ArticleAnnals of clinical and translational neurology2026
Understanding Further the Phenotypic Spectrum of Central Nervous System Inflammatory Demyelinating Disorders Using Unsupervised Clustering.
Article in Annals of clinical and translational neurology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundCentral nervous system (CNS) inflammatory demyelinating syndromes, including multiple sclerosis (MS), aquaporin-4 antibody-positive neuromyelitis optica spectrum disorder (AQP4 + NMOSD), and myelin oligodendrocyte glycoprotein (MOG) antibody-associated disease (MOGAD), occasionally overlap. Some patients remain double-seronegative, showing atypical features that challenge current classifications.
objectiveTo better characterize the phenotypic spectrum of antibody-negative atypical inflammatory demyelinating disorders (AIDD) using unsupervised clustering.
methodsWe retrospectively analyzed 316 patients (MS = 164, AQP4 + NMOSD = 36, double-seronegative NMOSD = 21, MOGAD = 15, AIDD = 80) followed between 2010 and 2023. Principal component analysis and k-means clustering were applied to AIDD cases using clinical, demographic, and radiological data.
resultsAIDD patients had lower disability and fewer corpus callosum and posterior fossa lesions than MS and NMOSD. Three clusters emerged: (1) myelitis-predominant with unmatched CSF oligoclonal bands and longitudinally extensive spinal lesions, (2) brainstem-dominant with recurrent brainstem attacks, and (3) optic neuritis-dominant with recurrent LEON meeting MS dissemination criteria. Treatment patterns differed; rituximab was most frequent.
conclusionDouble-seronegative AIDD represents a heterogeneous clinical spectrum. Unsupervised clustering provides a data-driven framework for refining phenotypic classification and may support biomarker and therapeutic development in antibody-negative CNS demyelination.
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