Identification and validation of biomarkers associated with mitochondrial dynamics dysfunction in Parkinson’s disease based on GEO datasets

Background Parkinson’s disease (PD), the second most prevalent neurodegenerative disorder, is characterized by an unclear etiology and a lack of specific early diagnostic biomarkers. This study investigated novel biomarkers associated with mitochondrial dynamics (MD) dysfunction in PD. Methods Transcriptomic data from the Gene Expression Omnibus database (training set: GSE6613, n = 72; validation set: GSE99039, n = 438) and 23 MD-related genes (MDRGs) were integrated. Differentially expressed genes were screened using the limma package. Three machine learning algorithms (random forest, support vector machine, and generalized linear model) were employed to construct diagnostic models. Feature importance analysis identified key candidate biomarkers, which were preliminarily validated in clinical samples via reverse transcription quantitative PCR (RT-qPCR). Functional enrichment, immune infiltration, and compound prediction analyses were subsequently performed. Results Cysteinyl leukotriene receptor 2 ( CYSLTR2 ) and alpha‑tocopherol transfer protein‑like gene ( TTPAL ) were identified as MDRG score-correlated biomarkers. In the validation set, CYSLTR2 was significantly downregulated (log 2 FC = −1.25, P < 0.001) and participated in neuroactive ligand–receptor interactions. Conversely, TTPAL was significantly upregulated (log 2 FC = 1.52, P < 0.001) and associated with the pathogenic Escherichia coli infection pathway. Immune analysis revealed six differentially infiltrated immune cell types. Notably, TTPAL expression was positively correlated with keratinocytes (cor = 0.30, P = 0.031). Four potential therapeutic compounds were predicted. RT-qPCR suggested the downregulation of CYSLTR2 and upregulation of TTPAL in patients with PD (P < 0.0001). Conclusion This study identified CYSLTR2 and TTPAL as novel candidate biomarkers associated with MD dysfunction in PD, providing novel targets for mechanistic investigation and therapeutic exploration.

Authors

Institutions

Publication Details

Journal
PLoS ONE
Published
2026-11-04
DOI
https://doi.org/10.1371/journal.pone.0362081
Primary Topic
Parkinson's Disease Mechanisms and Treatments
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Identification and validation of biomarkers associated with mitochondrial dynamics dysfunction in Parkinson’s disease based on GEO datasets

Dawei Gong, Jie Chen, Yi Zhao, Guanyu Li et al.
PLoS ONE
Parkinson's Disease Mechanisms and Treatments
article

Identification and validation of biomarkers associated with mitochondrial dynamics dysfunction in Parkinson’s disease based on GEO datasets

Dawei Gong, Jie Chen, Yi Zhao, Guanyu Li, Weixiao Wang, Ming Li, Bo Zhang
article en

Abstract

Background Parkinson’s disease (PD), the second most prevalent neurodegenerative disorder, is characterized by an unclear etiology and a lack of specific early diagnostic biomarkers. This study investigated novel biomarkers associated with mitochondrial dynamics (MD) dysfunction in PD. Methods Transcriptomic data from the Gene Expression Omnibus database (training set: GSE6613, n = 72; validation set: GSE99039, n = 438) and 23 MD-related genes (MDRGs) were integrated. Differentially expressed genes were screened using the limma package. Three machine learning algorithms (random forest, support vector machine, and generalized linear model) were employed to construct diagnostic models. Feature importance analysis identified key candidate biomarkers, which were preliminarily validated in clinical samples via reverse transcription quantitative PCR (RT-qPCR). Functional enrichment, immune infiltration, and compound prediction analyses were subsequently performed. Results Cysteinyl leukotriene receptor 2 ( CYSLTR2 ) and alpha‑tocopherol transfer protein‑like gene ( TTPAL ) were identified as MDRG score-correlated biomarkers. In the validation set, CYSLTR2 was significantly downregulated (log 2 FC = −1.25, P < 0.001) and participated in neuroactive ligand–receptor interactions. Conversely, TTPAL was significantly upregulated (log 2 FC = 1.52, P < 0.001) and associated with the pathogenic Escherichia coli infection pathway. Immune analysis revealed six differentially infiltrated immune cell types. Notably, TTPAL expression was positively correlated with keratinocytes (cor = 0.30, P = 0.031). Four potential therapeutic compounds were predicted. RT-qPCR suggested the downregulation of CYSLTR2 and upregulation of TTPAL in patients with PD (P < 0.0001). Conclusion This study identified CYSLTR2 and TTPAL as novel candidate biomarkers associated with MD dysfunction in PD, providing novel targets for mechanistic investigation and therapeutic exploration.

PLoS ONEVol. 21(11)
Nanjing University of Chinese Medicine (CN), Nanjing Medical University (CN)
Openalex Percentile: Top 15%
Parkinson's Disease Mechanisms and Treatments
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon