Circulating proteomics could complement imaging-based risk assessment in bicuspid aortic valve disease, but existing models from general aortic stenosis populations cannot be transferred directly.
Circulating proteomics holds promise for mechanistic phenotyping and cohort enrichment in bicuspid aortic valve disease, but requires BAV-specific prospective cohorts before clinical implementation.
Bicuspid aortic valve (BAV) disease is a lifelong disorder in which congenital anatomy, tissue susceptibility, abnormal flow, and acquired fibrocalcific remodeling produce heterogeneous valve and aortic outcomes. This narrative review examined peer-reviewed literature indexed in PubMed/MEDLINE through June 2026 to evaluate how circulating proteomics could complement established imaging-based risk assessment. Published studies of incident aortic stenosis consistently implicate integrated stress, inflammation, apoptosis, and extracellular-matrix remodeling, with recurrent signals including GDF15, MMP12, and natriuretic peptides. These data support a long preclinical molecular phase, but existing proteomic models were developed predominantly in general aortic stenosis populations and cannot be transferred directly to BAV. We propose a five-layer framework integrating valve morphology and function, aortic phenotype and growth, flow and wall mechanics, molecular activity, and patient-specific lifetime context. In the near term, proteomics is best used for cohort enrichment, mechanistic phenotyping, and trial design rather than intervention decisions. Prospective BAV-specific cohorts, standardized imaging, repeated sampling, competing-risk analysis, external calibration, and demonstration of management-changing utility are required before clinical implementation. Molecular phenotyping should refine, not replace, guideline-based imaging and shared decision-making.
Luo et al. (Wed,) conducted a review in Bicuspid aortic valve (BAV) disease. Circulating proteomics vs. Established imaging-based risk assessment was evaluated. Circulating proteomics could complement imaging-based risk assessment in bicuspid aortic valve disease, but existing models from general aortic stenosis populations cannot be transferred directly.