Identification of Plasma Cell Subsets and Molecular Markers of Alzheimer's Disease Based on Single-Cell Weighted Gene Co-Expression Network Analysis, Mendelian Randomization Analysis and Clinical Validation.

Abstract

Introduction: Alzheimer's disease (AD) is a neurodegenerative disorder characterized by gene expression alterations and immune dysregulation.

Methods: In this study, we downloaded the GSE181279 single-cell dataset from the Gene Expression Omnibus (GEO) and applied bioinformatic analysis and clinical subject validation.

Results: After quality control and harmony integration, we identified 21 cell subsets, including T cells, B cells, plasma cells, and macrophages. Plasma cells were significantly elevated in AD patients, and six plasma cell subtypes were associated with AD. High-dimensional weighted gene co-expression network analysis (hdWGCNA) revealed two AD-related modules. Mendelian randomization identified RGS1 as a key risk gene (p = 0.0123). Immune infiltration analysis showed RGS1 negatively correlated with macrophages and positively with tumor-infiltrating lymphocytes. Functional enrichment indicated that RGS1 is involved in JAK-STAT, NF-κB, and Wnt-β-catenin signaling pathways, suggesting a role in immune regulation and neuroinflammation. Furthermore, validation in AD patients confirmed that RGS1 expression levels were higher than in controls (p < 0.01).

Discussion: This study identified the key gene RGS1 related to AD and explored multiple signaling pathways associated with it, which provided important clues for the research on AD-related inflammation, gut microbiota, stretch-gated ion channel, and the evaluation of AD therapeutic targets.

Clinical trial registration number: CTR20210477.