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Integrated bioinformatics analysis of the shared molecular mechanisms between Parkinson's disease and COVID-19.

Overview

Authors: Yang Su1, Hui Ma1, Jiayuan Niu1, Dongnan Hou1, Liya Li1
ORCID iDs: Dongnan Hou, Liya Li
  1. Department of Anesthesiology, The Second Affiliated Hospital of Dalian Medical University, Dalian, China
Institutions: Dalian Medical University (China)
Journal: mSphere, volume 11, issue 4, pages e00908-25
Dates: received 20 December 2025; accepted 4 March 2026; published online 3 April 2026; in print April 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.1128/msphere.00908-25 · PMID 41930954 · PMCID PMC13123704 · OpenAlex W7148821760
Open access: gold, a free copy (OpenAlex)
Status: data only
Categories: genetics / omics (modality), human (organism), other condition (population), Parkinson's (population), cellular / molecular (subfield)
Methods: Smoothing, state filtering, decompositions, Preprocessing, Statistics
Keywords: Parkinson’s disease, COVID-19, CHI3L1, scRNA-seq, cell-to-cell communication
MeSH: Computational Biology*, COVID-19*, Parkinson Disease*, Astrocytes, Brain, Cell Communication, Chitinase-3-Like Protein 1, Dopaminergic Neurons, Gene Expression Profiling, Gene Ontology, Humans, Protein Interaction Maps, SARS-CoV-2, Single-Cell Analysis, Single-Cell Gene Expression Analysis (* major topic)
Topic: Long-Term Effects of COVID-19 (Neurology, Medicine), according to OpenAlex
Funding: National Natural Science Foundation of China (82401743); Natural Science Foundation of Liaoning Province (2025-BS-0661, 2025-MSLH-179); Dalian "1+X" program of China (2024LCJSYL30)
Citations: not cited yet (Europe PMC); 47 references in the paper

Abstract

To investigate the shared molecular mechanisms between Parkinson’s disease (PD) and COVID-19 through integrated bioinformatics analysis and single-cell RNA sequencing (scRNA-seq). We conducted a comprehensive analysis of bulk RNA-seq data from publicly available databases, along with scRNA-seq data from brain tissues of COVID-19 patients. Differential expression analysis identified 725 differentially expressed genes (DEGs) in COVID-19 and 633 in PD samples. A total of 77 overlapping DEGs were identified, highlighting common pathways associated with neuroinflammation and dopaminergic neuron dysfunction. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses revealed significant enrichment in inflammation-related pathways. The protein-protein interaction network analysis identified CHI3L1 as a key gene linking PD and COVID-19. ScRNA-seq analysis revealed a significant increase in CHI3L1-expressing astrocytes in COVID-19 samples, indicating a potential mechanism by which COVID-19 may exacerbate PD symptoms. Furthermore, cell-cell communication analysis revealed enhanced interactions between astrocytes and microglia, excitatory neurons, or oligodendrocytes through signaling molecules such as phosphoprotein 1, CADM1, NCAM1, NRG, and NRXN1, suggesting that astrocytes play a central role in regulating neuronal excitability, synaptic plasticity, and immune responses in the context of COVID-19. These findings suggest a complex interplay between COVID-19 and PD, emphasizing the need for further investigation into the shared pathogenic mechanisms and potential therapeutic targets.

IMPORTANCE: This study demonstrates the critical role of neuroinflammation and dopaminergic neuron damage in the shared pathogenesis of COVID-19 and Parkinson’s disease. CHI3L1 emerges as a key target, highlighting its potential involvement in modulating neuroinflammatory pathways and synaptic plasticity. The functional significance of CHI3L1, along with its pathological relevance, warrants further investigation through larger studies. Additionally, the active intercellular communication among astrocytes, microglia, and excitatory neurons underscores the profound impact of COVID-19 on neural circuitry. Collectively, these results provide important insights into the mechanisms driving the neurodegenerative consequences of COVID-19, emphasizing the need for continued exploration of therapeutic interventions and the long-term neurological effects of viral infection.

Reproduced under the paper's license (CC BY), from the paper cited above.

Code

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Data

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Other data links

Data availability

The bulk-seq expression profile and relevant clinical data of PD and COVID-19 samples at various stages were collected from the Gene Expression Omnibus (GEO; https://www.ncbi.nlm.nih.gov/geo/) with accession numbers GSE184950 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE184950) and GSE182299 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE182299).

Reproduced under the paper's license (CC BY), from the paper cited above.

Versions

The history of this record: each version stored by the harvester or made by a correction of its authors or of the maintainers of its code, and what changed in its facts. The texts of the paper (its abstract, its availability statements) are not part of it; versions that changed only those are not listed.

Version 1, 28 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 5 authors, 5 keywords, 15 MeSH terms, 3 funders, 47 references.

Cite

This paper

Su, Y., Ma, H., Niu, J., Hou, D., & Li, L. (2026). Integrated bioinformatics analysis of the shared molecular mechanisms between Parkinson's disease and COVID-19. mSphere, 11(4), e00908-25. https://doi.org/10.1128/msphere.00908-25

BibTeX

@article{su2026integrated,
author = {Su, Yang and Ma, Hui and Niu, Jiayuan and Hou, Dongnan and Li, Liya},
title = {{Integrated bioinformatics analysis of the shared molecular mechanisms between Parkinson's disease and COVID-19}},
journal = {mSphere},
year = {2026},
month = apr,
volume = {11},
number = {4},
pages = {e00908--25},
publisher = {American Society for Microbiology (ASM)},
issn = {2379-5042},
doi = {10.1128/msphere.00908-25},
url = {https://doi.org/10.1128/msphere.00908-25},
pmid = {41930954},
pmcid = {PMC13123704}
}

RIS

TY - JOUR
AU - Su, Yang
AU - Ma, Hui
AU - Niu, Jiayuan
AU - Hou, Dongnan
AU - Li, Liya
TI - Integrated bioinformatics analysis of the shared molecular mechanisms between Parkinson's disease and COVID-19
T2 - mSphere
J2 - mSphere
PY - 2026
DA - 2026/04/03
VL - 11
IS - 4
SP - e00908
EP - 25
SN - 2379-5042
PB - American Society for Microbiology (ASM)
DO - 10.1128/msphere.00908-25
UR - https://doi.org/10.1128/msphere.00908-25
LA - en
ER -

CSL-JSON

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