ORIGINAL RESEARCH article
Front. Endocrinol.
Sec. Cardiovascular Endocrinology
Association between plasma metabolites and atrial fibrillation in men
Provisionally accepted
Yingjie Ke1
Sihong Zhu2Na Lin3Xiaotian Liang1Cailing Zeng1Yuqing Li1Yuanyuan Lu1Zirou Huang1Kaihang Luo4
Huanlei Huang3*Runfen Lin1*
Jiansong Chen1*- 1Guangdong Provincial People's Hospital Nanhai Hospital, Foshan, China
- 2Sun Yat-Sen Memorial Hospital, Guangzhou, China
- 3Guangdong Provincial People's Hospital, Guangzhou, China
- 4The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
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Background:Atrial fibrillation is the most common cardiac arrhythmia globally, with rising incidence and a substantial public health impact. Identifying factors that contribute to atrial fibrillation risk is crucial for prevention and early detection. Methods:This study utilized data from the United Kingdom Biobank to explore the relationship between plasma metabolites and atrial fibrillation risk in men. A total of 168 plasma metabolites were analyzed using multivariable Cox proportional hazards analysis to identify associations with atrial fibrillation risk. Results:Our analysis identified several key findings:Most very-low-density lipoprotein subtypes were found to have a protective effect against atrial fibrillation.In contrast, most high-density lipoprotein subtypes were associated with an increased risk of atrial fibrillation. Specific amino acids, such as valine and histidine, demonstrated significant protective effects. Additionally, a predictive model combining traditional risk factors with metabolite data slightly enhanced the performance of conventional diagnostic models. Conclusion:The findings suggest that plasma metabolite profiles may serve as useful biomarkers for the early detection and prevention of atrial fibrillation. This highlights the potential for personalized interventions in clinical practice to better manage and mitigate atrial fibrillation risk.
Keywords: Atrial Fibrillation, HDL, Metabolites, UK Biobank, VLDL
Received: 22 Oct 2025; Accepted: 30 Jan 2026.
Copyright: © 2026 Ke, Zhu, Lin, Liang, Zeng, Li, Lu, Huang, Luo, Huang, Lin and Chen. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Huanlei Huang
Runfen Lin
Jiansong Chen
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