Understanding Further the Phenotypic Spectrum of Central Nervous System Inflammatory Demyelinating Disorders Using Unsupervised Clustering

Gulec B., Everest E., Tutuncu M., Bilge U., Saip S., UYGUNOĞLU U., ...Daha Fazla

Annals of Clinical and Translational Neurology, 2026 (SCI-Expanded, Scopus) identifier identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Basım Tarihi: 2026
  • Doi Numarası: 10.1002/acn3.70389
  • Dergi Adı: Annals of Clinical and Translational Neurology
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, EMBASE, MEDLINE, Directory of Open Access Journals
  • Anahtar Kelimeler: atypical demyelinating disorders, double-seronegative disorders, principal component analyses, unsupervised clustering
  • İstanbul Üniversitesi-Cerrahpaşa Adresli: Evet

Özet

Background: Central 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. Objective: To better characterize the phenotypic spectrum of antibody-negative atypical inflammatory demyelinating disorders (AIDD) using unsupervised clustering. Methods: We 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. Results: AIDD 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. Conclusion: Double-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.