gMS-Classifier1 does not predict disability progression in multiple sclerosis.

Several clinical, immunological and radiological biomarkers have been shown to predict the disease course of multiple sclerosis (MS).[1-5] One potential serum marker is the gMS-Classifier1, which is composed of IgM anti-Glc antibodies, namely anti-GAGA 2,3,4 and 6. Previous work demonstrated that the gMS-Classifier1 could not predict early conversion to clinically definite MS in a cohort of clinically isolated syndrome (CIS) patients, but predicted Expanded Disability Status Scale (EDSS) progression. Significance, however, was dependent on covariates, and confirmation in an independent study was required.[3]

The aim of this study was to test if the gMS-Classifier1 could predict early disability progression in a large multicenter cohort of patients with CIS or relapse-onset MS.

Blood samples and clinical data were prospectively collected in four MS centers between 1993 and 2007: The Ottawa Hospital, Ottawa, Canada; Amsterdam University Medical Centers, the Netherlands; UMass Memorial Medical Center, Worcester, USA; and Hospital Ramón y Cajal, Madrid, Spain. Patients had a diagnosis of CIS (n = 118) or relapsing remitting multiple sclerosis (RRMS; n = 240) at study onset. Age at blood sampling was between 18 and 50 years. Serum samples were stored frozen <–70°C until assayed.

Baseline (EDSS) was performed within 6 months of blood sampling and was repeated during patient routine visits. Disability progression was defined as a sustained (⩾6 months) progression of at least 1.0 EDSS point over the baseline EDSS and progression to an EDSS score of 3.0 or higher.

Mean follow-up was 94 months.

In 2012, frozen serum samples were shipped to Glycominds Inc Lab (Simi Valley, CA, USA) for testing for anti-glycan antibodies as described before.[3] If one of the antibodies was above the predefined cut-off (anti-GAGA2 >148.8 EIA units, anti-GAGA3 >164.6 EIA units, anti-GAGA4 >133.6 EIA units, and anti-GAGA6 >168.1 EIA units), patients were considered positive for the gMS-Classifier1. There were no significant differences for the key variables gMS-Classifier1 and EDSS progression between the four centers.

Of the 358 patients, 44 (12.3%) were gMS-Classifier1 status positive. EDSS progression was available for 355 patients, of whom 158 (44.5%) had confirmed progression at the end of follow-up. The percentage of patients showing EDSS progression did not differ between the groups, using the 1 point EDSS progression definition (p = 0.587) or for EDSS progression above 3.0 (p = 0.771). There was no association between EDSS progression and the gMS-Classifier1 (p = 0.778) or positive titres for any of the separate antibodies (anti-GAGA2: p = 0.934, anti-GAGA3: p = 0.663, anti-GAGA4: p = 0.712, and anti-GAGA6: p = 0.440).

No statistical differences between the gMS-Classifier1 positive and negative group were observed for age (p = 0.631), disease duration (p = 0.147), gender (p = 0.154), baseline EDSS (p = 1.000), number of CIS patients at blood sampling (p = 0.865), follow-up time (p = 0.587), relapse at blood sampling (p = 0.771), and steroids at blood sampling (p = 1.000).

Here, we present the results of a large cohort of patients from different centers from two continents, showing no statistical differences between gMS-Classifier1 positive and negative patients, convincingly indicating that the gMS-Classifier1 does not predict disability progression in MS.