1. Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration of Ministry of Education, Orthopedic Department of Tongji Hospital, Tongji University School of Medicine, Shanghai, China.
2. Stem Cell Translational Research Center, Tongji Hospital, Tongji University School of Medicine, Shanghai, China.
Alzheimer's disease (AD) is an age-related neurodegenerative disorder characterized by cognitive impairment and memory loss, for which there is no effective cure to date. In the past several years, numerous studies have shown that increased inflammation in AD is a major cause of cognitive impairment. This study aimed to reveal 22 kinds of peripheral immune cell types and key genes associated with AD. The prefrontal cortex transcriptomic data from Gene Expression Omnibus (GEO) database were collected, and CIBERSORT was used to assess the composition of 22 kinds of immune cells in all samples. Weighted gene co-expression network analysis (WGCNA) was used to construct gene co-expression networks and identified candidate module genes associated with AD. The least absolute shrinkage and selection operator (LASSO) and random forest (RF) models were constructed to analyze candidate module genes, which were selected from the result of WGCNA. The results showed that the immune infiltration in the prefrontal cortex of AD patients was different from healthy samples. Of all 22 kinds of immune cells, M1 macrophages were the most relevant cell type to AD. We revealed 10 key genes associated with AD and M1 macrophages by LASSO and RF analysis, including ARMCX5, EDN3, GPR174, MRPL23, RAET1E, ROD1, TRAF1, WNT7B, OR4K2 and ZNF543. We verified these 10 genes by logistic regression and k-fold cross-validation. We also validated the key genes in an independent dataset, and found GPR174, TRAF1, ROD1, RAET1E, OR4K2, MRPL23, ARMCX5 and EDN3 were significantly different between the AD and healthy controls. Moreover, in the 5XFAD transgenic mice, the differential expression trends of Wnt7b, Gpr174, Ptbp3, Mrpl23, Armcx5 and Raet1e are consistent with them in independent dataset. Our results provided potential therapeutic targets for AD patients.
Keywords: Alzheimer's Disease, immune infiltration, bioinformatics, key genes