Identification of Gene Signatures and Molecular Mechanisms for Diagnosing Parkinson's Disease and Nonalcoholic Fatty Liver Disease Using Machine Learning.

IF 2.2 4区 医学 Q3 CLINICAL NEUROLOGY
Parkinson's Disease Pub Date : 2026-05-26 eCollection Date: 2026-01-01 DOI:10.1155/padi/8731032
Xuan Chen, Yulin Wu, Yonglai Zhang, Yuli Hou
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引用次数: 0

Abstract

Background: Parkinson's disease (PD) is a prevalent neurodegenerative disease, whereas nonalcoholic fatty liver disease (NAFLD) is a common metabolic liver disorder. Growing evidence suggests that NAFLD may affect the central nervous system through the liver-brain axis, potentially contributing to PD, although the underlying molecular mechanisms remain unclear.

Methods: To identify differentially expressed genes (DEGs), transcriptomic data for NAFLD and PD were sourced from the GEO database. Key common candidate genes were screened using protein-protein interaction (PPI) networks, machine learning approaches (LASSO, neural networks, and random forest), and functional enrichment analyses, including GO, KEGG, GSEA, and GSVA. Immune infiltration, TF-miRNA regulatory networks, and single-cell RNA sequencing analyses were applied to investigate gene function, immune regulation, and cellular distribution. Candidate drugs were predicted using bioinformatic approaches and validated through molecular docking.

Results: CASP1, CCNA2, and INHBE were identified as three core common candidate genes that may be associated with NAFLD and PD. Involvement of these genes includes inflammatory responses, regulation of the cell cycle, metabolic pathways, and immune microenvironment remodeling. The analysis of the TF-miRNA network suggested possible regulation by transcription factors CEBPB, BRD4, FOS, and miRNAs such as hsa-miR-29b-1-5p and hsa-miR-128-3p. Drug prediction and molecular docking identified ethinyl estradiol, mesalamine, and seliciclib as candidate therapeutics, showing strong binding affinity to the core targets.

Conclusion: This study offers a comprehensive elucidation of the molecular ties between NAFLD and PD. The identified core genes and candidate drugs offer theoretical support for potential candidate biomarkers and therapeutic targets in comorbid NAFLD and PD.

利用机器学习识别帕金森病和非酒精性脂肪性肝病的基因特征和分子机制。
背景:帕金森病(PD)是一种常见的神经退行性疾病,而非酒精性脂肪性肝病(NAFLD)是一种常见的代谢性肝脏疾病。越来越多的证据表明NAFLD可能通过肝-脑轴影响中枢神经系统,可能导致PD,尽管其潜在的分子机制尚不清楚。方法:为了鉴定差异表达基因(DEGs), NAFLD和PD的转录组学数据来自GEO数据库。使用蛋白相互作用(PPI)网络、机器学习方法(LASSO、神经网络和随机森林)和功能富集分析(包括GO、KEGG、GSEA和GSVA)筛选关键的共同候选基因。应用免疫浸润、TF-miRNA调节网络和单细胞RNA测序分析来研究基因功能、免疫调节和细胞分布。利用生物信息学方法预测候选药物,并通过分子对接进行验证。结果:CASP1、CCNA2和INHBE被确定为可能与NAFLD和PD相关的三个核心共同候选基因。这些基因的参与包括炎症反应、细胞周期调节、代谢途径和免疫微环境重塑。对TF-miRNA网络的分析表明,可能受到转录因子CEBPB、BRD4、FOS和mirna如hsa-miR-29b-1-5p和hsa-miR-128-3p的调控。药物预测和分子对接发现乙炔雌二醇、美沙拉胺和seliciclib为候选治疗药物,与核心靶点具有较强的结合亲和力。结论:本研究全面阐明了NAFLD与PD之间的分子联系。鉴定出的核心基因和候选药物为NAFLD和PD共病的潜在候选生物标志物和治疗靶点提供了理论支持。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Parkinson's Disease
Parkinson's Disease CLINICAL NEUROLOGY-
CiteScore
5.80
自引率
3.10%
发文量
0
审稿时长
18 weeks
期刊介绍: Parkinson’s Disease is a peer-reviewed, Open Access journal that publishes original research articles, review articles, and clinical studies related to the epidemiology, etiology, pathogenesis, genetics, cellular, molecular and neurophysiology, as well as the diagnosis and treatment of Parkinson’s disease.
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