Identification of MS-specific serum miRNAs in an international multicenter study.

ObjectiveTo identify circulating microRNAs (miRNAs) linked to disease, disease stage, and disability in MS across cohorts.MethodsSamples were obtained from the Comprehensive Longitudinal Investigation of Multiple Sclerosis (CLIMB, Boston, MA), EPIC (San Francisco, CA), AMIR (Beirut, Lebanon) as part of the SUMMIT consortium, and Stockholm Prospective Assessment of Multiple Sclerosis (Stockholm, Sweden) cohorts. Serum miRNA expression was measured using locked nucleic acid-based quantitative PCR. Four groups were compared: (1) MS vs healthy control (HC), (2) relapsing-remitting (RR) vs HC, (3) secondary progressive (SP) vs HC, and (4) RR vs SP. A Wilcoxon rank-sum test was used for the comparisons. The association between each miRNA and the Expanded Disability Status Scale (EDSS) score was assessed using the Spearman correlation coefficient. For each comparison, the p values were corrected for multiple comparisons using the approach of Benjamini and Hochberg to control the false discovery rate.ResultsIn the CLIMB cohort, 5 miRNAs (hsa-miR-484, hsa-miR-140-5p, hsa-miR-320a, hsa-miR-486-5p, and hsa-miR-320c) showed a significant difference between patients with MS and healthy individuals; among these, miR-484 remained significant after accounting for multiple comparisons (p = 0.01). When comparing RRMS with HCs, hsa-miR-484 showed a significant difference (p = 0.004) between the groups after accounting for multiple group comparisons. When SP and HC were compared, 6 miRNAs (hsa-miR-484, hsa-miR-140-5p, hsa-miR-142-5p, hsa-miR-320a, hsa-miR-320b, and hsa-miR-320c) remained significantly different after accounting for multiple comparisons. Disability correlation analysis with miRNA provided 4 miRNAs (hsa-miR-320a, hsa-miR-337-3p, hsa-miR-199a-5p, and hsa-miR-142-5p) that correlated with the EDSS during the internal reproducibility phase. Among these, hsa-miR-337-3p was the most statistically significant miRNA that negatively correlated with the EDSS in three of the MS cohorts tested.ConclusionsThese findings further confirm the use of circulating serum miRNAs as biomarkers to diagnose and monitor disease status in MS.Classification of evidenceThis study provides Class III evidence that levels of circulating miRNAs identify patients with MS

A specific amino acid motif of HLA-DRB1 mediates risk and interacts with smoking history in Parkinson's disease.

Parkinson's disease (PD) is a neurodegenerative disease in which genetic risk has been mapped to HLA, but precise allelic associations have been difficult to infer due to limitations in genotyping methodology. Mapping PD risk at highest possible resolution, we performed sequencing of 11 HLA genes in 1,597 PD cases and 1,606 controls. We found that susceptibility to PD can be explained by a specific combination of amino acids at positions 70-74 on the HLA-DRB1 molecule. Previously identified as the primary risk factor in rheumatoid arthritis and referred to as the "shared epitope" (SE), the residues Q/R-K/R-R-A-A at positions 70-74 in combination with valine at position 11 (11-V) is highly protective in PD, while risk is attributable to the identical epitope in the absence of 11-V. Notably, these effects are modified by history of cigarette smoking, with a strong protective effect mediated by a positive history of smoking in combination with the SE and 11-V (P = 10-4; odds ratio, 0.51; 95% confidence interval, 0.36-0.72) and risk attributable to never smoking in combination with the SE without 11-V (P = 0.01; odds ratio, 1.51; 95% confidence interval, 1.08-2.12). The association of specific combinations of amino acids that participate in critical peptide-binding pockets of the HLA class II molecule implicates antigen presentation in PD pathogenesis and provides further support for genetic control of neuroinflammation in disease. The interaction of HLA-DRB1 with smoking history in disease predisposition, along with predicted patterns of peptide binding to HLA, provide a molecular model that explains the unique epidemiology of smoking in PD

SNPs in Multi-Species Conserved Sequences (MCS) as useful markers in association studies: a practical approach

<p>Abstract</p> <p>Background</p> <p>Although genes play a key role in many complex diseases, the specific genes involved in most complex diseases remain largely unidentified. Their discovery will hinge on the identification of key sequence variants that are conclusively associated with disease. While much attention has been focused on variants in protein-coding DNA, variants in noncoding regions may also play many important roles in complex disease by altering gene regulation. Since the vast majority of noncoding genomic sequence is of unknown function, this increases the challenge of identifying "functional" variants that cause disease. However, evolutionary conservation can be used as a guide to indicate regions of noncoding or coding DNA that are likely to have biological function, and thus may be more likely to harbor SNP variants with functional consequences. To help bias marker selection in favor of such variants, we devised a process that prioritizes annotated SNPs for genotyping studies based on their location within Multi-species Conserved Sequences (MCSs) and used this process to select SNPs in a region of linkage to a complex disease. This allowed us to evaluate the utility of the chosen SNPs for further association studies. Previously, a region of chromosome 1q43 was linked to Multiple Sclerosis (MS) in a genome-wide screen. We chose annotated SNPs in the region based on location within MCSs (termed MCS-SNPs). We then obtained genotypes for 478 MCS-SNPs in 989 individuals from MS families.</p> <p>Results</p> <p>Analysis of our MCS-SNP genotypes from the 1q43 region and comparison to HapMap data confirmed that annotated SNPs in MCS regions are frequently polymorphic and show subtle signatures of selective pressure, consistent with previous reports of genome-wide variation in conserved regions. We also present an online tool that allows MCS data to be directly exported to the UCSC genome browser so that MCS-SNPs can be easily identified within genomic regions of interest.</p> <p>Conclusion</p> <p>Our results showed that MCS can easily be used to prioritize markers for follow-up and candidate gene association studies. We believe that this novel approach demonstrates a paradigm for expediting the search for genes contributing to complex diseases.</p

