Identification of the putative causal risk factors and biomarkers of stroke using large-scale genome-wide studies

Abstract

AbstractStroke is a complex neurological disorder, and the risk factors and genetic biomarkers associated with stroke development are not completely understood. This study aims to identify putative causal traits and their biomarkers that influence the risk of stroke. Here the latent causal variable (LCV) method has been used to investigate the potential causal genetic relationships between large-scale genome-wide association studies (GWAS) data of 1504 complex traits from UK Biobank and stroke. Generalised Mendelian randomisation (GSMR) method has also been further used to examine causal inference. These analyses suggest 14 causal traits associated with stroke risk (|GCP|> 0.60; FDR < 0.05), including atrial fibrillation, deep venous thrombosis, gamma-glutamyl transferase, and platelet crit. Gene-based analysis has revealed shared genes, providing novel insights into the genetic biomarkers of the causal traits on stroke risk. Functional enrichment analyses of the shared genes have provided biological pathways underlying biological mechanisms to stroke risk, including “oxidative damage”, “platelet activation”, “cell aging”, and others. This study provides causal evidence of cardiovascular, metabolic, and blood clot-related traits increasing stroke risk. The identified shared gene biomarkers provide valuable insights into the shared genetic biomarkers and underlying mechanisms linking causal traits to stroke risk.