Association of Genetic Markers with CSF Oligoclonal Bands in Multiple Sclerosis Patients

Objective:to explore the association between genetic markers and Oligoclonal Bands (OCB) in the Cerebro Spinal Fluid (CSF) of Italian Multiple Sclerosis patients.Methods:We genotyped 1115 Italian patients for HLA-DRB1*15 and HLA-A*02. In a subset of 925 patients we tested association with 52 non-HLA SNPs associated with MS susceptibility and we calculated a weighted Genetic Risk Score. Finally, we performed a Genome Wide Association Study (GWAS) with OCB status on a subset of 562 patients. The best associated SNPs of the Italian GWAS were replicated in silico in Scandinavian and Belgian populations, and meta-analyzed.Results:HLA-DRB1*15 is associated with OCB+: p = 0.03, Odds Ratio (OR) = 1.6, 95% Confidence Limits (CL) = 1.1-2.4. None of the 52 non-HLA MS susceptibility loci was associated with OCB, except one SNP (rs2546890) near IL12B gene (OR: 1.45; 1.09-1.92). The weighted Genetic Risk Score mean was significantly (p = 0.0008) higher in OCB+ (7.668) than in OCB- (7.412) patients. After meta-analysis on the three datasets (Italian, Scandinavian and Belgian) for the best associated signals resulted from the Italian GWAS, the strongest signal was a SNP (rs9320598) on chromosome 6q (p = 9.4×10-7) outside the HLA region (65 Mb).Discussion:genetic factors predispose to the development of OCB

Multiple sclerosis progression is not associated with birth timing in Italy

Background Month of birth has been associated in some studies with the susceptibility to develop Multiple Sclerosis (MS). However, only few studies have evaluated whether birth timing also affects disease progression. Objectives To assess whether season and month of birth are associated with disease progression in a large cohort of Italian patients. Methods Quantile regression was used to analyze the impact of each month and season of birth with all the others combined on the median Multiple Sclerosis Severity Score of 1866 MS patients. Results No significant temporal trend was found after adjustment for multiple comparisons. Conclusions Birth timing showed no association with MS progression in Italian patients

Potential Role of Gut Microbiota in ALS Pathogenesis and Possible Novel Therapeutic Strategies

Recent preclinical studies suggest that dysfunction of gastrointestinal tract may play a role in amyotrophic lateral sclerosis (ALS) pathogenesis through a modification of the gut microbiota brain axis. Our study is the first focused on microbiota analysis in ALS patients

Data from: A reliability study of colour-Doppler sonography for the diagnosis of chronic cerebrospinal venous insufficiency shows low inter-rater agreement

Objective: Chronic cerebrospinal venous insufficiency (CCSVI) has been extremely variable associated with multiple sclerosis in color-Doppler sonographic studies. We aimed to evaluate inter-rater agreement in color doppler sonograpy venous examination. Design: Inter-rater agreement study. Setting: First-referral multiple sclerosis centre. Participants: thirty-eight multiple sclerosis patients, and 55 age-matched (± 5 years) controls. Intervention: sonography was carried out in accordance with Zamboni's five criteria by 8 sonographers with different expertise, blinded to the status of cases and controls. Each subject was evaluated by two operators. Primary and secondary outcome measures: inter-rater agreement was measured through the Kappa statistics and the Intraclass Correlation Coefficient. Results: The agreement was no higher than chance for criterion 2-reflux in the deep cerebral veins (Kappa=-0.02) and 4-flow not Doppler-detectable in one or both the internal jugular (IJVs) or vertebral veins (VVs) (-0.09). It was substantially low for criterion 1-reflux in the IJVs and/or VVs (0.29), criterion 3-IJV stenosis or malformations (0.23), and criterion 5-absence of IJV diameter increase when passing from sitting to supine position (0.22). The Kappa value for CCSVI as a whole was 0.20 (95% confidence limits=-0.01 - 0.42). Intraclass Correlation Coefficients for the measure of cross-sectional area ranged from 0.05 to 0.25. Inter-rater agreement was low for CCSVI experts (kappa= 0.24; -0.11 to 0.59), and non-experts (0.20; -0.33 to 0.73); neurologists (0.21; -0.06 to 0.47) and non neurologists (0.18; -0.20 to 0.56); cases (0.19; -0.14 to 0.52) and controls (0.21; -0.08 to 0.49). Zamboni-trained neurosonographers ascertained CCSVI more frequently than non-trained. Conclusions: Agreement was unsatisfactory for the diagnosis of CCSVI as a whole, for each of its five criteria, and according to different subgroups. Standardization of the method is urgently needed prior to its further application in studies of patients with multiple sclerosis or other neurological diseases

