Multiple sclerosis and related disorders · 2026
ST8SIA4 as a candidate diagnostic biomarker: Blood-cerebrospinal fluid signature in RRMS.
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Denkçeken Tuba, Onur Elif
Аннотация
OBJECTIVE: Multiple Sclerosis (MS) is a chronic autoimmune disease of the central nervous system characterized by inflammation, demyelination, and axonal degeneration, with relapsing-remitting MS (RRMS) representing its most prevalent clinical phenotype. This study aimed to investigate hub-genes and hub-miRNAs that were differentially expressed in peripheral blood mononuclear cell (PBMC) samples from RRMS patients and validate the hub-genes in cerebrospinal fluid (CSF) to assess their potential clinical diagnostic value.
METHODS: All mRNA and miRNA expression profiling studies of RRMS in PBMC samples were downloaded from the GEO and ArrayExpress databases and differentially expressed mRNAs (DEGs) and miRNAs (DEMs) were determined. The regulation patterns of DEGs and DEMs were determined by fold change. Target genes of DEMs and common-gene clusters were defined, and then other bioinformatic approaches were applied. External validation of hub-genes was performed in CSF samples to confirm biological relevance beyond PBMCs and to evaluate their applicability as clinically accessible biomarkers.
RESULTS: mRNA datasets 228 control and 209 RRMS, and miRNA datasets included 93 control and 84 RRMS PBMC samples. It was found that ATM, CREB1, ST8SIA4, hsa-miR-19b-3p, and hsa-miR-181c-5p are dysregulated in RRMS patients' PBMC samples. Then, hub-genes were validated and ST8SIA4 ROC analysis provided a sensitivity of 83.9% and specificity of 88% in discriminating RRMS from controls with an accuracy of 85.7%.
CONCLUSION: ST8SIA4 is regulated in the same direction in PBMC and CSF samples from RRMS patients and can discriminate between the RRMS and control groups with high sensitivity. It can be concluded that the high diagnostic accuracy of ST8SIA4 has the potential to be used as a novel biomarker alongside existing clinical and laboratory parameters to distinguish RRMS from controls during clinical examinations.
METHODS: All mRNA and miRNA expression profiling studies of RRMS in PBMC samples were downloaded from the GEO and ArrayExpress databases and differentially expressed mRNAs (DEGs) and miRNAs (DEMs) were determined. The regulation patterns of DEGs and DEMs were determined by fold change. Target genes of DEMs and common-gene clusters were defined, and then other bioinformatic approaches were applied. External validation of hub-genes was performed in CSF samples to confirm biological relevance beyond PBMCs and to evaluate their applicability as clinically accessible biomarkers.
RESULTS: mRNA datasets 228 control and 209 RRMS, and miRNA datasets included 93 control and 84 RRMS PBMC samples. It was found that ATM, CREB1, ST8SIA4, hsa-miR-19b-3p, and hsa-miR-181c-5p are dysregulated in RRMS patients' PBMC samples. Then, hub-genes were validated and ST8SIA4 ROC analysis provided a sensitivity of 83.9% and specificity of 88% in discriminating RRMS from controls with an accuracy of 85.7%.
CONCLUSION: ST8SIA4 is regulated in the same direction in PBMC and CSF samples from RRMS patients and can discriminate between the RRMS and control groups with high sensitivity. It can be concluded that the high diagnostic accuracy of ST8SIA4 has the potential to be used as a novel biomarker alongside existing clinical and laboratory parameters to distinguish RRMS from controls during clinical examinations.