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基于机器学习和实验验证预测神经性疼痛中与细胞焦亡相关的诊断生物标志物

Predicting Diagnostic Biomarkers Associated with Pyroptosis in Neuropathic Pain Based on Machine Learning and Experimental Validation.

作者信息

Tian Sheng, Zheng Heqing, Wu Wei, Wu Lanxiang

机构信息

Department of Neurology, the Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330006, People's Republic of China.

Institute of Neuroscience, Nanchang University, Nanchang, 330006, People's Republic of China.

出版信息

J Inflamm Res. 2024 Feb 20;17:1121-1145. doi: 10.2147/JIR.S445382. eCollection 2024.

DOI:10.2147/JIR.S445382
PMID:38406324
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10893895/
Abstract

PURPOSE

Previous studies have shown that pyroptosis plays a vital role in the progress of neuropathic pain (NP), but the molecular mechanisms have not been fully elucidated. The aim of this study was to identify crucial pyroptosis-related genes (PRGs) in NP.

METHODS

We identified pyroptosis-related differentially expressed genes (PRDEGs) in NP by machine learning analysis of the GSE24982 and GSE60670 datasets. Furthermore, these PRDEGs were subjected to Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, Gene Set Enrichment Analysis (GSEA) and Friends analysis, respectively. Meanwhile, receiver operator characteristic (ROC) analysis was performed to assess the diagnostic value of PRDEGs in NP. Finally, we performed immune infiltration analysis of key PRDEGs using CIBERSORTR R package.

RESULTS

We found that 5 PRDEGs by least absolute shrinkage and selection operator (LASSO) regression and random forest and verified by RT-qPCR. GO, KEGG and GSEA revealed that these PRDEGs were mainly enriched in regulation of neuron death, IL-4 signaling, IL-23 pathway, and NF-κB pathway. ROC analysis revealed that most of the PRDEGs performed well in diagnosing NP. We also revealed transcription factors, miRNA regulatory networks and drug interaction networks of PRDEGs. For immune infiltration analysis, PRDEGs were mainly correlated with dendritic cells, monocytes and follicular T helper cells, suggested that it might be involved in the regulation of neuroimmune-related signaling.

CONCLUSION

A total of five PRDEGs were can be employed as NP biomarkers, particularly Tlr4, Il1b and Casp8, and provide additional evidence for a vital role of pyroptosis in NP.

摘要

目的

先前的研究表明，细胞焦亡在神经性疼痛（NP）的进展中起重要作用，但其分子机制尚未完全阐明。本研究的目的是鉴定NP中关键的细胞焦亡相关基因（PRG）。

方法

通过对GSE24982和GSE60670数据集进行机器学习分析，我们鉴定了NP中与细胞焦亡相关的差异表达基因（PRDEG）。此外，这些PRDEG分别进行了基因本体（GO）、京都基因与基因组百科全书（KEGG）富集分析、基因集富集分析（GSEA）和Friend分析。同时，进行了受试者工作特征（ROC）分析，以评估PRDEG在NP中的诊断价值。最后，我们使用CIBERSORTR R包对关键PRDEG进行了免疫浸润分析。

结果

我们通过最小绝对收缩和选择算子（LASSO）回归和随机森林发现了5个PRDEG，并通过RT-qPCR进行了验证。GO、KEGG和GSEA显示，这些PRDEG主要富集在神经元死亡调节、IL-4信号传导、IL-23途径和NF-κB途径中。ROC分析显示，大多数PRDEG在诊断NP方面表现良好。我们还揭示了PRDEG的转录因子、miRNA调控网络和药物相互作用网络。对于免疫浸润分析，PRDEG主要与树突状细胞、单核细胞和滤泡辅助性T细胞相关，表明其可能参与神经免疫相关信号的调节。

结论

共有5个PRDEG可作为NP的生物标志物，特别是Tlr4、Il1b和Casp8，并为细胞焦亡在NP中的重要作用提供了额外证据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7bd/10893895/245f8ac4650a/JIR-17-1121-g0012.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d7bd/10893895/322d8ec20f4e/JIR-17-1121-g0008.jpg
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