ReviewFrontiers in endocrinology2026
Multi-omics in coronary atherosclerosis: mechanistic insights and advances in precision diagnosis and treatment.
Review in Frontiers in endocrinology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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8 authors.
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Abstract
Coronary atherosclerosis, driven by the interplay of lipid metabolic derangements and chronic inflammation, constitutes the pathological basis of atherosclerotic cardiovascular disease and has emerged as the leading cause of mortality among Chinese residents. In patients with acute coronary syndrome, subsequent events may arise from initially nonculprit coronary lesions that appear angiographically mild. Invasive coronary angiography, the conventional diagnostic reference standard, is inherently invasive and incapable of characterizing plaque biological properties. Meanwhile, traditional risk factors only enable crude risk stratification, resulting in a critical shortage of precise early clinical screening modalities. Multi-omics technologies enable comprehensive molecular profiling of the human organism and effectively address the limitations of conventional detection approaches. Nevertheless, existing investigations remain largely confined to single-omics analyses; candidate biomarkers lack validation in large independent cohorts, and substantial bottlenecks persist in clinical translation. This review evaluates the respective advantages and limitations of genomics, epigenomics, transcriptomics, proteomics, metabolomics, lipidomics, and gut metagenomics in coronary atherosclerosis research. It elucidates the scientific value of integrated multi-omics analysis in dissecting pathogenic regulatory networks, unraveling gut-heart axis mechanisms, and identifying targets for precision therapy. Furthermore, it summarizes cutting-edge technological advances including single-cell multi-omics, spatial multi-omics, liquid biopsy, and AI-powered multi-omics integration, and compiles multi-omics risk prediction models developed on the basis of large-scale population cohorts. By bridging genetic susceptibility, cellular remodeling, peripheral molecular signatures, and plaque phenotypes, multi-omics integration can underpin early risk warning for high-risk populations, plaque subtyping, and therapeutic efficacy monitoring. Looking ahead, the establishment of standardized, multicenter prospective cohorts and the application of Mendelian randomization to infer causal relationships will be pivotal. These efforts are essential to translate multi-omics into a practical framework for comprehensive precision medicine across the entire continuum of coronary atherosclerosis.
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