Abstract
Aims: Genetic disposition and lifestyle factors are understood as independent components underlying the risk of multiple diseases. In this study, we aim to investigate the interplay between genetics, educational attainment - an important denominator of lifestyle - and coronary artery disease (CAD) risk. Methods and results: Based on the effect sizes of 74 genetic variants associated with educational attainment, we calculated a 'genetic education score' in 13 080 cases and 14 471 controls and observed an inverse correlation between the score and risk of CAD [P = 1.52 × 10-8; odds ratio (OR) 0.79, 95% confidence interval (CI) 0.73-0.85 for the higher compared with the lowest score quintile]. We replicated in 146 514 individuals from UK Biobank (P = 1.85 × 10-6) and also found strong associations between the 'genetic education score' with 'modifiable' risk factors including smoking (P = 5.36 × 10-23), body mass index (BMI) (P = 1.66 × 10-30), and hypertension (P = 3.86 × 10-8). Interestingly, these associations were only modestly attenuated by adjustment for years spent in school. In contrast, a model adjusting for BMI and smoking abolished the association signal between the 'genetic education score' and CAD risk suggesting an intermediary role of these two risk factors. Mendelian randomization analyses performed with summary statistics from large genome-wide meta-analyses and sensitivity analysis using 1271 variants affecting educational attainment (OR 0.68 for the higher compared with the lowest score quintile; 95% CI 0.63-0.74; P = 3.99 × 10-21) further strengthened these findings. Conclusion: Genetic variants known to affect educational attainment may have implications for a health-conscious lifestyle later in life and subsequently affect the risk of CAD.
| Original language | English |
|---|---|
| Journal | European Heart Journal |
| Volume | 40 |
| Issue number | 29 |
| Pages (from-to) | 2413-2420 |
| Number of pages | 8 |
| ISSN | 0195-668X |
| DOIs | |
| Publication status | Published - 08.2019 |
Funding
This work was supported by grants from the Fondation Leducq (CADgenomics: Understanding CAD Genes, 12CVD02), the German Federal Ministry of Education and Research (BMBF) within the framework of the e:Med research and funding concept (e:AtheroSysMed, grant 01ZX1313A-2014), and the European Union Seventh Framework Programme FP7/2007-2013 under grant agreement no HEALTH-F2-2013-601456 (CVgenes-at-target). Further grants were received from the DFG as part of the Sonderforschungsbereich CRC 1123 (B2). T.K. was supported by a DZHK Rotation Grant. Analysis in UK Biobank was funded by British Heart Foundation (BHF) grant RG/14/5/30893 to P.D. and forms part of the research themes contributing to the translational research portfolio of Barts Cardiovascular Biomedical Research Centre which is funded by the National Institute for Health Research (NIHR). Conflict of interest: J.D. reports grants from UK Medical Research Council, grants from British Heart Foundation, grants from UK National Institute of Health Research, grants from European Commission, during the conduct of the study; personal fees and non-financial support from Merck Sharpe & Dohme UK Atherosclerosis, personal fees and nonfinancial support from Novartis Cardiovascular and Metabolic Advisory Board, personal fees and non-financial support from Pfizer Population Research Advisory Panel, grants from British Heart Foundation, grants from European Research Council, grants from Merck, grants from National Institute of Health Research, grants from NHS Blood and Transplant, grants from Novartis, grants from Pfizer, grants from UK Medical Research Council, grants from Wellcome Trust, outside the submitted work.
Research Areas and Centers
- Research Area: Medical Genetics
