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Scientific reports · 2024

Integrated analysis of single-cell RNA sequencing and bulk transcriptome data identifies a pyroptosis-associated diagnostic model for Parkinson's disease.

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Wang Lin, Qin Yidan, Song Jia, Xu Jing, Quan Wei, Su Hang, Zeng Huibin, Zhang Jian, Li Jia, Chen Jiajun

Аннотация

Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by an insidious onset. Despite the emphasis on motor symptom-based diagnosis, there remains an unmet clinical need for effective diagnostic approaches during the prodromal phase of PD. Recent advances in single-cell RNA sequencing (scRNA-seq) and bulk transcriptomic analyses of PD patients open avenues for identifying potential diagnostic biomarkers. A comprehensive cell trajectory analysis was conducted using scRNA-seq datasets to identify gene expressions associated with the cellular transition from healthy to PD-associated states. Integration of scRNA-seq datasets with weighted gene co-expression network analysis (WGCNA) allowed extraction of pyroptosis-associated differentially expressed genes (PDEGs). Using LASSO logistic regression, support vector machine recursive feature elimination (SVM-RFE) and random forest methods, we developed a diagnostic model centred on PDEGs. In addition, immunoinfiltration, inflammatory signalling pathways and intercellular communication were detected by scRNA-seq analyses. In PD patients, the number of cells including metencephalic-like cells, excitatory neurons, inhibitory neurons and MHB-like cells was significantly reduced, whereas the proportion of astrocytes and microglia, immunoinfiltration and inflammatory signalling pathways were upregulated compared to healthy individuals. Using scRNA-seq and WGCNA analyses, two pyroptosis-related diagnostic genes, POLR2K and TIMM8B, were identified and a diagnostic model based on them was constructed, which showed promising performance upon validation. This study established a pyroptosis-related diagnostic model for PD through the analyses of scRNA-seq combined with bulk transcriptome data, which improved the understanding of the role of PDEGs in PD and provided new insights into the diagnostic strategies for this neurodegenerative disease.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты