Identification of Biomarkers Related to M2 Macrophage Infiltration in Alzheimer's Disease

Cells. 2022 Aug 1;11(15):2365. doi: 10.3390/cells11152365.

Abstract

Many studies have demonstrated that neuroinflammation contributes to the onset and development of Alzheimer's disease (AD). The infiltration of immune cells in the brain was observed in AD. The purpose of the present study was to verify potential mechanisms and screen out biomarkers related to immune infiltration in AD. We collected the expression profiling datasets of AD patients and healthy donors from the NCBI's Gene Expression Omnibus (GEO) database. We confirmed that immune-related mechanisms were involved in AD using differentially expressed genes analysis and functional enrichment analysis. We then found that M2 macrophage infiltration was most positively correlated with AD according to the CIBERSORT algorithm and a weighted gene co-expression network analysis (WGCNA). TLR2, FCGR2A, ITGB2, NCKAP1L and CYBA were identified as hub genes correlated with M2 macrophage infiltration in AD. Furthermore, the expression levels of these hub genes were positively correlated with Aβ42 and β-secretase activity. A diagnostic model of these hub genes was constructed, which showed a high area under the curve (AUC) value in both the derivation and validation cohorts. Overall, our work further expanded our understanding of the immunological mechanisms of AD and provided new insights into therapeutic strategies in AD.

Keywords: Alzheimer’s disease; M2 macrophages; immune infiltration; toll-like receptor 2.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Alzheimer Disease* / genetics
  • Alzheimer Disease* / metabolism
  • Biomarkers / metabolism
  • Gene Expression Profiling
  • Gene Regulatory Networks
  • Humans
  • Macrophages / metabolism
  • Membrane Proteins / genetics

Substances

  • Biomarkers
  • Membrane Proteins
  • NCKAP1L protein, human

Grants and funding

This research was funded by Zhejiang Provincial Natural Science Foundation of China (grant number LQ21H090005) and the National Natural Science Foundation of China (grant number 81902604).