id_786. MESSAGES IN EXTRACELLULAR VESICLES: DECODING MIRNA BIOMARKERS IN MULTIPLE SCLEROSIS
Andrėja Strigauskaitė1,2, Violeta Belickienė1, Rūta Juozaitienė3, Gabrielė Dargė3, Monika Kurgonaitė4, Renata Balnytė5, Ieva Masiulienė5, Paulina Vaitkienė1, Ugnė Zubrickaitė3, Dalia Čalnerytė3, Edita Kuncevičienė1
1 Laboratory of Molecular Neurobiology, Neuroscience Institute, Lithuanian University of Health Sciences, evenių st. 4, Kaunas, Lithuania
2 Medical Faculty, Lithuanian University of Health Sciences, A. Mickevičiaus st. 9, Kaunas, Lithuani
3 Faculty of Informatics, Vytautas Magnus University, Universiteto st. 10, Kaunas, Lithuania
4 Department of Applied Informatics, Kaunas University of Technology, Studentų st. 50, Kaunas, Lithuania
5 Department of Neurology, Lithuanian University of Health Sciences, evenių st. 2, Kaunas, Lithuania
INTRODUCTION: Multiple sclerosis (MS) is a chronic immune-mediated disease of the CNS characterized by neuroinflammation, demyelination, and progressive neurological disability. Despite significant advances in understanding MS pathogenesis, reliable biomarkers for diagnosis or prognosis are still lacking. MicroRNAs (miRNAs), small non-coding regulators of gene expression involved in immune and neuroinflammatory processes, are stable and detectable in circulation – particularly within extracellular vesicles – making them promising candidates for minimally invasive biomarker discovery.
AIM(S): To identify EV derived miRNAs associated with Multiple sclerosis, evaluate their biomarker potential, and explore their relationships with clinical and radiological features.
METHOD(S): Illumina sequencing of EV‑derived miRNAs from 22 patient samples. Data were analyzed using DESeq2, PCA, sPLS‑DA, and Elastic Net to identify candidate miRNAs. Selected miRNAs were validated by qPCR in an independent cohort of 47 patient samples, followed by evaluation of clinical and radiological associations.
RESULTS: PCA revealed two clearly separated clusters corresponding to HC and untreated MS patients. Differential expression analysis using DESeq2 identified 13 miRNAs significantly dysregulated in MS compared to HC. Both sPLS‑DA and Elastic Net modelling highlighted several miRNAs as major contributors to class discrimination. Strong correlations were observed between miR‑197‑3p and miR‑30e‑3p and multiple clinical parameters, including disease duration, Expanded Disability Status Scale (EDSS) score, lesion localization, and additional disease‑related measures. Among the top candidates, miR‑197‑3p and miR‑30e‑3p were selected for validation by qPCR. Validation confirmed a significant upregulation of miR‑197‑3p in MS patients relative to healthy controls.
CONCLUSIONS: The significant upregulation of miR‑197‑3p in MS highlights its biomarker potential, but larger studies are needed to confirm these preliminary findings.
FINANCIAL SUPPORT: Funding received from the Association “Santakos slėnis” joint research project competition for science and study institutions.
P-ST-25-15, Funded by Reasearch Council of Lithuania