From Exposure to Atherosclerosis: Mechanistic Insights into Phthalate-Driven Ischemic Heart Disease and Prevention Strategies

TL;DR

This paper reviews how phthalates, common plasticizers, may contribute to ischemic heart disease through mechanisms like oxidative stress and atherosclerosis.

Contribution

The paper provides a comprehensive synthesis of phthalate-induced IHD mechanisms and novel prevention strategies using AI.

Findings

Phthalates are linked to atherosclerosis through oxidative stress and mitochondrial dysfunction.

Epidemiological and experimental evidence supports phthalate-induced endothelial damage and atherogenesis.

AI-based frameworks could improve risk prediction and prevention of phthalate-related heart disease.

Abstract

Despite decades of interventions targeting modifiable risk factors to reduce the burden of cardiovascular disease, ischemic heart disease (IHD) remains the leading cause of mortality and the second leading cause of disability-adjusted life-years worldwide. Growing evidence suggests that phthalates–plasticizers widely used in consumer products, cosmetics, and medical devices, and therefore ubiquitous across environmental media, may contribute to IHD development. Epidemiological studies have reported associations between phthalate exposure and multiple markers of atherosclerosis, the pathological hallmark of IHD, with or without mediation by traditional cardiovascular risk factors. Experimental models support these findings, showing that phthalates can induce oxidative stress, mitochondrial dysfunction, apoptosis, lipid accumulation, and epigenetic alterations, all of which promote endothelial damage and atherogenesis. In this review, we synthesize current epidemiological findings linking phthalate exposure to IHD, describe the main cellular and molecular mechanisms involved, and outline research gaps and regulatory perspectives. We also discuss how novel analytical frameworks—including artificial intelligence—may enhance the integration of environmental, clinical, and molecular data to advance risk prediction and prevention strategies.

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