Abstract

Background: Evolutionary biology suggests growth and reproduction trade-off against longevity. Genetically predicted insulin, a promotor of both growth and reproduction, is positively associated with ischemic heart disease. Here, we further investigate the role of genetically predicted insulin and insulin resistance in cardiovascular disease sub-types (myocardial infarction (MI), angina, and heart failure) and its risk factors by sex, given drivers of reproduction have sexspecific effects. Methods: Two-sample Mendelian randomization was used to obtain unconfounded estimates. Genetic variants strongly (p-value<5x10-8) associated with insulin, insulin adjusted for body mass index, and a validated insulin resistance genetic score, obtained from 108,557 Europeans without diabetes in MAGIC, were applied to 392,010 white British in the UK Biobank, with 14,442 MI cases (77% men), 21,939 angina cases (65% men), and 5,537 heart failure cases (71% men). The role in cardiovascular risk factors (low density lipoprotein (LDL)-cholesterol, apolipoprotein B, blood pressure, and reticulocyte count) was similarly examined. Findings: Genetically predicted insulin was associated with MI (odds ratio (OR) 4·27 per pmol/L higher insulin, 95% confidence interval (CI) 1·60 to 11·3) and angina (OR 2·93, 1·27 to 6·73) in men, but not women (OR for MI 0·80, 95% CI 0·23 to 2·84; angina 1·10, 95% CI 0·38 to 3·18), as was insulin resistance. The pattern was similar for heart failure. Interpretation: As suggested by evolutionary biology, genetically predicted insulin and insulin resistance were associated with MI and angina in a sex-specific way. Clarifying the underlying pathways could provide new insights into prevention and treatment strategies. Funding Statement: The authors received no specific funding for this work. Declaration of Interests: The authors declare: None. Ethics Approval Statement: The UK Biobank has already received ethical approval from the Research Ethics Committee and participants provided written informed consent. The analysis of other publicly available data or summary statistics does not require additional ethical approval.

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