Modeling the cumulative genetic risk for multiple sclerosis from genome-wide association data

Background: Multiple sclerosis (MS) is the most common cause of chronic neurologic disability beginning in early to middle adult life. Results from recent genome-wide association studies (GWAS) have substantially lengthened the list of disease loci and provide convincing evidence supporting a multifactorial and polygenic model of inheritance. Nevertheless, the knowledge of MS genetics remains incomplete, with many risk alleles still to be revealed. Methods: We used a discovery GWAS dataset (8,844 samples, 2,124 cases and 6,720 controls) and a multi-step logistic regression protocol to identify novel genetic associations. The emerging genetic profile included 350 independent markers and was used to calculate and estimate the cumulative genetic risk in an independent validation dataset (3,606 samples). Analysis of covariance (ANCOVA) was implemented to compare clinical characteristics of individuals with various degrees of genetic risk. Gene ontology and pathway enrichment analysis was done using the DAVID functional annotation tool, the GO Tree Machine, and the Pathway-Express profiling tool. Results: In the discovery dataset, the median cumulative genetic risk (P-Hat) was 0.903 and 0.007 in the case and control groups, respectively, together with 79.9% classification sensitivity and 95.8% specificity. The identified profile shows a significant enrichment of genes involved in the immune response, cell adhesion, cell communication/ signaling, nervous system development, and neuronal signaling, including ionotropic glutamate receptors, which have been implicated in the pathological mechanism driving neurodegeneration. In the validation dataset, the median cumulative genetic risk was 0.59 and 0.32 in the case and control groups, respectively, with classification sensitivity 62.3% and specificity 75.9%. No differences in disease progression or T2-lesion volumes were observed among four levels of predicted genetic risk groups (high, medium, low, misclassified). On the other hand, a significant difference (F = 2.75, P = 0.04) was detected for age of disease onset between the affected misclassified as controls (mean = 36 years) and the other three groups (high, 33.5 years; medium, 33.4 years; low, 33.1 years). Conclusions: The results are consistent with the polygenic model of inheritance. The cumulative genetic risk established using currently available genome-wide association data provides important insights into disease heterogeneity and completeness of current knowledge in MS genetics

Cognitive interviewing techniques used in developing questionnaires on functional electrical stimulation in spinal cord injury

© 2016 MA Healthcare Ltd. Background/Aims: This paper illustrates the application of a technique, cognitive interviewing, which was used in the development of three questionnaires to determine the views of use of functional electrical stimulation by people with spinal cord injury, health care professionals and researchers working in spinal cord injury. Methods: Three questionnaires for the three populations were developed in order to explore views about the current and future use of functional electrical stimulation. The questionnaires were reviewed and discussed by the team. Cognitive interviews were carried out at participants’ homes, university or workplace and each interview lasted a mean time of 65 minutes. The interviewer used ‘think aloud’ techniques. They were transcribed and analysed using content analysis. Results: Twelve participants (four people with spinal cord injury, four health care professionals and four researchers) from across the United Kingdom took part. The process identified several areas for modification, including clarification of words, format and legibility of questions, changes to sections, and the layout of the questionnaires. Conclusions: Cognitive interviewing ensured that the questionnaires were readable, clear and relevant, unambiguous and related to current clinical practice and research. The technique resulted in good quality questionnaires with enhanced patient-centred language

Evidence of novel finescale structural variation at autism spectrum disorder candidate loci

Background: Autism spectrum disorders (ASD) represent a group of neurodevelopmental disorders characterized by a core set of social-communicative and behavioral impairments. Gamma-aminobutyric acid (GABA) is the major inhibitory neurotransmitter in the brain, acting primarily via the GABA receptors (GABR). Multiple lines of evidence, including altered GABA and GABA receptor expression in autistic patients, indicate that the GABAergic system may be involved in the etiology of autism. Methods: As copy number variations (CNVs), particularly rare and de novo CNVs, have now been implicated in ASD risk, we examined the GABA receptors and genes in related pathways for structural variation that may be associated with autism. We further extended our candidate gene set to include 19 genes and regions that had either been directly implicated in the autism literature or were directly related (via function or ancestry) to these primary candidates. For the high resolution CNV screen we employed custom-designed 244 k comparative genomic hybridization (CGH) arrays. Collectively, our probes spanned a total of 11 Mb of GABA-related and additional candidate regions with a density of approximately one probe every 200 nucleotides, allowing a theoretical resolution for detection of CNVs of approximately 1 kb or greater on average. One hundred and sixty-eight autism cases and 149 control individuals were screened for structural variants. Prioritized CNV events were confirmed using quantitative PCR, and confirmed loci were evaluated on an additional set of 170 cases and 170 control individuals that were not included in the original discovery set. Loci that remained interesting were subsequently screened via quantitative PCR on an additional set of 755 cases and 1,809 unaffected family members. Results: Results include rare deletions in autistic individuals at JAKMIP1, NRXN1, Neuroligin4Y, OXTR, and ABAT. Common insertion/deletion polymorphisms were detected at several loci, including GABBR2 and NRXN3. Overall, statistically significant enrichment in affected vs. unaffected individuals was observed for NRXN1 deletions. Conclusions: These results provide additional support for the role of rare structural variation in ASD