Exploring Genetic Associations of Three Types of Risk Factors with Ischemic Stroke: An Integrated Bioinformatics Study
Liu, Y.; Wang, W.; Cui, X.; Xie, Y.
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BackgroundIschemic stroke (IS) is a primary cause of disability and mortality globally. More and more reports suggest a strong association between blood pressure, blood glucose, and blood lipids and their metabolic products with IS. MethodsWe extracted the genetic tools of blood pressure, blood glucose, and blood lipids and their metabolites as instrumental variables, which were then paired with GWAS data on IS and a Mendelian randomization (MR) analysis was performed to assess the effect of these exposures on the disease. Following the positive results, colocalization analysis was performed to identify shared genes associated with exposures and IS. We then performed differential expression analysis using the GEO dataset to identify the differentially expressed associated genes (DEAGs) from associated shared genes. Additional analyzes were performed on these DEAGs to obtain their importance scores using four machine learning models. A nomogram was created using genes with high importance scores to predict the level of risk assessment between DEAGs and IS. ResultsThere is a positive correlation between blood pressure, blood glucose and the risk of IS onset, while blood lipids and their metabolic products are positively or negatively correlated with the risk. There are 64 shared genes of blood pressure, blood lipids and their metabolic products with IS. Thirteen DEAGs were obtained, and among which FURIN, MAN2A2, HDDC3, ALDH2, and TOMM40 were identified as feature genes for creating the nomogram which can quantitatively predict the risk of IS onset with the expression of these feature genes. By cluster analysis, we found that DEAGs expression underlying immune inflammation, angiogenesis and development, lipid metabolism, etc. ConclusionThis study suggests a significant association between blood pressure, blood glucose, and blood lipids and their metabolic products with IS, and predicts that these exposures mainly regulate the occurrence, development, and prognosis of IS through mechanisms such as DNA repair, DNA methylation, mitochondrial repair, apoptosis, autophagy, etc.
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