Identification of putative causal relationship between stroke and 1504 complex traits using large-scale phenome-wide screening

Abstract

Stroke is the second leading cause of death and the third leading cause of long-term disability in the world. This study aimed to explore the novel putative causal genetic relationship of stroke with hundreds of complex traits by leveraging genetic data. We used genome-wide association studies (GWAS) data and the latent causal variable method to identify potential causal relationships between stroke and 1,504 complex traits of the UK biobank. We found that 262 traits were genetically correlated with stroke risk at a false discovery rate (FDR <0.05). Of those correlated traits, 28 showed robust evidence of partial genetic causality (GCP) with stroke (|GCP|> 0.60; FDR < 0.05). Our results showed that some conditions, including atrial fibrillation, pulmonary embolism, blood clots in the lung, platelet crit, self-reported deep venous thrombosis, weight gain after depression, and the use of some medications such as insulin, pioglitazone, and gliclazide were inferred to increase stroke risk. On the other hand, greater levels of testosterone, apolipoprotein A, SHBG, and HDL cholesterol decrease the risk of stroke. Also, our results suggest that genetic susceptibility to stroke raises the risk of neck and chest pain and loose teeth. Finally, our findings suggest that cardiac vascular disease, blood clot in lung, deep venous thrombosis, and certain anti-diabetic medications could have a causal role in increasing the risk of stroke, which could be used as novel testable hypotheses for future epidemiological studies.