that the upstream biological driver of inflammation is molecular damage that is either not readily prevented or repaired by inadequate resilience mechanisms. Understanding the coordination of these responses offers new opportunities for targeted prevention and treatment of CVD.
Key points
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Ageing, endothelial dysfunction and impaired perfusion lead to molecular damage and trigger resilience mechanisms to maintain tissue integrity.
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Persistent, unrepaired molecular damage activates inflammatory responses that, over time, contribute to atherosclerosis.
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In ageing, impaired vascular regulation and tissue fibrosis can cause recurrent hypoperfusion, leading to energy deficits and progressive molecular damage.
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Chronic inflammation acts as a component of stress response pathways that, ultimately, lead to the onset and progression of cardiovascular disease.
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Biomarkers of cardiovascular disease, such as fibroblast growth factor 23 and growth/differentiation factor 15, reflect not only inflammation, but also changes in the extracellular matrix, cellular senescence and proteostasis.
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Data availability
Datasets and the custom R source code used in the proteomic meta-analysis are available on the Open Science Framework repository117.
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The authors acknowledge the support of the Intramural Research Program of the National Institute on Aging, National Institutes of Health, Baltimore, MD, USA.
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Glossary
- Biomarkers
-
Measurable indicators of biological and pathogenic processes or therapeutic efficacy.
- Cellular senescence
-
A state of stable cell cycle arrest caused by sublethal DNA damage and stress.
- Entropy
-
The measure of a system’s thermal energy per unit temperature that is unavailable for doing useful work.
- Immunosenescence
-
Innate and adaptive immune dysregulation that occurs with ageing.
- Integrated stress response
-
The signalling pathway activated in response to various forms of stress, including nutrient and oxygen deprivation, oxidative stress and viral infections.
- Macromolecular damage
-
The accumulation of structural and chemical alterations in DNA, proteins, lipids and polysaccharides within cells.
- Perfusion
-
The passing of a fluid through spaces.
- Proteostasis or proteostatic
-
Protein homeostasis or homeostatic state.
- Resilience response
-
The capacity of an organism to adapt or recover from stress. The response involves molecular pathways that detect stress, promote survival and enable repair.
- Senescence-associated secretory phenotype
-
The secretion of bioactive molecules associated with damage-induced cellular senescence.
- Stochastic
-
Occurring by chance or random variables.
- Thermodynamics
-
The relationships between heat, work, temperature and energy.
- Unfolded protein response
-
The signalling pathway responsible for the fidelity of protein folding in the lumen of the endoplasmic reticulum.
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Herman, A.B., Candia, J., Wilson, D.M. et al. Molecular damage associated with ageing drives inflammation in cardiovascular disease. Nat Rev Cardiol (2026). https://doi.org/10.1038/s41569-026-01253-3
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DOI: https://doi.org/10.1038/s41569-026-01253-3


