Novel Genes Associated With Atrial Fibrillation and the Predictive Models for AF Incorporating Polygenic Risk Score and PheWAS-Derived Risk Factors.

Autor: Chen SY; School of Chinese Medicine, China Medical University, Taichung, Taiwan; Genetics Center, Department of Medical Research, China Medical University Hospital, Taichung, Taiwan., Chen YC; Million-Person Precision Medicine Initiative, Department of Medical Research, China Medical University Hospital, Taichung, Taiwan., Liu TY; Million-Person Precision Medicine Initiative, Department of Medical Research, China Medical University Hospital, Taichung, Taiwan., Chang KC; Division of Cardiovascular Medicine, Department of Medicine, China Medical University Hospital, Taichung, Taiwan; School of Medicine, College of Medicine, China Medical University, Taichung, Taiwan., Chang SS; Division of Cardiovascular Medicine, Department of Medicine, China Medical University Hospital, Taichung, Taiwan; School of Medicine, College of Medicine, China Medical University, Taichung, Taiwan., Wu N; Department of Biological Sciences, Southeastern Oklahoma State University, Durant, Oklahoma, USA., Lee Wu D; Department of Internal Medicine, University of Oklahoma Health Sciences Center, Tulsa, Oklahoma, USA., Dunlap RK; College of Osteopathic Medicine, Oklahoma State University Center for Health Sciences, Tulsa, Oklahoma, USA., Chan CJ; Genetics Center, Department of Medical Research, China Medical University Hospital, Taichung, Taiwan., Yang JS; Genetics Center, Department of Medical Research, China Medical University Hospital, Taichung, Taiwan., Liao CC; Genetics Center, Department of Medical Research, China Medical University Hospital, Taichung, Taiwan., Tsai FJ; School of Chinese Medicine, China Medical University, Taichung, Taiwan; Genetics Center, Department of Medical Research, China Medical University Hospital, Taichung, Taiwan; Department of Medical Genetics, China Medical University Hospital, Taichung, Taiwan.
Jazyk: angličtina
Zdroj: The Canadian journal of cardiology [Can J Cardiol] 2024 Aug 13. Date of Electronic Publication: 2024 Aug 13.
DOI: 10.1016/j.cjca.2024.07.029
Abstrakt: Background: Atrial fibrillation (AF), the most common atrial arrhythmia, presents with varied clinical manifestations. Despite the identification of genetic loci associated with AF, particularly in specific populations, research within Asian ethnicities remains limited. In this study we aimed to develop predictive models for AF using AF-associated single-nucleotide polymorphisms (SNPs) from a genome-wide association study (GWAS) on a substantial cohort of Taiwanese individuals, to evaluate the predictive efficacy of the model.
Methods: There were 75,121 subjects, that included 5694 AF patients and 69,427 normal control subjects with GWAS data, and we merged polygenic risk scores from AF-associated SNPs with phenome-wide association study-derived risk factors. Advanced statistical and machine learning techniques were used to develop and evaluate AF predictive models for discrimination and calibration.
Results: The study identified the top 30 significant SNPs associated with AF, predominantly on chromosomes 10 and 16, implicating genes like NEURL1, SH3PXD2A, INA, NT5C2, STN1, and ZFHX3. Notably, INA, NT5C2, and STN1 were newly linked to AF. The GWAS predictive power using polygenic risk score-continuous shrinkage analysis for AF exhibited an area under the curve of 0.600 (P < 0.001), which improved to 0.855 (P < 0.001) after adjusting for age and sex. Phenome-wide association study analysis showed the top 10 diseases associated with these genes were circulatory system diseases.
Conclusions: Integrating genetic and phenotypic data enhanced the accuracy and clinical relevance of AF predictive models. The findings suggest promise for refining AF risk assessment, enabling personalized interventions, and reducing AF-related morbidity and mortality burdens.
Competing Interests: Disclosures The authors have no conflicts of interest to disclose.
(Copyright © 2024 Canadian Cardiovascular Society. Published by Elsevier Inc. All rights reserved.)
Databáze: MEDLINE
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