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Meta-Analysis
. 2024 Oct 1;14(1):22838.
doi: 10.1038/s41598-024-73535-0.

Hepatitis C virus infection and Parkinson's disease: insights from a joint sex-stratified BioOptimatics meta-analysis

Affiliations
Meta-Analysis

Hepatitis C virus infection and Parkinson's disease: insights from a joint sex-stratified BioOptimatics meta-analysis

Isis Narváez-Bandera et al. Sci Rep. .

Abstract

Hepatitis C virus (HCV) infection poses a significant public health challenge and often leads to long-term health complications and even death. Parkinson's disease (PD) is a progressive neurodegenerative disorder with a proposed viral etiology. HCV infection and PD have been previously suggested to be related. This work aimed to identify potential biomarkers and pathways that may play a role in the joint development of PD and HCV infection. Using BioOptimatics-bioinformatics driven by mathematical global optimization-, 22 publicly available microarray and RNAseq datasets for both diseases were analyzed, focusing on sex-specific differences. Our results revealed that 19 genes, including MT1H, MYOM2, and RPL18, exhibited significant changes in expression in both diseases. Pathway and network analyses stratified by sex indicated that these gene expression changes were enriched in processes related to immune response regulation in females and immune cell activation in males. These findings suggest a potential link between HCV infection and PD, highlighting the importance of further investigation into the underlying mechanisms and potential therapeutic targets involved.

Keywords: Flavivirus; Hepatitis C Virus; Meta-analysis; Microarray gene expression datasets; Parkinson’s disease; RNA sequence analysis.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Case study design of MCO analysis. MCO was used to analyze the datasets in four steps: (1) individual dataset analysis, (2) individual analysis stratified by sex, (3) meta-analysis by sex within each condition, and (4) meta-analysis by sex between PD and HCV conditions.
Fig. 2
Fig. 2
Individual analysis by sex. This resulted in 362 genes of interest for PD and 131 genes for HCV. The expression of these genes changed according to the condition but not by sex.
Fig. 3
Fig. 3
Summary of genes of interest from three cases of MCO analysis. Individual analysis, analysis by sex, and meta-analysis within conditions. MT1H, MYOM2, and S100A12 were the most common genes associated with PD and HCV infection.
Fig. 4
Fig. 4
Common genes from the between meta-analysis. A total of 98 genes were found in the joint analysis, ten of which were found to be shared by the two meta-analyses.
Fig. 5
Fig. 5
The results of the MST meta-analysis within conditions after expression changes present only in one sex were excluded.
Fig. 6
Fig. 6
MST Female_4D meta-analysis between PD and HCV from the GSE18838, GSE57475, GSE99039, and GSE119117 female subsets. Four common groups of genes were identified between (a) the MST and (b) STRING. In each figure, each individual gene is identified with a circular node. Four common groups of genes were identified and are shown in orange, green, blue and dark purple. Genes in each common group are identified with an arrow.
Fig. 7
Fig. 7
MST Male_5D meta-analysis between PD and HCV from the GSE18838, GSE57475, GSE99039, GSE38542, and GSE119117 male subsets. Three common groups of genes were identified between (a) the MST and (b) STRING. In each figure, each individual gene is identified with a circular node. Three common groups of genes were identified and are shown in orange, green and dark purple. The genes analyzed in each common group are identified with an arrow.
Fig. 8
Fig. 8
Biological process enrichment according to Gene Ontology analysis for genes of interest from (a) MCO 4D females and (b) MCO 5D males.
Fig. 9
Fig. 9
The role of gene expression changes in HCV infection and their potential implications for neuroinflammation and Parkinson’s disease. HCV preferentially targets liver parenchymal cells, and the expression of genes such as MT1H, SLC30A2, KRT23, RPL18, IFIT1, and S100A12 is upregulated, while that of MYOM2 and GPX3 is downregulated. Overexpression of IFIT1 may activate the cGAS/STING inflammatory pathway, but HCV antagonizes this pathway to prevent the host immune response. RPL18 may facilitate viral RNA translation, while KRT23 has been identified as an HCV host factor gene. MT1H and SLC30A2 may play a role in neurotoxin accumulation and zinc homeostasis, while GPX3 regulates ROS species. HCV-induced gene expression changes may contribute to neurodegeneration and PD development, possibly through blood‒brain barrier disruption and activation of proinflammatory mechanisms in microglia and astrocytes.

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