Plasma n -glycan profiling enhances diagnostic precision in multiple sclerosis, APQ4-AB NMOSD, and MOGAD

Journal article

Background and objectivesDifferentiating multiple sclerosis (MS) from antibody (Ab)-defined diseases, such as neuromyelitis optica spectrum disorders (NMOSDs), remains challenging, particularly as Ab levels decline. N-glycans play a key role in immunity, with changes in branching and fucosylation linked to T/B-cell function and MS onset while increased N-acetylglucosamine residues correlate with disease progression. Despite growing recognition of glycosylation in neuroinflammation, direct comparisons of the N-glycome between MS and Ab-defined diseases are lacking. This study aims to assess whether plasma N-glycome profiling can effectively differentiate these conditions and their subtypes.MethodsThis cohort study included 120 participants: 30 with relapsing-remitting MS (RRMS), 30 with secondary progressive MS (SPMS), 30 with myelin oligodendrocyte glycoprotein Ab-associated disease (MOGAD), and 30 with aquaporin-4 (AQP4)-Ab NMOSD, recruited from the John Radcliffe Hospital, Oxford University Hospitals National Health System (NHS) Trust. Plasma N-glycans were analyzed using ultra-high-performance (UHPLC) hydrophilic interaction liquid chromatography (HILIC) coupled with high-resolution mass spectrometry. Orthogonal partial least-squares discriminant analysis was applied to identify disease-specific glycomic patterns.ResultsDistinct N-glycome profiles were identified across diseases and phenotypes. Plasma N-glycans differentiated MS from Ab-defined diseases with 80.5% accuracy (±1.5%), MOGAD from AQP4-Ab NMOSD with 77.8% accuracy (±3.1%), and RRMS from SPMS with 75.2% accuracy (±3.6%). Key discriminatory features included increased monosialylation (S1; odds ratio [OR] = 2.57, p < 0.0001), trigalactosylation (G3; OR = 2.70, p < 0.0001), highly branched N-glycans (OR = 2.32, p = 0.0002), and antennary fucosylation (OR = 2.89, p < 0.0001), effectively distinguishing Ab-defined diseases from MS, independent of Ab serostatus at the time of sampling.DiscussionThese findings underscore the potential of plasma N-glycomics as a diagnostic tool for neuroinflammatory diseases. While further research is needed to clarify the mechanistic links between glycomic alterations and disease pathology, our results suggest that plasma N-glycan profiling could improve disease classification. Given its noninvasive and cost-effective nature, this approach holds promise as a complementary diagnostic tool for CNS demyelinating diseases in clinical practice.

Authors: Kacerova, T; Sealey, M; Saldana, L; Xiong, W; Woodhall, MR

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Lippincott, Williams & Wilkins
• Journal: Neurology, Neuroimmunology & Neuroinflammation
• Volume: 12
• Issue: 6
• Pages: e200502
• Publication date: 2025-10-16
• Acceptance date: 2025-08-21
• DOI: 10.1212/nxi.0000000000200502
• EISSN: 2332-7812
• ISSN: 2332-7812
• Pmid: 41100797
• Language: English
• Keywords: Multiple Sclerosis, Relapsing-Remitting; Multiple Sclerosis; Biomarkers; Polysaccharides; Neuromyelitis Optica; Multiple Sclerosis, Chronic Progressive; Male; Middle Aged; Adult; Diagnosis, Differential; Myelin Oligodendrocyte Glycoprotein Antibody-Associated Disease; Female; Aquaporin 4; Humans; Glycomics; Myelin-Oligodendrocyte Glycoprotein; Autoantibodies; Cohort Studies