Leone_CCSVI

The filke contains data about 38 multiple sclerosis patients and 55 age-matched (± 5 years) controls. Each subject (case or control) has been evaluated with color-Doppler sonography by two operators (column headline= alpha or beta) in accordance with Zamboni's five criteria (column headline=criterion1 to criterion5). The file contains additional data on smoke and the presence of varicous veins at lower limbs

Association of Genetic Markers with CSF Oligoclonal Bands in Multiple Sclerosis Patients

<div><p>Objective</p><p>to explore the association between genetic markers and Oligoclonal Bands (OCB) in the Cerebro Spinal Fluid (CSF) of Italian Multiple Sclerosis patients.</p><p>Methods</p><p>We genotyped 1115 Italian patients for <i>HLA-DRB1*15</i> and <i>HLA-A*02</i>. In a subset of 925 patients we tested association with 52 non-HLA SNPs associated with MS susceptibility and we calculated a weighted Genetic Risk Score. Finally, we performed a Genome Wide Association Study (GWAS) with OCB status on a subset of 562 patients. The best associated SNPs of the Italian GWAS were replicated <i>in silico</i> in Scandinavian and Belgian populations, and meta-analyzed.</p><p>Results</p><p>HLA-<i>DRB1*15</i> is associated with OCB+: p = 0.03, Odds Ratio (OR) = 1.6, 95% Confidence Limits (CL) = 1.1–2.4. None of the 52 non-HLA MS susceptibility loci was associated with OCB, except one SNP (rs2546890) near <i>IL12B</i> gene (OR: 1.45; 1.09–1.92). The weighted Genetic Risk Score mean was significantly (p = 0.0008) higher in OCB+ (7.668) than in OCB− (7.412) patients. After meta-analysis on the three datasets (Italian, Scandinavian and Belgian) for the best associated signals resulted from the Italian GWAS, the strongest signal was a SNP (rs9320598) on chromosome 6q (p = 9.4×10⁻⁷) outside the HLA region (65 Mb).</p><p>Discussion</p><p>genetic factors predispose to the development of OCB.</p></div

Distribution of the wGRS in MS patients positive (OCB+) or negative (OCB−) for OCB.

<p>wGRS (weighted Genetic Risk Score) has been calculated using the ORs for the 52 non-HLA MS susceptibility variants,⁶ and three HLA alleles (<i>DRB1*15, DRB1*03</i> and <i>A*02</i>). The reported p value derived from the comparison of the mean wGRS (Student's t test) in OCB+ vs OCB−.</p

Clinical characteristics of MS patients according to OCB status in the three populations.

<p><i>Abbreviations:</i><b>PP</b>  =  Primary Progressive, <b>OCB</b>  =  oligoclonal bands, <b>EDSS</b>  =  Expanded disability status scale, <b>MSSS</b>  =  Multiple sclerosis severity score.</p

Results of the GWAS for OCB status and meta-analysis after <i>in silico</i> replication.

<p>(<b>a</b>) Manhattan Plot of the GWAS performed in the Italian OCB+ vs OCB− MS patients, as a discovery dataset. The blue horizontal line indicates the threshold of p values arbitrarily chosen to select the “best associated SNPs” (p-value <10⁻⁴, 89 SNPs) to perform <i>in silico</i> replication (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0064408#pone.0064408.s002" target="_blank">Table S1</a>) using data from Scandinavia and Belgium populations. (<b>b</b>) Meta-analysis for the rs9320598 SNP, the strongest signal after the meta-analysis of the combined results of all datasets (Italy, Scandinavia and Belgium). The forest plot summarizes the results obtained for the discovery Italian dataset, for the replication datasets from Scandinavia and Belgium, and the combined analysis calculated using the random and fixed-effect method.</p