Anti-α-glucose–based glycan IgM antibodies predict relapse activity in multiple sclerosis after the first neurological event

Abstract

BackgroundThere is no specific serum-based biomarker for the diagnosis or prognosis of relapsing-remitting multiple sclerosis (RRMS).ObjectiveWe investigated whether levels of IgM antibodies to Glc(α1,4)Glc(α) (GAGA4) or to a panel of four glucose-based glycans could differentiate MS from other neurological diseases (OND) or predict risk of early relapse following first presentation (FP) of RRMS.MethodsRetrospective analysis of 440 sera samples of three cohorts: A) FP-RRMS (n = 44), OND (n = 44); B) FP-RRMS (n = 167), OND (n = 85); and C) FP (n = 100). Anti-GAGA4 IgM levels were measured by enzyme immunoassay in cohort-A and cohort-B. Cohort-C IgM antibodies to glucosebased glycan panel were measured by immunofluorescence.ResultsFP-RRMS had higher levels of anti-GAGA4 IgM than OND patients (cohort-A, P = 0.01; cohort-B, P = 0.0001). Sensitivity and specificity were 27% and 97% for cohort-A; and 26% and 90% for cohort-B, respectively. In cohort-C, 58 patients experienced early relapse (<24 months), 31 had late relapse (≥24 months), and 11 did not experience second attack during follow-up. Kaplan– Meier curves demonstrated decrease in time to next relapse for patients positive for the antibody panel (P = 0.02, log rank).ConclusionsSerum anti-GAGA4 IgM discerns FP-RRMS patients from OND patients. Higher levels of serum anti-α-glucose IgM in FP patients predict imminent early relapse.

Construction and Use of Glycan Microarrays

“…These arrays are beginning to provide new insights into the many biological processes influenced by glycosylation. So far, the applications of glycan microarrays include characterizing binding properties of monoclonal antibodies and lectins [for some recent examples, see (Blixt et al, 2008a; Manimala et al, 2006; Manimala et al, 2007; Schallus et al, 2008; Song et al, 2009)], defining substrate specificities of glycosyltransferases (Ban and Mrksich, 2008; Park and Shin, 2007), as well as measuring antibody titers against tumors (Wang et al, 2008), pathogens (Blixt et al, 2008b; Kamena et al, 2008; Parthasarathy et al, 2008) and autoantigens (Freedman et al, 2009; Seow et al, 2009). As glycan microarrays become more widely accessible, their application will likely be extended to new problems.…”

Predictive nature of IgM anti-α-glucose serum biomarker for relapse activity and EDSS progression in CIS patients: a BENEFIT study analysis

“…In BENEFIT, as in the previous study, 16 a diagnosis of CDMS was based on the occurrence of a second clinical event (i.e. first relapse).…”

“…15 More recently, higher levels of at least one of a panel of anti-GAGA IgM antibodies (GAGA2, 3, 4, and 6), gMS-Classifier1, were more frequently observed in patients experiencing their first neurologic event and who were more likely to have a more rapid first relapse, which would establish the diagnosis of RRMS within 48 months (clinically definite MS [CDMS]), thus potentially serving as both a diagnostic and more importantly early prognostic marker for disease activity. 16 …”

Utility of Autoantibodies as Biomarkers for Diagnosis and Staging of Neurodegenerative Diseases

“…In addition, anti-GAGA4 antibodies were shown to differentiate patients with RRMS from those with the secondary progressive form of MS (Brettschneider et al, 2009). Similarly, high titers of anti-α-glucose IgM have been reported to be predictive of imminent relapse in first presentation MS patients (Freedman et al, 2009).…”