Key result
Multiomics review links >240 genetic risk loci to AS, reframing it as an active disease.
Why the study?
A limited understanding of the molecular pathogenesis of aortic valve stenosis has hindered the development of approved pharmacological therapies, leaving aortic valve replacement as the only effective treatment.
A comprehensive multiomics characterization reframes aortic stenosis as an active, genetically influenced disease, paving the way for targeted pharmacotherapies and precision diagnostics.
Answers are grounded in this paper and cite their sources.
Multiomics synthesis of AS pathogenesis extends molecular models; leaves open identification of druggable targets for future trials.
Aortic valve stenosis (AS) is the most prevalent form of valvular heart disease in developed countries. However, a limited understanding of its molecular pathogenesis has hindered the development of an approved pharmacological therapy. Currently, the only effective treatment is aortic valve replacement once the disease becomes severe. This review synthesizes our current understanding of AS with a multiomics approach, which integrates findings from genomics, transcriptomics, proteomics, and metabolomics to construct a systems-level view of AS. Recent landmark studies in 2025 have exponentially expanded the known genetic architecture of AS, identifying over 240 risk loci through massive multiancestry meta-analyses and deep learning–derived imaging phenotypes. Genomics has identified key genetic risk loci, most notably LPA , and established that the genetic framework of AS is distinct from that of atherosclerosis. Transcriptomics, particularly at the single-cell level, has revealed cellular heterogeneity within the valve, identifying specific profibrocalcific cell populations and highlighting pathogenic processes such as endothelial-to-mesenchymal transition. This discipline has also revealed the role of noncoding RNAs, such as H19 , in regulating osteogenic programs. Proteomics has identified effector proteins and candidate circulating biomarkers, including Matrix Metalloproteinase-12 as a marker of progression and Complement C1q TNF-Related Protein 1 as a potential causal factor. Additionally, proteomics has uncovered a novel link between AS and amyloidogenesis. Metabolomics has mapped the metabolic reprogramming that fuels AS, identifying procalcific metabolites such as lysophosphatidic acid and linking them to genetic risk factors. These omics domains reveal cohesive pathogenic pathways, such as the Lp(a)-autotaxin-LysoPA axis. This comprehensive molecular characterization has revolutionized our understanding of AS, reframing it as an active, genetically influenced disease and paving the way for the development of targeted pharmacotherapies and precision diagnostics.
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Treleaven et al. (2026) conducted a review in Aortic valve stenosis. A multiomics review of aortic stenosis identifies over 240 genetic risk loci and cohesive pathogenic pathways, reframing the condition as an active, genetically influenced disease.
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