| Title: | Genetically determined intelligence and coronary artery disease risk |
| Journal: | Clinical Research in Cardiology |
| Published: | 2 Aug 2020 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/32740755/ |
| DOI: | https://doi.org/10.1007/s00392-020-01721-x |
| URL: | https://link.springer.com/content/pdf/10.1007/s00392-020-01721-x.pdf |
Publication 4960
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Abstract
BackgroundEpidemiological studies have shown inverse association between intelligence and coronary artery disease (CAD) risk, but the underlying mechanisms remain unclear.MethodsBased on 242 SNPs independently associated with intelligence, we calculated the genetic intelligence score (gIQ) for participants from 10 CAD case-control studies (n = 34,083) and UK Biobank (n = 427,306). From UK Biobank, we extracted phenotypes including body mass index (BMI), type 2 diabetes (T2D), smoking, hypertension, HDL cholesterol, LDL cholesterol, measured intelligence score, and education attainment. To estimate the effects of gIQ on CAD and its related risk factors, regression analyses was applied. Next, we studied the mediatory roles of measured intelligence and educational attainment. Lastly, Mendelian randomization was performed to validate the findings.ResultsIn CAD case-control studies, one standard deviation (SD) increase of gIQ was related to a 5% decrease of CAD risk (odds ratio [OR] of 0.95; 95% confidence interval [CI] 0.93 to 0.98; P = 4.93e-5), which was validated in UK Biobank (OR = 0.97; 95% CI 0.96 to 0.99; P = 6.4e-4). In UK Biobank, we also found significant inverse correlations between gIQ and risk factors of CAD including smoking, BMI, T2D, hypertension, and a positive correlation with HDL cholesterol. The association signals between gIQ and CAD as well as its risk factors got largely attenuated after the adjustment of measured intelligence and educational attainment. The causal role of intelligence in mediating CAD risk was confirmed by Mendelian randomization analyses.ConclusionGenetic components of intelligence affect measured intelligence and educational attainment, which subsequently affect the prevalence of CAD via a series of unfavorable risk factor profiles.Graphic abstract</p>
5 Authors
- Ling Li
- Shichao Pang
- Lingyao Zeng
- Ulrich Güldener
- Heribert Schunkert
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