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Large-scale online assessment uncovers a distinct Multiple Sclerosis subtype with selective cognitive impairment

Author

Listed:
  • Annalaura Lerede

    (King’s College London
    Imperial College London)

  • Alexandra Moura

    (Imperial College London)

  • Valentina Giunchiglia

    (King’s College London
    Imperial College London
    Harvard University)

  • Elisa Carta

    (University of Cagliari)

  • William Trender

    (Imperial College London)

  • Katherine Tuite-Dalton

    (Swansea University Medical School)

  • James Witts

    (Swansea University Medical School)

  • Elaine Craig

    (Swansea University Medical School)

  • Sarah Knowles

    (Swansea University Medical School)

  • Jeff Rodgers

    (Swansea University Medical School)

  • Eleonora Cocco

    (University of Cagliari)

  • Peter J. Hellyer

    (King’s College London)

  • Rod Middleton

    (Swansea University Medical School)

  • Richard Nicholas

    (Imperial College London
    Swansea University Medical School)

  • Adam Hampshire

    (King’s College London
    Imperial College London)

Abstract

Cognitive impairments in Multiple Sclerosis (MS) are prevalent and disabling yet often unaddressed. Here, we optimised automated online assessment technology for people with MS and used it to characterise their cognitive deficits in greater detail and at a larger population scale than previously possible. The study involved 4526 UK MS Register members over three stages. Stage 1 evaluated 22 online cognitive tasks and established their feasibility. Based on MS discriminability a 12-task battery was selected. Stage 2 validated the resulting battery at scale, while Stage 3 compared it to a standard neuropsychological assessment. Clustering analysis identified a prevalent MS subtype exhibiting significant cognitive deficits with minimal motor impairment. Disability in this group is currently unrecognised and untreated. These findings underscore the importance of cognitive assessment in MS, the feasibility of integrating online tools into patient registries, and the potential of such large-scale data to derive insights into symptom heterogeneity.

Suggested Citation

  • Annalaura Lerede & Alexandra Moura & Valentina Giunchiglia & Elisa Carta & William Trender & Katherine Tuite-Dalton & James Witts & Elaine Craig & Sarah Knowles & Jeff Rodgers & Eleonora Cocco & Peter, 2025. "Large-scale online assessment uncovers a distinct Multiple Sclerosis subtype with selective cognitive impairment," Nature Communications, Nature, vol. 16(1), pages 1-15, December.
    • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-62156-4
    DOI: 10.1038/s41467-025-62156-4
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