Identification of Autophagy-Related Biomarkers in Ischemic Stroke

Abstract

Objective: This study utilizes bioinformatics technology to screen and predict potential diagnostic autophagy related biomarkers in CIS. Methods: By analyzing genes in the GEO dataset GSE16561 and the autophagy database HADb, differentially expressed genes (DEGs) related to autophagy in CIS were identified. GO and KEGG enriched and analyzed these autophagy related DEGs. Subsequently, module analysis was conducted using LASSO and SVM-REF algorithms, and finally, the diagnostic value of autophagy related biomarkers in CIS was evaluated through subject operating characteristic curve (ROC) univariate analysis. Results: After intersection of differential genes and autophagy gene data, a total of 31 DEGs related to autophagy were identified. GO and KEGG analysis showed that these autophagy related DEGs are mainly enriched in the reactions of autophagy, apoptosis, inflammation, and aging. They have molecular functions such as binding to cadherin and cell adhesion molecules, and are involved in utilizing autophagy mechanisms, biological processes of apoptosis, and cellular components of lysosomes, whole membranes, cytoplasmic colloids, and cytoplasmic vesicles. And it is related to the FoxO signaling pathway, NOD like receptor signaling pathway, chemokine signaling pathway, PI3K Akt signaling pathway, IL-17 signaling pathway, etc. In addition, LASSO and SVM-REF identified 10 autophagy related biomarkers, namely CASP4, FOXO3, HSPA8, EIF2AK2, PRKCQ, GAA, NLRC4, TNFSF10, CXCR4, RAB1A. ROC univariate analysis showed that CASP4, FOXO3, EIF2AK2, NLRC4, and CXCR4 have good expression and diagnostic value in CIS. Conclusion: CASP4, FOXO3, EIF2AK2, NLRC4, and CXCR4 genes may be potential autophagy related biomarkers for the diagnosis and treatment of CIS, and provide some evidence for the important role of autophagy in CIS.