Evidence map›Paper›PMID 41816793›Full record

ArticleFrontiers in genetics2026

m6AHD: a new framework for identifying abnormal N6-methyladenosine (m6A) in heart diseases based on sequencing features.

Jiajie Lu, Yanan Li, Yuxiang Hong, Dongshan Liao, Guanhua Fang

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Article in Frontiers in genetics, 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

5 authors.

Jiajie LuDepartment of Cardiovascular Surgery, Fujian Medical University Union Hospital, Fuzhou, Fujian, China.
Yanan LiKey Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China.
Yuxiang HongKey Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou, China.
Dongshan LiaoDepartment of Cardiovascular Surgery, Fujian Medical University Union Hospital, Fuzhou, Fujian, China.
Guanhua FangDepartment of Cardiovascular Surgery, Fujian Medical University Union Hospital, Fuzhou, Fujian, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Cardiovascular disease (CVD) is a major threat to health, with high incidence rates and a trend toward younger age groups. RNA modifications are an important component of epigenetics, widely present and indispensable in cells. Increasing evidence suggests that RNA modifications are key regulatory factors involved in cardiac physiological and pathological changes. Understanding the role of RNA modifications in heart-related diseases can help us to identify new drug targets. Methods: To systematically investigate the role of m6A modification in different cardiac diseases, we integrated m6A epitranscriptome profiles from five cardiac pathological conditions (three drug-induced cardiac toxicity models-Evodiamine, Matrine, and TKI, hypertrophy, and heart calcification) and their control groups to construct the first predictive model for abnormal m6A modification in cardiac diseases. We constructed separate models for upregulated and downregulated modifications under different pathological conditions, performed feature selection and parameter optimization, and validated the performance of our models using an independent test set. Results: m6AHD demonstrated excellent performance on the independent test set, with AUROC scores ranging from 0.728 to 0.880 across various pathological conditions. Cross-validation across different conditions and model interpretability demonstrated that m6A modifications exhibit similar patterns under different pathological conditions and are potentially regulated by similar factors, providing new clues for identifying targets in cardiovascular diseases at the epitranscriptome level. Furthermore, we validated our findings using a zebrafish model of Evodiamine-induced cardiotoxicity. The experimental results revealed significant morphological defects and a broad downregulation of m6A methyltransferase complex components, confirming the involvement of aberrant m6A machinery in the pathology of cardiotoxicity. Discussion: m6AHD is the first dedicated framework for predicting multi-condition cardiac m6A dysregulation. Our findings underscore the critical role of m6A homeostasis in cardiomyocyte function and demonstrate that aberrant methylation patterns can serve as reliable indicators of cardiac pathology. This framework provides a robust computational tool for identifying potential therapeutic targets at the epitranscriptome level for cardiovascular diseases.

Indexed as

bioinformatics frameworkcardiac diseasem6Amachine learningRNA modification

Identifiers

PMID41816793
PMCPMC12975140

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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 Socratic graph.