Affiliations: [a] State Key Laboratory of Functions and Applications of Medicinal Plants, Guizhou Medical University, Guiyang, Guizhou, China
| [b] Key Laboratory of Optimal Utilization of Natural Medicinal Resources, Guizhou Medical University, Guiyang, Guizhou, China
| [c] Department of Anatomy, School of Basic Medical Sciences, Guizhou Medical University, Guiyang, China
Correspondence:
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Correspondence to: Erdong Zhang, State Key Laboratory of Functions and Applications of Medicinal Plants, Guizhou Medical University, Guiyang, Guizhou, China. E-mail: [email protected] and Fengqiu Dai, Department of Anatomy, School of Basic Medical Sciences, Guizhou Medical University, Guiyang, China. E-mail: [email protected].
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.
