Discovery and Validation of Key Biomarkers Based on Immune Infiltrates in Alzheimer’s Disease - Liu, Zhuohang; Li, Hang; Pan, Shuyi (Frontiers in Genetics, 2021)
Background: As the most common neurodegenerative disease, Alzheimer Disease (AD) leads to progressive loss of cognition and memory. Presently, the underlying pathogenic genes of AD patients remain elusive and effective disease-modifying therapy is not available. This study explored novel biomarkers that can affect diagnosis and treatment in AD based on immune infiltration. Methods：The gene expression profiles of 139 AD cases and 134 normal controls were obtained from the NCBI GEO public database. We applied the computational method CIBERSORT to bulk gene expression profiles of AD to quantify 22 subsets of immune cells. Besides, based on the use of the Least Absolute Shrinkage Selection Operator (LASSO), this study also applied SVM-RFE analysis to screen key genes. GO-based semantic similarity and Logistic regression model analyses were applied to explore hub genes further. Results: There was a remarkable significance in the infiltration of immune cells between the subgroups. The proportions for Monocytes, M0 Macrophages and Dendritic cells in AD group were significantly higher than those in the normal group, while the proportion of some cells was lower than that of the normal group, such as NK cells resting, T cells CD4 naive, T cell CD4 memory activation, eosinophils. Additionally, 7 genes (ABCA2, CREBRF, CD72, CETN2, KCNG1, NDUFA2, RPL36AL) were identified as hub genes. Then we performed the analysis of immune factor correlation, Gene set enrichment analysis (GSEA) and GO based on 7 hub genes. The AUC of ROC prediction model in test and validation sets were 0.845 and 0.839, respectively. Eventually, the mRNA expression analysis of ABCA2, NDUFA2, CREBRF and CD72 revealed significant differences among 7 hub genes and then was confirmed by RT-PCR. Conclusion: A model based on immune cell infiltration might be used to forecast the AD patients diagnosis, and it provided a new perspective for AD treatment targets.