Gene expression in multiple sclerosis during pregnancy based on integrated bioinformatics analysis

Martha Rocio Hernández-Preciado; Blanca Miriam Torres-Mendoza; Mario Alberto Mireles-Ramírez; Antonio Kobayashi-Gutiérrez; Nayeli Alejandra Sánchez-Rosales; Eduardo Vázquez-Valls; Jazmin Marquez-Pedroza

doi:10.1016/j.msard.2023.105373

Gene expression in multiple sclerosis during pregnancy based on integrated bioinformatics analysis

Mult Scler Relat Disord. 2024 Feb:82:105373. doi: 10.1016/j.msard.2023.105373. Epub 2023 Dec 14.

Authors

Martha Rocio Hernández-Preciado¹, Blanca Miriam Torres-Mendoza², Mario Alberto Mireles-Ramírez³, Antonio Kobayashi-Gutiérrez⁴, Nayeli Alejandra Sánchez-Rosales³, Eduardo Vázquez-Valls⁵, Jazmin Marquez-Pedroza⁶

Affiliations

¹ High Specialty Medical Unit, Pediatric Hospital, Western National Medical Center of the Mexican Institute of Social Security, Guadalajara 44340, Mexico; Department of Philosophical and Methodological Disciplines, University Health Sciences Center, University of Guadalajara, Guadalajara 44340, Mexico.
² Department of Philosophical and Methodological Disciplines, University Health Sciences Center, University of Guadalajara, Guadalajara 44340, Mexico; Neurosciences Division, Western Biomedical Research Center (IMSS), Guadalajara 44340, Mexico.
³ High Specialty Medical Unit, Western National Medical Center of the Mexican Institute of Social Security, Guadalajara 44340, Mexico.
⁴ High Specialty Medical Unit, Western National Medical Center of the Mexican Institute of Social Security, Guadalajara 44340, Mexico; PhD in Psychology of Health, University Health Sciences Center, University of Guadalajara, Guadalajara 44340, Mexico.
⁵ Directorate of Generation of Professional Resources, Research, and Development, Secretary of Health, Guadalajara 44100, Mexico.
⁶ Neurosciences Division, Western Biomedical Research Center (IMSS), Guadalajara 44340, Mexico. Electronic address: jaz180688@gmail.com.

PMID: 38154347
DOI: 10.1016/j.msard.2023.105373

Abstract

Background: The modulation of the activity disease in patients with Multiple Sclerosis (MS) that occurs during pregnancy is a helpful model which could provide insight into central disease mechanisms and facilitate treatment. Therefore, the aim of the study was to identify differentially expressed genes in-silico to perform biological function pathway enrichment analysis and protein-protein interaction from pregnant women with MS.

Methods: Transcriptome data were obtained from the Gene Expression Omnibus (GEO) database. We selected the microarray dataset GSE17449. The gene expression dataset contains the data of mononuclear cells from four different groups sought, including seven healthy women (H), four healthy pregnant women (HP), eight women with multiple sclerosis (WMS), and nine women nine months pregnant with multiple sclerosis (PMS). The GSEA software was employed for enrichment analysis, and the REACTOME database was used for biological pathways. The protein-protein interaction (PPI) network was plotted with STRING. The databases used to identify the connection of DEGs with different signaling pathways were KEGG and WIKIPATHWAYS.

Results: We identified 42 differentially expressed genes in pregnant women with MS. The significant pathways included IL-10 signaling pathway, ErbB2 activates, the hemoglobin complex (HBD, HBB, HBA1, AHSP, and HBA2), IL-17 signaling pathway (LCN2 and MMP9), antigen processing and presentation, and Th17 cell differentiation (HLA-DQA1), Rap1 signaling pathway (ID1), NOD-Like receptor signaling pathway (CAMP and DEFA4), PD-L1 Signaling, Interferon gamma signaling (MMP9 and ARG1), Neutrophil degranulation (CAMP, DEFA4, ELANE, CEACAM8, S100P, CHI3L1, AZU1, OLFM4, CRISP3, LTF, ARG1, PGLYRP1, and TCN1). In the WIKIPATHWAYS set, significance was found Vitamin B12 metabolism (TCN1, HBB, and HBA2), and IL-18 signaling pathway (S100P).

Conclusion: This study can be used to understand several essential target genes and pathways identified in the present study, which may serve as feasible targets for MS therapies.

Keywords: Bioinformatics analysis; Functional analysis; Genes; Multiple sclerosis; Pathway; Pregnancy.

MeSH terms

Blood Proteins
Computational Biology
Female
Humans
Matrix Metalloproteinase 9*
Molecular Chaperones
Multiple Sclerosis* / genetics
Pregnancy
Protein Interaction Maps
Transcriptome

Substances

Matrix Metalloproteinase 9
AHSP protein, human
Blood Proteins
Molecular Chaperones