Predictive factors and early biomarkers of response in multiple sclerosis patients treated with natalizumab.

There are an increasing number of treatments available for multiple sclerosis (MS). The early identification of optimal responders to individual treatments is important to achieve individualized therapy. With this aim, we performed a multicenter retrospective longitudinal study including 186 MS patients treated with natalizumab who were followed for 2 years. We analyzed the following variables at recruitment: sex, current age, age at disease onset, disease duration, EDSS, number of T2 and Gd + lesions, IgG and IgM oligoclonal bands, HLA class II (DR, DRB, DQA, DQB, and DRB1*15:01), IgG and IgM antibody titers against human herpesvirus 6 (HHV-6) and the antibody response to Epstein-Barr virus (EBV) through the measurement of the anti-EBNA-1 and anti-VCA IgG titers, in relation to clinical response (no relapses or disability progression), and to NEDA-3 (no evidence of disease activity in terms of clinical response and no changes in MRI scans either) after 2-years follow-up. Baseline EDSS score, baseline EBNA-1 IgG titers and percentage change of HHV6 IgG titers between baseline and 6 month visits were significantly different in clinical responders and in NEDA-3 status (all of them remained significant in the multivariate analysis). We identified three variables for the early identification of natalizumab optimal responders in a rapid and cost-effective approach.

Multimarker risk stratification approach at multiple sclerosis onset.

Delay in the diagnosis of multiple sclerosis (MS) stems from the lack of specific clinical and analytical markers to assist in the early diagnosis and prediction of progressive course. We propose a decision-tree model that better defines early at onset MS patients and those with the progressive form by analysing a 12-biomarkers panel in serum and CSF samples of patients with MS, other neurological diseases (OND) and healthy contols. Thus, patients at onset of neurological disease were first classified by serum IL-7 levels <141pg/ml (OR=6.51, p<0.001). Combination of IL-7 and CXCL10 indicated risk for a specific MS clinical form, where IL-7<141 and CXCL10<570pg/ml were associated with the highest risk for PP-MS (OR=22, p=0.01). Unexpectedly, both PP-MS and RR-MS patients shared significantly decreased prototypical biomarkers of inflammation and tissue regeneration in CSF than OND suggesting a defective intrinsic immune response playing a role at the beginning of the disease.

Protein-Based Classifier to Predict Conversion from Clinically Isolated Syndrome to Multiple Sclerosis.

Multiple sclerosis is an inflammatory, demyelinating, and neurodegenerative disease of the central nervous system. In most patients, the disease initiates with an episode of neurological disturbance referred to as clinically isolated syndrome, but not all patients with this syndrome develop multiple sclerosis over time, and currently, there is no clinical test that can conclusively establish whether a patient with a clinically isolated syndrome will eventually develop clinically defined multiple sclerosis. Here, we took advantage of the capabilities of targeted mass spectrometry to establish a diagnostic molecular classifier with high sensitivity and specificity able to differentiate between clinically isolated syndrome patients with a high and a low risk of developing multiple sclerosis. Based on the combination of abundances of proteins chitinase 3-like 1 and ala-ß-his-dipeptidase in cerebrospinal fluid, we built a statistical model able to assign to each patient a precise probability of conversion to clinically defined multiple sclerosis. Our results are of special relevance for patients affected by multiple sclerosis as early treatment can prevent brain damage and slow down the disease progression.

A functional variant that affects exon-skipping and protein expression of SP140 as genetic mechanism predisposing to multiple sclerosis.

Several variants in strong linkage disequilibrium (LD) at the SP140 locus have been associated with multiple sclerosis (MS), Crohn's disease (CD) and chronic lymphocytic leukemia (CLL). To determine the causal polymorphism, we have integrated high-density data sets of expression quantitative trait loci (eQTL), using GEUVADIS RNA sequences and 1000 Genomes genotypes, with MS-risk variants of the high-density Immunochip array performed by the International Multiple Sclerosis Genetic Consortium (IMSGC). The variants most associated with MS were also correlated with a decreased expression of the full-length RNA isoform of SP140 and an increase of an isoform lacking exon 7. By exon splicing assay, we have demonstrated that the rs28445040 variant was the causal factor for skipping of exon 7. Western blots of peripheral blood mononuclear cells from MS patients showed a significant allele-dependent reduction of the SP140 protein expression. To confirm the association of this functional variant with MS and to compare it with the best-associated variant previously reported by GWAS (rs10201872), a case-control study including 4384 MS patients and 3197 controls was performed. Both variants, in strong LD (r(2) = 0.93), were found similarly associated with MS [P-values, odds ratios: 1.9E-9, OR = 1.35 (1.22-1.49) and 4.9E-10, OR = 1.37 (1.24-1.51), respectively]. In conclusion, our data uncover the causal variant for the SP140 locus and the molecular mechanism associated with MS risk. In addition, this study and others previously reported strongly suggest that this functional variant may be shared with other immune-mediated diseases as CD and CLL.