Integration of Genetic and Immune Infiltration Insights into Data Mining of Multiple Sclerosis Pathogenesis

Zhang, Xiaoyun; Song, Ying; Chen, Xiao; Zhuang, Xiaojia; Wei, Zhiqiang; Li, Yi

doi:10.1155/2022/1661334

Cited by 2 publications

(1 citation statement)

References 47 publications

(39 reference statements)

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“…Multiple sclerosis (MS) is an autoimmune disease that causes inflammatory demyelinating lesions of white matter in the central nervous system [ 4 ]. Even though the cause of MS is unclear, current findings suggest that environmental and genetic variables contribute to the disease’s development [ 5 ]. Several environmental factors, such as infection, latitude, vitamin D deficiency, and smoking, contribute to the development of MS [ 6 ].…”

Section: Introductionmentioning

confidence: 99%

Exploration of potential shared gene signatures between periodontitis and multiple sclerosis

Wu,

Cheng,

Zhang

et al. 2024

BMC Oral Health

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Background Although periodontitis has previously been reported to be linked with multiple sclerosis (MS), but the molecular mechanisms and pathological interactions between the two remain unclear. This study aims to explore potential crosstalk genes and pathways between periodontitis and MS. Methods Periodontitis and MS data were obtained from the Gene Expression Omnibus (GEO) database. Shared genes were identified by differential expression analysis and weighted gene co-expression network analysis (WGCNA). Then, enrichment analysis for the shared genes was carried out by multiple methods. The least absolute shrinkage and selection operator (LASSO) regression was used to obtain potential shared diagnostic genes. Furthermore, the expression profile of 28 immune cells in periodontitis and MS was examined using single-sample GSEA (ssGSEA). Finally, real-time quantitative fluorescent PCR (qRT-PCR) and immune histochemical staining were employed to validate Hub gene expressions in periodontitis and MS samples. Results FAM46C, SLC7A7, LY96, CFI, DDIT4L, CD14, C5AR1, and IGJ genes were the shared genes between periodontitis, and MS. GO analysis revealed that the shared genes exhibited the greatest enrichment in response to molecules of bacterial origin. LASSO analysis indicated that CFI, DDIT4L, and FAM46C were the most effective shared diagnostic biomarkers for periodontitis and MS, which were further validated by qPCR and immunohistochemical staining. ssGSEA analysis revealed that T and B cells significantly influence the development of MS and periodontitis. Conclusions FAM46C, SLC7A7, LY96, CFI, DDIT4L, CD14, C5AR1, and IGJ were the most important crosstalk genes between periodontitis, and MS. Further studies found that CFI, DDIT4L, and FAM46C were potential biomarkers in periodontitis and MS.

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Section: Introductionmentioning

confidence: 99%

Exploration of potential shared gene signatures between periodontitis and multiple sclerosis

Wu,

Cheng,

Zhang

et al. 2024

BMC Oral Health

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Gene expression and alternative splicing analysis in a large-scale Multiple Sclerosis study

Sak,

Chariker,

Park

et al. 2024

Preprint

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Background: Multiple Sclerosis (MS) is an autoimmune neurodegenerative disease affecting approximately 3 million people globally. Despite rigorous research on MS, aspects of its development and progression remain unclear. Understanding molecular mechanisms underlying MS is crucial to providing insights into disease pathways, identifying potential biomarkers for early diagnosis, and revealing novel therapeutic targets for improved patient outcomes. Methods: We utilized publicly available RNA-seq data (GSE138614) from post-mortem white matter tissues of five donors without any neurological disorder and ten MS patient donors. This data was interrogated for differential gene expression, alternative splicing and single nucleotide variants as well as for functional enrichments in the resulting datasets. Results: A comparison of non-MS white matter (WM) to MS samples yielded differentially expressed genes involved in adaptive immune response, cell communication, and developmental processes. Genes with expression changes positively correlated with tissue inflammation were enriched in the immune system and receptor interaction pathways. Negatively correlated genes were enriched in neurogenesis, nervous system development, and metabolic pathways. Alternatively spliced transcripts between WM and MS lesions included genes that play roles in neurogenesis, myelination, and oligodendrocyte differentiation, such as brain enriched myelin associated protein (BCAS1), discs large MAGUK scaffold protein 1 (DLG1), KH domain containing RNA binding (QKI), and myelin basic protein (MBP). Our approach to comparing normal appearing WM (NAWM) and active lesion (AL) from one donor and NAWM and chronic active (CA) tissues from two donors, showed that different IgH and IgK gene subfamilies were differentially expressed. We also identified pathways involved in white matter injury repair and remyelination in these tissues. Differentially spliced genes between these lesions were involved in axon and dendrite structure stability. We also identified exon skipping events and spontaneous single nucleotide polymorphisms in membrane associated ring-CH-type finger 1 (MARCHF1), UDP glycosyltransferase 8 (UGT8), and other genes important in autoimmunity and neurodegeneration. Conclusion: Overall, we identified unique genes, pathways, and novel splicing events affecting disease progression that can be further investigated as potential novel drug targets for MS treatment.

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Integration of Genetic and Immune Infiltration Insights into Data Mining of Multiple Sclerosis Pathogenesis

Cited by 2 publications

References 47 publications

Exploration of potential shared gene signatures between periodontitis and multiple sclerosis

Exploration of potential shared gene signatures between periodontitis and multiple sclerosis

Gene expression and alternative splicing analysis in a large-scale Multiple Sclerosis study

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