Abstract
AbstractBackgroundAtrial fibrillation and heart failure are closely related and share multiple risk factors. We aimed to apply the mendelian randomization (MR) analysis to explore the bidirectional causal link between atrial fibrillation and heart failure, and the independent effect of potential risk factors on the risk of both conditions.MethodsThis is a two-sample MR study using publicly available summary-level statistics of genome-wide association studies (GWAS). Bidirectional MR was performed to explore the relation between atrial fibrillation and heart failure. A total of 14 factors were selected as potential risk factors, univariable MR analyses were used to identify shared risk factors, and then the multivariable MR analyses were further used to investigate the independent effect of these factors on both conditions. Inverse-variance-weighted MR (IVW-MR) were used to obtain the effect estimates.ResultsMR analysis found evidence of causal relationship between atrial fibrillation and heart failure (odds ratio [OR], 1.24; 95% confidence interval [CI], 1.19–1.29), as well as between heart failure and atrial fibrillation (OR, 3.88; 95% CI, 1.45–10.37). Univariable MR analyses identified several shared risk factors for both conditions, including body mass index (BMI), blood pressure, smoking, coronary heart disease and myocardial infarction. After adjusting for atrial fibrillation, the observed associations between shared factors and heart failure kept stable, such as BMI, smoking, coronary heart disease and myocardial infarction. However, after adjusting for heart failure, the relationships between most risk factors and atrial fibrillation attenuated to null.ConclusionsThis two-sample MR study found a bidirectional relationship between atrial fibrillation and heart failure, and identified several shared risk factors of both conditions, which had an independent effect on the risk of heart failure while probably affected the risk of atrial fibrillation via cardiac impairment.FundingStart-up Fund for high-level talents of Fujian Medical University (grant no.XRCZX2021026) and Natural Science Foundation of Fujian Province (grant no. 2022J01706).
Publisher
Cold Spring Harbor Laboratory