Diagnostic Model for Alzheimer’s Disease Based on PANoptosis-Related Genes
Erdong Zhang, Fengqiu Dai
Abstract
BACKGROUND: The pathophysiology of Alzheimer's disease (AD) involves the interplay of three different processes: pyroptosis, apoptosis, and necroptosis. OBJECTIVE: To explore role of PANoptosis, a novel pro-inflammatory programmed cell death pathway, in AD patients. METHODS: We performed a consensus clustering analysis to identify distinct transcriptional profiles in the samples using the R package "ConsensusClusterPlus". The PANoptosis key genes were obtained by crossing the WGCNA brown module and differentially expressed PANoptosis genes. We accomplished regression analyses using the LASSO-Cox method, combined with pathological status and gene expression data. At the same time, we also constructed PANscore system. The expression of PANoptosis hub genes were validated by qRT-PCR in AD transgenic mice. RESULTS: Our study utilized tissue expression profile data from AD patients to construct three distinct PANoptosis patterns, each with unique molecular and clinical characteristics. We have created a risk scoring system called PANscore, which can analyze patterns specific for each AD patient. Additionally, we observed significantly lower levels of follicular helper T (Tfh) cells in the high PANscore and AD patients. Further analysis revealed a significant negative correlation of Tfh with GSDMD and MLKL. CONCLUSIONS: These findings provide a roadmap for personalized patient stratification, enabling clinicians to develop personalized treatment plans for AD patients and advance the field of precision medicine.