Identification of Ferroptosis- and Hypoxia-related Genes in iPSC-derived Oligodendrocyte Precursor Cells from Multiple Sclerosis Patients

Summary

This study provides novel insights into the interactions among hypoxia, ferroptosis, and immune infiltration in the pathogenesis of multiple sclerosis (MS) via bioinformatics analysis. By employing weighted gene coexpression network analysis (WGCNA) and protein-protein interaction (PPI) analysis, we identified three pivotal hub genes (ITGB1, ITGB8, and VIM).

Abstract

Multiple sclerosis (MS) is a chronic inflammatory disorder characterized by demyelination, with failed remyelination leading to progressive axon loss in chronic stages. Oligodendrocyte precursor cells (OPCs) are critical for remyelination. Recent studies suggest that both hypoxia and ferroptosis play crucial roles in the dysfunctional differentiation of OPCs. This research seeks to identify key genes linked to hypoxia and ferroptosis and immune infiltration characteristics in OPCs derived from induced pluripotent stem cells (iPSCs) of MS patients and to construct a diagnostic model centered on these pivotal genes.

We analyzed gene expression data from the GSE196575 and GSE147315 datasets and compared MS patients with healthy individuals. Using weighted gene coexpression network analysis (WGCNA), we pinpointed primary module genes and essential genes associated with hypoxia, ferroptosis, and MS. The ferroptosis Z score and the hypoxia Z score calculated via gene set variation analysis (GSVA) were greater in the iPSC-derived OPCs of MS patients than those of the control group. The implicated genes are predominantly linked to the PI3K/Akt/mTOR pathway, as identified through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses.

A protein-protein interaction (PPI) network of crucial genes revealed 10 central hub genes (COL4A1, COL4A2, ITGB5, ITGB1, ITGB8, ITGAV, VIM, FLNA, VCL, and SPARC). The robust expression of ITGB1, ITGB8, and VIM was validated in the GSE151306 dataset, supporting their role as key hub genes. Additionally, an interaction network between transcription factors (TFs) and hub genes was established via Transcriptional Regulatory Relationships Unraveled by Sentence-based Text (TRRUST), which identified five key TFs. The results of this study could help elucidatenovel biomarkers or therapeutic targets for MS.

Introduction

Multiple sclerosis (MS) is a chronic inflammatory condition characterized by demyelination, that affects approximately 2.5 million individuals globally. The majority of those diagnosed with MS exhibit a relapsing-remitting (RR) disease course. During the relapsing phase, acute inflammation leads to the inevitable loss of myelin and axons. Conversely, during remission, demyelination lesions can be repaired by remyelination, providing trophic support to axons and preventing progressive axon loss¹. Remyelination failure occurs in the chronic stages of MS and leads to progressive axonal degeneration².

Protocol

1. Data download and preprocessing

1. Download the datasets GSE196575 and GSE147315 from the Gene Expression Omnibus (GEO).
2. Merge the two datasets and remove batch effects, using an online analysis platform (see Table of Materials).
   1. Choose the Expression module | data merge module. Upload the two expression matrix files as input files and click Run to automatically output the merged matrix.
   2. Create a sample annotation file as a spreadsheet.
   3. Choose the Expression module | Remove batch effect module. Input the annotati....

Discussion

Given its pivotal role in the remyelination process, the migration, differentiation, and death of OPCs have long been determined to be crucial factors in MS pathogenesis and therapeutic targets of MS. Inflammation-independent progressive nerve degeneration has been observed in all three types of MS¹⁹, and a pronounced loss of oligodendrocyte was noted at the center of demyelinated lesions²⁰, suggesting that primary disorders of oligodendrocyte lineage cells could accelerate.......

Materials

Name	Company	Catalog Number	Comments
BioInfoTools	/		online analysis website http://biowinford.site:3838/patrick_wang87/
Cytoscape	/		bioinformatics network analysis software
GSE196575,GSE147315 and GSE151306	/		RNA-seq from GEO dataset
Omicshare	GENE DENOVO		online analysis tools https://www.omicshare.com/tools/Home/Soft/getsoft
R-studio	RStudio, Inc		R integrated development environment software