Evidence map›Paper›PMID 42627512›Full record

ArticleActa neuropathologica2026

Genetic subtypes of multiple sclerosis severity are uncoupled from inflammatory lesion burden.

Gianmarco Abbadessa, Karim L Kreft, Owain Howell, Jean Victor Carlos de Oliveira, Benjamin Cooze, Artemis Papadaki, Joic Majo Jacinto, Ildiko Farkas, Yeung-Yeung Leung, Simona Bonavita and 8 more

Abstract read
In one paragraph

Article in Acta neuropathologica, 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
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1 · What the graph read from it

What it found

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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

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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

18 authors.

Gianmarco Abbadessa *Department of Advanced Medical and Surgical Sciences, University of Campania Luigi Vanvitelli, Naples, Italy.
Karim L Kreft *Academic Neurology, Academic Unit of Mental Health and Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, UK. karim.kreft@nottingham.ac.uk.
Owain HowellDepartment of Brain Sciences, Imperial College London, London, UK.
Jean Victor Carlos de OliveiraInstitute for Life Sciences, Swansea University, Swansea, UK.
Benjamin CoozeInstitute for Life Sciences, Swansea University, Swansea, UK.
Artemis PapadakiDepartment of Brain Sciences, Imperial College London, London, UK.
Joic Majo JacintoInstitute for Life Sciences, Swansea University, Swansea, UK.
Ildiko FarkasDepartment of Brain Sciences, Imperial College London, London, UK.
Yeung-Yeung LeungDepartment of Brain Sciences, Imperial College London, London, UK.
Simona BonavitaDepartment of Advanced Medical and Surgical Sciences, University of Campania Luigi Vanvitelli, Naples, Italy.
Emma Clare TallantyreInstitute of Psychological Medicine and Clinical Neuroscience, Cardiff University, Cardiff, Wales, UK.
Neil P RobertsonInstitute of Psychological Medicine and Clinical Neuroscience, Cardiff University, Cardiff, Wales, UK.
Ai NaganoDepartment of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, London, UK.
Mie RizigDepartment of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, London, UK.
Roberta MagliozziDepartment of Brain Sciences, Imperial College London, London, UK.
David OwenDepartment of Brain Sciences, Imperial College London, London, UK.
Richard ReynoldsDepartment of Brain Sciences, Imperial College London, London, UK.
Richard NicholasDepartment of Brain Sciences, Imperial College London, London, UK. r.nicholas@imperial.ac.uk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Determinants of long-term disability in multiple sclerosis (MS) remain incompletely understood, with clinical course varying greatly among individuals. Recent integrative genetic models have identified genomic clusters associated with divergent disability trajectories. Here, we integrated clinical, genetic, and postmortem neuropathological data from 291 MS brain donors from the UK MS Society Tissue Bank to test whether genomic severity clusters converge on distinct tissue phenotypes. Consistent with prior stratification, donors in genomic cluster 2 had lower age-adjusted disease duration score (ADDS) than cluster 3 (β = - 0.195, P = 0.023) and a shorter interval from progression to death than cluster 1 (β = - 0.225, P = 0.049). However, this adverse clinical profile did not reflect greater active or chronic active lesion burden. Instead, chronic active broad-rim lesions were more frequent in cluster 1 than clusters 2 and 3 (37.3% vs 24.0% and 27.2%; both FDR = 0.043), whereas chronic inactive lesions were enriched in clusters 2 and 3 relative to cluster 1 (58.2% vs 70.0% and 73.8%; FDR = 0.154 and 0.030, respectively). This dissociation was strongly influenced by HLA genetic background: cluster 1 carried the highest HLA genetic burden, which was associated with greater non-lesional HLA-D immunoreactivity (rho = 0.48, FDR < 0.001), higher HLA-DRB1 (rho = 0.514, FDR < 0.001) and HLA-DRB5 (rho = 0.740, FDR < 0.001) mRNA expression, more active lesions (rho = 0.21, FDR = 0.007) and chronic active broad-rim lesions (rho = 0.19, FDR = 0.017), and fewer chronic inactive lesions (rho = - 0.26, FDR < 0.001), but not with clinical severity. Although chronic active lesion burden remained a strong tissue correlate of severity, adjustment for it strengthened the association between cluster 2 and worse outcome (ADDS: cluster 2 vs 1: β = - 0.216, Holm-adjusted P = 0.038; cluster 2 vs 3: β = - 0.246, Holm-adjusted P = 0.012; time from progression to death: cluster 2 vs 1: β = - 0.288, Holm-adjusted P = 0.049). Overall, these findings indicate that (i) HLA genetic background shapes the neuropathological representation of inflammatory lesions, and (ii) the adverse clinical profile of cluster 2 is not fully explained by HLA-D-defined chronic active lesion burden in the sampled postmortem tissue, suggesting that genomic severity clusters and chronic active lesion burden capture complementary aspects of MS progression.

Indexed as

BrainMultiple SclerosisAdultDisease ProgressionFemaleHumansInflammationMaleMiddle AgedSeverity of Illness IndexChronic active lesionsDisability progressionGeneticHuman Leukocyte AntigenMultiple sclerosisNeuropathology

Identifiers

PMID42627512
PMCPMC13498620

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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 OpenQuestion graph.