Identification of causally linked blood biomarkers for Alzheimer's disease via reverse transcriptome-wide Mendelian randomization

BackgroundAlzheimer's disease (AD) is a progressive neurodegenerative disorder with poorly understood molecular mechanisms and limited early detection biomarkers.ObjectiveTo identify genes causally associated with AD risk using reverse transcriptome-wide Mendelian randomization (revTWMR) and bulk RNA-sequencing (RNA-seq).MethodsWe analyzed publicly available RNA-seq data from peripheral blood samples of patients with clinically diagnosed AD and cognitively normal controls, obtained from the GEO database. Differential expression analysis was performed to identify differentially expressed genes (DEGs). We used revTWMR by integrating genome-wide association study (GWAS) summary statistics with expression quantitative trait loci (eQTL) data to infer causal relationships between gene expression and AD risk.ResultsUsing RNA-seq data from peripheral blood samples of AD patients and cognitively normal controls, we identified 126 DEGs. Through revTWMR analysis, we narrowed down to 91 genes with significant causal associations with AD, and further prioritized 5 genes with strong causal effects (|α| ≥ 0.8). Among these, PSMA6, CD19, and CMTM6 have potential roles in AD pathogenesis and may serve as promising blood-based biomarkers for early detection and therapeutic targeting.ConclusionsOur findings highlight the utility of revTWMR in identifying causally relevant genes in AD and suggest several blood-based candidate biomarkers for early detection and therapeutic development. This integrative approach provides novel insights into the molecular underpinnings of AD.