ArticleScientific reports2026
Extracellular vesicle-derived miR-760 as a novel promising candidate biomarker differentiating stable RRMS from SPMS.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Article
- Uncovering the dynamics of extracellular vesicle microRNA trafficking in multiple sclerosis: delivery, diversion and retention.Extracellular vesicles and circulating nucleic acids · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors.
Funding
Abstract
Multiple sclerosis (MS) is a chronic autoimmune disease of the central nervous system with heterogenous clinical course, lacking non-invasive biomarkers for phenotype differentiation. This study aimed to explore circulating extracellular vesicle (EV)-derived microRNA (miRNA) signatures and related molecular profiles capable of distinguishing stable relapsing-remitting MS (RRMS) from secondary progressive MS (SPMS). Plasma samples were collected from stable RRMS (n = 30), SPMS (n = 30), and healthy controls (HC) (n = 30), followed by total EVs isolation and characterization using transmission electron microscopy, dynamic light scattering, and flow cytometry. RNA was extracted from EVs, and miRNA profiles were analyzed via RNA sequencing and RT-qPCR. Cytokines and neuronal/astroglial injury biomarkers were quantified using the BioPlex system and ELISA. Functional enrichment and network analyses of miRNA targets were performed, alongside logistic regression modeling to explore potential distinguishing features. Four EV-derived miRNAs (miR-760, miR-98-5p, miR-301a-3p, miR-223-3p) showed significant differences (p < 0.05) between stable RRMS and SPMS. An integrative model combining miRNAs with fibroblast growth factor (FGF) basic protein enabled accurate phenotypic differentiation (AUC = 0.942). miR-760 showed the strongest distinctive capacity for stable RRMS. Additionally, miR-98-5p was markedly up-regulated in both stable RRMS and SPMS compared to HC. Network analysis of miRNA targets suggested distinct immunoregulatory patterns across MS phenotypes. Plasma EV-derived miRNAs—particularly miR-760, and miR-98-5p—showed potential as molecular indicators associated with disease phenotype in MS. Integrating EV-miRNA profiling with protein markers support efforts toward more precise stratification of MS patients. Further studies in independent cohorts and functional validation are warranted before clinical translation.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.