Large-Scale Plasma Proteomics Profiles for Predicting Atrial Fibrillation Associated Stroke Risk : Type of manuscript: Original Research.
S, H., X, F., H, W., R, L., Y, G., Z, W., B, T., J, W., J, F., & Z, Y. (2026). Large-Scale Plasma Proteomics Profiles for Predicting Atrial Fibrillation Associated Stroke Risk : Type of manuscript: Original Research.. Translational stroke research. https://doi.org/10.1007/s12975-026-01476-z
S H, X F, H W, R L, Y G, Z W, et al. Large-Scale Plasma Proteomics Profiles for Predicting Atrial Fibrillation Associated Stroke Risk : Type of manuscript: Original Research.. Translational stroke research. 2026; doi: 10.1007/s12975-026-01476-z
S H, X F, H W, et al. Large-Scale Plasma Proteomics Profiles for Predicting Atrial Fibrillation Associated Stroke Risk : Type of manuscript: Original Research.[J]. Translational stroke research. 2026. DOI: 10.1007/s12975-026-01476-z.
@article{s2026,
author = {Huang S and Feng X and Wu H and Liang R and Gao Y and Wang Z and Tang B and Wu J and Fang J and Yang Z},
title = {Large-Scale Plasma Proteomics Profiles for Predicting Atrial Fibrillation Associated Stroke Risk : Type of manuscript: Original Research.},
journal = {Translational stroke research},
year = {2026},
doi = {10.1007/s12975-026-01476-z},
note = {PMID: 42489810},
}
TY - JOUR AU - Huang S AU - Feng X AU - Wu H AU - Liang R AU - Gao Y AU - Wang Z AU - Tang B AU - Wu J AU - Fang J AU - Yang Z TI - Large-Scale Plasma Proteomics Profiles for Predicting Atrial Fibrillation Associated Stroke Risk : Type of manuscript: Original Research. T2 - Translational stroke research PY - 2026 DO - 10.1007/s12975-026-01476-z AN - PMID:42489810 ER -
BACKGROUND: Stroke is a major complication of atrial fibrillation (AF), and risk prediction using the congestive heart failure, hypertension, age, diabetes, stroke, vascular disease, and sex category score (CHA₂DS₂-VASc) remains limited by residual heterogeneity. We aimed to identify plasma proteins associated with post-AF stroke and evaluate whether a protein score provides incremental predictive information beyond CHA₂DS₂-VASc. METHODS: We analyzed 709 AF participants from the UK Biobank Pharma Proteomics Project, with 76 incident strokes. Stroke-related proteins were identified using multivariable Cox regression, least absolute shrinkage and selection operator (LASSO) Cox regression, and machine-learning approaches. A five-protein score was constructed, and its incremental value beyond CHA₂DS₂-VASc was assessed by discrimination, calibration, reclassification, clinical net benefit, and 1000-bootstrap internal validation. Mendelian randomization served as supportive genetic evidence. RESULTS: Five core proteins were identified: epidermal growth factor receptor (EGFR), V-type proton ATPase subunit D (ATP6V1D), neurotrophin 4 (NTF4), amnionless (AMN), and discoidin, CUB and LCCL domain-containing protein 2 (DCBLD2). Adding the five-protein score to CHA₂DS₂-VASc improved discrimination, increasing the concordance index from 0.681 to 0.768. The combined model had 3-, 5-, and 8-year receiver operating characteristic areas of 0.799, 0.775, and 0.806, respectively, and showed favorable five-year prediction error and calibration, with a Brier score of 0.0347, calibration intercept of -0.068, and calibration slope of 0.968. The score improved continuous net reclassification improvement (0.459; P = 0.028). Mendelian randomization provided supportive genetic evidence for AMN, EGFR, and DCBLD2. CONCLUSIONS: The five-protein score provided incremental predictive information beyond CHA₂DS₂-VASc for post-AF stroke risk assessment.