AUTHOR=Wang Xin , Wu Zelin , Wei Shaoli , Zhao Xinran , Lin Juan , Zhao Fang , Liu Xiaolei 

TITLE=Integrated transcriptomic and single-cell RNA sequencing identifies lysosomal ion channel genes as potential biomarkers for Alzheimer’s disease

JOURNAL=Frontiers in Genetics

VOLUME=Volume 16 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2025.1676565

DOI=10.3389/fgene.2025.1676565

ISSN=1664-8021

ABSTRACT=Previous research has highlighted lysosomal ion channel-related genes (LICRGs) as promising therapeutic targets for neurodegenerative diseases. This study aimed to identify and analyze LICRG-associated biomarkers for Alzheimer’s disease (AD), elucidating their underlying biological mechanisms. Three datasets (GSE63061, GSE63060, GSE181279) were analyzed. In GSE63061, intersecting genes were identified by integrating differentially expressed genes (DEGs) from differential expression analysis with key module genes from Weighted Gene Co-expression Network Analysis (WGCNA). Candidate biomarkers were then selected using the MCODE plugin for PPI analysis (top 30 genes), two machine learning approaches, and cross-validation of gene expression profiles in GSE63061 and GSE63060. Single-cell RNA sequencing (scRNA-seq) analysis of GSE181279 identified key biomarkers and cell populations, followed by pseudo-temporal analysis of these cells. Nomogram construction, functional enrichment analysis, immune infiltration assessment, and RT-qPCR analysis were subsequently performed. scRNA-seq analysis revealed that SRP14, EIF3E, and COX7C were prominently expressed across most cell types, particularly in CD4+ T cells, which were identified as key cells in AD. Pseudo-temporal analysis indicated that CD4+ T cells from control subjects primarily resided in early differentiation stages, whereas those from patients with AD were predominantly found in later stages. The reduced expression of these biomarkers in AD CD4+ T cells was consistent with transcriptomic data and further validated by RT-qPCR. A nomogram incorporating these biomarkers demonstrated strong predictive power for AD risk. Functional analysis linked the biomarkers to pathways such as “ribosome” and “oxidative phosphorylation.” Immune infiltration analysis revealed 23 differentially abundant immune cell types, with significant correlations between all three biomarkers and memory CD4+ T cells, mesangial cells, and other immune cell types. This study identified SRP14, EIF3E, and COX7C as novel biomarkers, underscoring CD4+ T cells as pivotal in AD pathogenesis. These findings offer new mechanistic insights and potential therapeutic strategies for AD.