| Title: | Associations of Observational and Genetically Determined Caffeine Intake With Coronary Artery Disease and Diabetes Mellitus |
| Journal: | Journal of the American Heart Association |
| Published: | 8 Dec 2020 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/33287642/ |
| DOI: | https://doi.org/10.1161/jaha.120.016808 |
| URL: | https://www.ahajournals.org/doi/pdf/10.1161/JAHA.120.016808 |
Publication 9313
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Abstract
Background Caffeine is the most widely consumed psychostimulant and is associated with lower risk of coronary artery disease (CAD) and type 2 diabetes mellitus (T2DM). However, whether these associations are causal remains unknown. This study aimed to identify genetic variants associated with caffeine intake, and to investigate evidence for causal links with CAD or T2DM. In addition, we aimed to replicate previous observational findings. Methods and Results Observational associations were tested within UK Biobank using Cox regression analyses. Moderate observational caffeine intakes from coffee or tea were associated with lower risks of CAD or T2DM, with the lowest risks at intakes of 121 to 180 mg/day from coffee for CAD (hazard ratio [HR], 0.77 [95% CI, 0.73-0.82; P<1×10-16]), and 301 to 360 mg/day for T2DM (HR, 0.76 [95% CI, 0.67-0.86]; P=1.57×10-5). Next, genome-wide association studies were performed on self-reported caffeine intake from coffee, tea, or both in 407 072 UK Biobank participants. These analyses identified 51 novel genetic variants associated with caffeine intake at P<1.67×10-8. These loci were enriched for central nervous system genes. However, in contrast to the observational analyses, 2-sample Mendelian randomization analyses using the identified loci in independent disease-specific cohorts yielded no evidence for causal links between genetically determined caffeine intake and the development of CAD or T2DM. Conclusions Mendelian randomization analyses indicate genetically determined higher caffeine intake might not protect against CAD or T2DM, despite protective associations in observational analyses.</p>
4 Authors
- M. Abdullah Said
- Yordi J. van de Vegte
- Niek Verweij
- Pim van der Harst
2 Applications
| Application ID | Title |
|---|---|
| 12006 | The value of risk scores to predict in the UK biobank population to predict clinical outcome, with a focus on atherosclerotic and thrombotic vascular events. |
| 15031 | Genetic dissection of cardiovascular risk factors and their relation to disease to establish causality and identify novel targets of therapy |
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