| Title: | Bidirectional associations between coronary artery disease and epilepsy: cross-sectional and prospective analyses from the UK biobank |
| Journal: | The Journal of Cardiovascular Aging |
| Published: | 27 Apr 2026 |
| DOI: | https://doi.org/10.20517/jca.2026.03 |
| URL: | https://f.oaes.cc/xmlpdf/published/article/054b5d9a5950cd3ab22c215185c424fa/jca6003.pdf |
Publication 17824
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Abstract
Aim: This study aimed to evaluate the bidirectional association between coronary artery disease (CAD) and epilepsy and to examine the modifying effect of genetic susceptibility. Methods: Using data from the UK Biobank, we conducted cross-sectional and longitudinal analyses. In the cross-sectional analysis (n = 502,359), logistic regression estimated odds ratios for the association between CAD and epilepsy. In Cohort 1 (n = 496,921 without baseline epilepsy), stratified Cox models assessed the risk of incident epilepsy by CAD status. In Cohort 2 (n = 475,130 without baseline CAD), the risk of incident CAD by epilepsy status was similarly evaluated. Polygenic risk scores for CAD and epilepsy were incorporated to assess genetic modification.Results: The median baseline age was 58.0 years, and 45.6% were male. Over a median follow-up of 13.8 years, 3,590 participants developed epilepsy and 39,223 developed CAD. CAD was significantly associated with epilepsy both cross-sectionally and longitudinally (hazard ratio (HR) 1.32; 95% confidence interval (CI): 1.15-1.51; P < 0.001). Conversely, epilepsy increased CAD risk (HR 1.31; 95%CI: 1.12-1.54; P < 0.001). These associations were consistent across age, sex, and body mass index (BMI) strata. CAD predicted epilepsy only in participants with low genetic risk, while epilepsy predicted CAD mainly in those with high genetic risk. Conclusions: Our findings indicate a bidirectional association between CAD and epilepsy. Additionally, this association exhibits heterogeneity across subgroups and may be influenced by genetic susceptibility. These results underscore the need for further studies to elucidate the underlying mechanisms and clinical implications.</p>
7 Authors
- Li Zhang
- Weifang Liu
- Yilu Xue
- Liwen Wang
- Cong Gong
- Zhi-Gang She
- Hongliang Li
1 Application
| Application ID | Title |
|---|---|
| 77195 | Identifying the association factors and causal determinants in metabolic diseases |
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