The Ulcerative Colitis Response Index for Detection of Mucosal Healing in Patients Treated With Anti-tumour Necrosis Factor.

BACKGROUND: Surrogate markers that accurately detect mucosal healing [MH] in patients with ulcerative colitis [UC] are urgently needed. Several stool neutrophil-related proteins are currently used as biomarkers for MH. However, the sensitivity and specificity are not sufficient to avoid unnecessary endoscopic evaluations. METHODS: Novel serum neutrophil-related markers (neutrophil gelatinase B-associated lipocalin and matrix metalloproteinase-9 [NGAL-MMP-9 complex], cathelicidin LL-37 and chitinase 3-like 1 [CHI3L1]), together with C-reactive protein [CRP] and neutrophil counts were studied. Serum samples were obtained from 176 anti-tumour necrosis factor [anti-TNF]-treated UC patients (145 infliximab [IFX] and 31 adalimumab [ADM]) at baseline and after a median of 9.5 weeks. All patients had active disease prior to treatment (Mayo endoscopic subscore [MES] ≥ 2), and MH was defined as MES ≤ 1. Serum was also obtained from 75 healthy controls. Binary logistic regression analysis was used to generate the Ulcerative Colitis Response Index [UCRI]. The performance of individual markers and UCRI was tested with receiver operating characteristic analysis. RESULTS: All neutrophil-related markers were significantly higher in active UC patients compared to healthy controls. In the IFX cohort, CRP, NGAL-MMP-9, CHI3L1 and neutrophil count decreased significantly after treatment and all marker levels were significantly lower in healers compared to non-healers following IFX. In the ADM cohort, CRP, NGAL-MMP-9, CHI3L1 and neutrophil count decreased significantly only in healers. UCRI [including CRP, CHI3L1, neutrophil count and LL-37] accurately detected MH in both IFX-treated (area under the curve [AUC] = 0.83) and ADM-treated [AUC = 0.79] patients. CONCLUSIONS: The new UCRI index accurately detects MH after treatment with IFX and ADM. This panel is useful for monitoring MH in UC patients under anti-TNF treatment. PODCAST: This article has an associated podcast which can be accessed at https://academic.oup.com/ecco-jcc/pages/podcast.

Serum biomarker gMS-Classifier2: predicting conversion to clinically definite multiple sclerosis.

BACKGROUND: Anti-glycan antibodies can be found in autoimmune diseases. IgM against glycan P63 was identified in clinically isolated syndromes (CIS) and included in gMS-Classifier2, an algorithm designed with the aim of identifying patients at risk of a second demyelinating attack. OBJECTIVE: To determine the value of gMS-Classifier2 as an early and independent predictor of conversion to clinically definite multiple sclerosis (CDMS). METHODS: Data were prospectively acquired from a CIS cohort. gMS-Classifier2 was determined in patients first seen between 1995 and 2007 with ≥ two 200 µL serum aliquots (N = 249). The primary endpoint was time to conversion to CDMS at two years, the factor tested was gMS-Classifier2 status (positive/negative) or units; other exploratory time points were 5 years and total time of follow-up. RESULTS: Seventy-five patients (30.1%) were gMS-Classifier2 positive. Conversion to CDMS occurred in 31/75 (41.3%) of positive and 45/174 (25.9%) of negative patients (p = 0.017) at two years. Median time to CDMS was 37.8 months (95% CI 10.4-65.3) for positive and 83.9 months (95% CI 57.5-110.5) for negative patients. gMS-Classifier2 status predicted conversion to CDMS within two years of follow-up (HR = 1.8, 95% CI 1.1-2.8; p = 0.014). gMS-Classifier2 units were also independent predictors when tested with either Barkhof criteria and OCB (HR = 1.2, CI 1.0-1.5, p = 0.020) or with T2 lesions and OCB (HR = 1.3, CI 1.1-1.5, p = 0.008). Similar results were obtained at 5 years of follow-up. Discrimination measures showed a significant change in the area under the curve (ΔAUC) when adding gMS-Classifier2 to a model with either Barkhof criteria (ΔAUC 0.0415, p = 0.012) or number of T2 lesions (ΔAUC 0.0467, p = 0.009), but not when OCB were added to these models. CONCLUSIONS: gMS-Classifier2 is an independent predictor of early conversion to CDMS and could be of clinical relevance, particularly in cases in which OCB are not available.

A new kind of carbohydrate array, its use for profiling antiglycan antibodies, and the discovery of a novel human cellulose-binding antibody.

In this study, we use a novel glycan array to analyze the glycan-binding antibody repertoire in a pool of affinity-purified IgG collected from a healthy human population. The glycan array used is based on mono- and oligosaccharides covalently linked to the surface via a long linker at their reducing ends. They are thus presented to the medium with a well-defined orientation and are accessible for specific binding by glycan-binding proteins, such as antibodies and lectins. A novel anticellulose antibody was detected that binds specifically to beta4-linked saccharides with a preference for glucopyranose over galactopyranose residues. We also found previously known antiglycan antibodies against mono- and oligosaccharides that are constituents of commonly occurring bacterial polysaccharides. We propose that this array can facilitate high-throughput screening of glycan-binding proteins and the search for biomarkers for personalized medicine.