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. 2025 Sep;62(9):12280-12295.
doi: 10.1007/s12035-025-04932-3. Epub 2025 May 19.

Serum sEV miRNAs as Biomarkers in Myelin Oligodendrocyte Glycoprotein Antibody-Associated Disease

Affiliations

Serum sEV miRNAs as Biomarkers in Myelin Oligodendrocyte Glycoprotein Antibody-Associated Disease

Hark Kyun Kim et al. Mol Neurobiol. 2025 Sep.

Abstract

Myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) is a distinct CNS demyelinating disorder that differs from multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD). However, diagnosing MOGAD remains challenging due to the need to clinically exclude similar conditions and the variability in assay results. While liquid biomarkers have been extensively studied in MS and NMOSD, research on biomarkers for MOGAD remains limited. This study aims to investigate serum-derived small extracellular vesicle (sEV) miRNAs as potential diagnostic and prognostic biomarkers for MOGAD, distinguishing it from MS, NMOSD, and healthy controls. A comprehensive analysis of miRNAs in serum-derived sEVs was conducted to identify differentially expressed miRNAs among the groups. Correlations between miRNA profiles and clinical parameters, including the expanded disability status scale (EDSS) score and annualized relapse rate (ARR), were examined. The diagnostic potential of miRNAs was evaluated using the area under the curve (AUC) in the receiver operating characteristics (ROC) analyses. Serum samples were obtained from 47 patients (N = 11, MOGAD; N = 12, MS; and N = 12, NMOSD) and 12 healthy controls (HCs). We identified 77 dysregulated miRNAs in MOGAD patients, compared to HCs. Each three-miRNA panel demonstrated the highest AUC values for distinguishing MOGAD from HC (1.000), MOGAD from MS (0.939), and MOGAD from NMOSD (1.000). Additionally, hsa-miR-924 exhibited the strongest correlation with the EDSS score (ρ = -0.67, p < 0.001), while hsa-miR-548i showed the strongest correlation with ARR (ρ = -0.69, p < 0.001) in MOGAD. These miRNAs are involved in various pathways, including neuronal development, immune response, synaptic function, and chromatin remodeling, highlighting their potential roles in the pathophysiology of MOGAD. Serum sEV-derived miRNAs show strong potential as biomarkers for MOGAD, offering high diagnostic accuracy and correlations with clinical parameters. These findings pave the way for improved diagnostic and therapeutic strategies in MOGAD; however, further validation in larger cohorts is necessary.

Keywords: Annualized relapse rate; Biomarker; Expanded disability scale status; Extracellular vesicle; MiRNA; Multiple sclerosis; Myelin oligodendrocyte glycoprotein antibody-associated disease; Neuromyelitis optica spectrum disorder.

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Conflict of interest statement

Declarations. Ethical Approval and Consent to Participate: A signed informed consent was received from all the participants. This study has been approved from the institutional review board of the Samsung Medical Center (IRB No. 2020–04 - 119). Consent for Publication: Signed informed consent was received from all the participants including consent for publication. Competing interests: JHM is funded by and has received research support from the National Research Foundation of Korea (MIST and KHIDI) and SMC Research and Development grant. She has lectured, consulted, and received honoraria from Bayer Healthcare, Merk, Biogen Idec, Sanofi, UCB, Samsung Bioepis, Mitsubishi Tanabe, Celltrion, Roche, Janssen, and AstraZeneca. All other authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Characterization of isolated sEV from serum and analysis for miRNA expression in sEV. A Representative cryo-TEM images displaying the morphology of sEVs isolated from serum. Scale bar: 100 nm. B Western blot analysis for ALIX, Calnexin, HSP70, TSG101, and CD63 of sEV. C Nanoparticle tracking analysis of size distributions and concentration measurements of sEV. Venn diagram illustrating the overlapping miRNAs identified in the differential expression analysis when comparing the HC with MS, NMOSD, and MOGAD: D total differentially expressed miRNAs, as well as E the upregulated and F downregulated miRNAs
Fig. 2
Fig. 2
Comprehensive analysis of DEmiRNAs in sEV from MOGAD patients compared with HCs, MS, and NMOSD patients. Hierarchical clustering of DE miRNAs and heatmap representing the significantly differentially expressed miRNAs and volcano plot displaying the DE miRNAs A between MOGAD and HC, B between MOGAD and MS, and C between MOGAD and NMOSD. The red dots indicate statistically significant DE miRNAs
Fig. 3
Fig. 3
GO analysis and KEGG pathway enrichment analysis conducted on the genes targeted by the top 10 DE miRNAs in MOGAD patients compared with HC, MS and NMOSD patients: A between MOGAD and HC, B between MOGAD and MS, and C between MOGAD and NMOSD
Fig. 4
Fig. 4
ROC curve analysis with serum sEV miRNAs showing top three miRNAs with the highest AUC values and ROC curve with the three miRNAs combined as a panel. ROC curves for distinguishing A MOGAD from HC, B MOGAD from MS, C MOGAD from NMOSD, D MOGAD from MS/NMOSD, and E MOGAD from MS/NMOSD/HC. *P < 0.05; **P < 0.01
Fig. 5
Fig. 5
Correlation analysis of DEmiRNAs with EDSS and ARR in MOGAD patients. A Four DEmiRNAs showed correlation with expanded disability status scale (EDSS) score. B Four DEmiRNAs showed correlation with annualized relapse rate (ARR)

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References

    1. Marignier R, Hacohen Y, Cobo-Calvo A, Probstel AK, Aktas O, Alexopoulos H et al (2021) Myelin-oligodendrocyte glycoprotein antibody-associated disease. Lancet Neurol 20(9):762–772 - PubMed
    1. Takai Y, Misu T, Kaneko K, Chihara N, Narikawa K, Tsuchida S et al (2020) Myelin oligodendrocyte glycoprotein antibody-associated disease: an immunopathological study. Brain 143(5):1431–1446 - PubMed
    1. Jakimovski D, Bittner S, Zivadinov R, Morrow SA, Benedict RH, Zipp F et al (2024) Multiple sclerosis. Lancet 403(10422):183–202 - PubMed
    1. Banwell B, Bennett JL, Marignier R, Kim HJ, Brilot F, Flanagan EP et al (2023) Diagnosis of myelin oligodendrocyte glycoprotein antibody-associated disease: International MOGAD Panel proposed criteria. The Lancet Neurology 22(3):268–282 - PubMed
    1. Lipps P, Ayroza Galvao Ribeiro Gomes AB, Kulsvehagen L, Mutke MA, Kuhle J, Papadopoulou A, et al (2023) Ongoing challenges in the diagnosis of myelin oligodendrocyte glycoprotein antibody-associated disease. JAMA Neurol 80(12):1377–9. - PMC - PubMed

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