Cardiac Risk Factors for Stroke: A Comprehensive Mendelian Randomization Study

Background and Purpose: Observational studies suggest an association of stroke with cardiac traits beyond atrial fibrillation, the leading source of cardioembolism. However, controversy remains regarding a causal role of these traits in stroke pathogenesis. Here, we leveraged genetic data to systematically assess associations between cardiac traits and stroke risk using a Mendelian Randomization framework. Methods: We studied 66 cardiac traits including cardiovascular diseases, magnetic resonance imaging–derived cardiac imaging, echocardiographic imaging, and electrocardiographic measures, as well as blood biomarkers in a 2-sample Mendelian Randomization approach. Genetic predisposition to each trait was explored for associations with risk of stroke and stroke subtypes in data from the MEGASTROKE consortium (40 585 cases/406 111 controls). Using multivariable Mendelian Randomization, we adjusted for potential pleiotropic or mediating effects relating to atrial fibrillation, coronary artery disease, and systolic blood pressure. Results: As expected, we observed strong independent associations between genetic predisposition to atrial fibrillation and cardioembolic stroke and between genetic predisposition to coronary artery disease as a proxy for atherosclerosis and large-artery stroke. Our data-driven analyses further indicated associations of genetic predisposition to both heart failure and lower resting heart rate with stroke. However, these associations were explained by atrial fibrillation, coronary artery disease, and systolic blood pressure in multivariable analyses. Genetically predicted P-wave terminal force in V1, an electrocardiographic marker for atrial cardiopathy, was inversely associated with large-artery stroke. Conclusions: Available genetic data do not support substantial effects of cardiac traits on the risk of stroke beyond known clinical risk factors. Our findings highlight the need to carefully control for confounding and other potential biases in studies examining candidate cardiac risk factors for stroke.