Evidence map›Paper›PMID 42902265›Full record

ArticleBMC medicine2026

Integrated proteomics and machine learning reveal AHNAK as a discriminative biomarker of atrial fibrillation in heart failure.

Wengen Zhu, Zhenbang Gu, Yuwen Huang, Min Ye, Ruicong Xue, Yugang Dong, Yuzhong Wu, Chen Liu

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Article in BMC medicine, 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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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Wengen Zhu *Department of Cardiology, the First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510080, PR China. zhuwg6@mail.sysu.edu.cn.
Zhenbang Gu *Department of Cardiology, the First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510080, PR China.
Yuwen Huang *Department of Cardiology, the First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510080, PR China.
Min YeDepartment of Cardiology, the First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510080, PR China.
Ruicong XueDepartment of Cardiology, the First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510080, PR China.
Yugang DongDepartment of Cardiology, the First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510080, PR China.
Yuzhong WuDepartment of Cardiology, the First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510080, PR China. yuzungng@qq.com.
Chen LiuDepartment of Cardiology, the First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510080, PR China. liuch75@mail.sysu.edu.cn.

Funding

Basic and Applied Basic Research Foundation of Guangdong Province 2023A1515110248Guangdong Natural Science Foundation 2024A1515013289Guangzhou Municipal Science and Technology Bureau Basic Research Program 2024A04J4561Key R and D Projects of Guangzhou Science and Technology Program 2023B03J1243National Natural Science Foundation of China 82370383, 82170384the Non-profit Central Research Institute Fund of Chinese Academy of Medical Sciences 2023-PT320-03
6 · The paper itself

Abstract

backgroundAtrial fibrillation (AF) is a frequent complication of heart failure (HF), markedly increasing morbidity and mortality. Although atrial fibrosis is increasingly recognized as a central mechanistic substrate linking HF to AF, the molecular determinants driving fibrotic remodeling and enabling early AF discrimination in HF remain poorly defined.

methodsWe integrated label-free quantitative plasma proteomics with machine learning-based feature selection to analyze samples from 59 age- and sex-matched patients hospitalized with acute decompensated HF. Differentially expressed proteins were subjected to functional and pathway enrichment analyses, and candidate biomarkers were prioritized using an incremental feature selection framework. AHNAK, the top-ranked candidate, was functionally interrogated in vitro using TGF-β1-stimulated primary mouse atrial fibroblasts with siRNA-mediated knockdown and in vivo using a pressure overload-induced HF model in AHNAK heterozygous mice. A two-sample Mendelian randomization analysis was performed to evaluate the association between genetically proxied AHNAK expression and AF risk.

resultsPlasma proteomic profiling identified 126 proteins that were significantly dysregulated in HF patients with AF compared with those in sinus rhythm, among which AHNAK was the most upregulated. Machine learning-based feature selection consistently ranked AHNAK as the most discriminative protein, with robust performance for AF discrimination in HF patients (AUC = 0.897, 95% confidence interval: 0.82-0.97). Functionally, AHNAK heterozygous deficiency promoted a profibrotic phenotype, characterized by increased expression of α-smooth muscle actin, fibronectin, and collagen Iα in atrial fibroblasts and exacerbated atrial fibrosis and cardiac dysfunction in pressure-overloaded mice. Mendelian randomization analysis demonstrated a significant protective effect of higher AHNAK expression against AF, with no evidence of horizontal pleiotropy.

conclusionsThis study identifies AHNAK as a discriminative plasma biomarker for AF in HF patients and implicates AHNAK deficiency as a contributor to atrial fibrotic remodeling and AF pathogenesis. External validation in larger and prospective HF cohorts will be required to confirm the clinical utility of AHNAK for AF risk stratification and early detection.

Indexed as

Atrial FibrillationHeart FailureMachine LearningMembrane ProteinsProteomicsAnimalsBiomarkersFemaleHumansMaleMiceNeoplasm ProteinsAhnak protein, mouseBiomarkersMembrane ProteinsNeoplasm ProteinsAHNAK proteinAtrial fibrillationAtrial fibrosisBiomarkersHeart failure

Identifiers

PMID42902265
PMCPMC13685328

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.