Evidence map›Paper›PMID 42700718›Full record

Observational studyEBioMedicine2026

Gut microbiome profiling at multiple sclerosis onset as a potential early prognostic marker of disease course: evidence from an observational cohort study.

Alessandro Maglione, Rachele Rosso, Dora Tortarolo, Francesco Pantini, Simone Pernice, Sandro Gepiro Contaldo, Roberta Lanzillo, Antonio Luca Spiezia, Cinzia Cordioli, Eleonora Virgilio and 11 more

Abstract readObservational Study
In one paragraph

Observational study in EBioMedicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

21 authors.

Alessandro MaglioneDepartment of Clinical and Biological Sciences, University of Torino, Orbassano, Torino, 10043, Italy; Department of Computer Sciences, University of Torino, Torino, 10149, Italy.
Rachele RossoDepartment of Clinical and Biological Sciences, University of Torino, Orbassano, Torino, 10043, Italy.
Dora TortaroloDepartment of Computer Sciences, University of Torino, Torino, 10149, Italy.
Francesco PantiniDepartment of Computer Sciences, University of Torino, Torino, 10149, Italy.
Simone PerniceDepartment of Computer Sciences, University of Torino, Torino, 10149, Italy.
Sandro Gepiro ContaldoDepartment of Computer Sciences, University of Torino, Torino, 10149, Italy.
Roberta LanzilloDepartment of Neurosciences, Reproductive Sciences and Odontostomatology, Federico II University, Naples, Italy.
Antonio Luca SpieziaDepartment of Neurosciences, Reproductive Sciences and Odontostomatology, Federico II University, Naples, Italy.
Cinzia CordioliASST Spedali Civili di Brescia, Multiple Sclerosis Centre, Montichiari, Italy.
Eleonora VirgilioDepartment of Clinical and Biological Sciences, University of Torino, Orbassano, Torino, 10043, Italy; AOU San Luigi Gonzaga, SSD Specialist Neurological Pathologies, Orbassano, Italy.
Federica MasuzzoAOU San Luigi Gonzaga, SSD Specialist Neurological Pathologies, Orbassano, Italy.
Manuela MattaAOU San Luigi Gonzaga, SSD Specialist Neurological Pathologies, Orbassano, Italy.
Simona MalucchiAOU San Luigi Gonzaga, CReSM, Orbassano, Italy.
Paola CavallaDepartment. of Neuroscience, University of Torino, MS centre, City of Health and Science University Hospital of Torino, Turin, Italy.
Luca CocolinDepartment of Agriculture, Forest and Food Science (DISAFA), University of Torino, Grugliasco, Torino, 10095, Italy.
Roberta SirovichDepartment of Mathematics G. Peano, University of Torino, Torino, 10123, Italy.
Marco BeccutiDepartment of Computer Sciences, University of Torino, Torino, 10149, Italy.
Ilario FerrocinoDepartment of Agriculture, Forest and Food Science (DISAFA), University of Torino, Grugliasco, Torino, 10095, Italy.
Francesca CorderoDepartment of Computer Sciences, University of Torino, Torino, 10149, Italy. Electronic address: Francesca.cordero@unito.it.
Marinella ClericoDepartment of Clinical and Biological Sciences, University of Torino, Orbassano, Torino, 10043, Italy; AOU San Luigi Gonzaga, SSD Specialist Neurological Pathologies, Orbassano, Italy.
Simona RollaDepartment of Clinical and Biological Sciences, University of Torino, Orbassano, Torino, 10043, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAlterations in gut microbiome composition have been associated with multiple sclerosis (MS), but their impact on disease severity and early progression remains poorly understood. In this study we investigated whether gut microbiome profiling at diagnosis could identify microbial signatures associated with clinical and radiological features of early MS and provide prognostic information.

methodsWe analysed the gut microbiome of 53 treatment-naïve patients with MS (pwMS) and 55 healthy donors (HD) using shotgun metagenomic sequencing, combined with clinical features collected over 1 year from diagnosis. To clarify whether gut microbiome composition at MS onset could have prognostic relevance, pwMS were stratified according to lesion burden, lesion localisation, and magnetic resonance imaging (MRI) activity.

findingsOverall beta diversity in Bacteria, Archaea, and Eukarya differed significantly between pwMS and HD (p-value <0.001, <0.02, <0.03, respectively). Within the MS group, glucocorticoid treatment at disease onset was the clinical factor most strongly associated with gut microbiota diversity. Stratification according to lesion burden, lesion localisation, and MRI activity identified two clinically distinct MS subgroups with different baseline clinical characteristics at onset (p-value <0.03) and different risk of early disease progression. The cluster associated with an unfavourable prognosis showed greater progression within 12 months and was enriched for motor symptoms and spinal cord lesions at diagnosis.

interpretationOur findings suggest that gut microbiome alterations are detectable at the earliest stages of MS and are associated with clinical and radiological features linked to short-term disease evolution. Gut microbial profiling may therefore represent a promising early prognostic biomarker and may help to identify candidate targets for early intervention and therapeutic development in MS, although further validation in larger longitudinal cohorts is needed.

fundingThis study was supported by grants from the Italian Multiple Sclerosis Foundation, the Cassa di Risparmio di Torino Foundation, and the Italian Ministry of University and Research.

Indexed as

Gastrointestinal MicrobiomeMultiple SclerosisAdultBiomarkersCohort StudiesDisease ProgressionFemaleHumansMagnetic Resonance ImagingMaleMetagenomeMetagenomicsMiddle AgedPrognosisBiomarkersDisease progressionGut microbiomeMultiple sclerosisPrognostic biomarkerShotgun metagenomic analysis

Identifiers

PMID42700718
PMCPMC13688122

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