PT - JOURNAL ARTICLE AU - Yeo, Tianrong AU - Probert, Fay AU - Jurynczyk, Maciej AU - Sealey, Megan AU - Cavey, Ana AU - Claridge, Timothy D.W. AU - Woodhall, Mark AU - Waters, Patrick AU - Leite, Maria Isabel AU - Anthony, Daniel C. AU - Palace, Jacqueline TI - Classifying the antibody-negative NMO syndromes AID - 10.1212/NXI.0000000000000626 DP - 2019 Nov 01 TA - Neurology - Neuroimmunology Neuroinflammation PG - e626 VI - 6 IP - 6 4099 - http://nn.neurology.org/content/6/6/e626.short 4100 - http://nn.neurology.org/content/6/6/e626.full SO - Neurol Neuroimmunol Neuroinflamm2019 Nov 01; 6 AB - Objective To determine whether unsupervised principal component analysis (PCA) of comprehensive clinico-radiologic data can identify phenotypic subgroups within antibody-negative patients with overlapping features of multiple sclerosis (MS) and neuromyelitis optica spectrum disorders (NMOSDs), and to validate the phenotypic classifications using high-resolution nuclear magnetic resonance (NMR) plasma metabolomics with inference to underlying pathologies.Methods Forty-one antibody-negative patients were recruited from the Oxford NMO Service. Thirty-six clinico-radiologic parameters, focusing on features known to distinguish NMOSD and MS, were collected to build an unbiased PCA model identifying phenotypic subgroups within antibody-negative patients. Metabolomics data from patients with relapsing-remitting MS (RRMS) (n = 34) and antibody-positive NMOSD (Ab-NMOSD) (aquaporin-4 antibody n = 54, myelin oligodendrocyte glycoprotein antibody n = 20) were used to identify discriminatory plasma metabolites separating RRMS and Ab-NMOSD.Results PCA of the 36 clinico-radiologic parameters revealed 3 phenotypic subgroups within antibody-negative patients: an MS-like subgroup, an NMOSD-like subgroup, and a low brain lesion subgroup. Supervised multivariate analysis of metabolomics data from patients with RRMS and Ab-NMOSD identified myoinositol and formate as the most discriminatory metabolites (both higher in RRMS). Within antibody-negative patients, myoinositol and formate were significantly higher in the MS-like vs NMOSD-like subgroup; myoinositol (mean [SD], 0.0023 [0.0002] vs 0.0019 [0.0003] arbitrary units [AU]; p = 0.041); formate (0.0027 [0.0006] vs 0.0019 [0.0006] AU; p = 0.010) (AU).Conclusions PCA identifies 3 phenotypic subgroups within antibody-negative patients and that the metabolite discriminators of RRMS and Ab-NMOSD suggest that these groupings have some pathogenic meaning. Thus, the identified clinico-radiologic discriminators may provide useful diagnostic clues when seeing antibody-negative patients in the clinic.Ab-NMOSD=antibody-positive NMOSD; ANOVA=analysis of variance; AQP4-Ab=aquaporin-4 antibody; AU=arbitrary units; AUC=area under the curve; CPMG=Carr-Purcell-Meiboom-Gill; LBL=low brain lesion; MOG-Ab=myelin oligodendrocyte glycoprotein antibody; MRS=magnetic resonance spectroscopy; NMOSD=neuromyelitis optica spectrum disorders; OPLS-DA=orthogonal partial least square discriminant analysis; PCA=principal component analysis; ppm=parts per million; RRMS=relapsing-remitting MS; VIP=variable importance in projection