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http://ki.se/en/imm/the-imse-studies-imse-i-and-imse-ii

Immunomodulatory drugs in multiple sclerosis (IMSE) is a nation-wide pharmacoepidemiological and genetic study on persons treated with Tysabri. The study focuses on response to treatment and development of neutralizing antibodies, and to perform large-scale genetic studies. Sample types * EDTA whole blood * DNA * Plasma Number of sample donors: 1293 (June 2010)

Proper citation: KI Biobank - IMSE (RRID:SCR_005899) Copy   

•   Source: SciCrunch Registry

http://www.ms-research.dk/genetics.htm

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. We have collected DNA for more than 15 years, and today we have DNA from more than 1,800 Danish MS patients and 1,200 controls, all kept in the Danish Multiple Sclerosis Biobank in DMSC. In order to increase the sample size for genetic testing, we have participated in the Nordic MS Genetic Network since 1994, and today the Nordic material consists of more than 6,000 MS cases and 6,000 controls. The research in DMSC is focused on the candidate gene approaches and the genetic influence on the differences in treatment response. We are part of the IMSGC (International Multiple Sclerosis Genetic Consortium) and the Wellcome Trust Case Control Consortium (WTCCC), where 23 research groups from 15 countries are performing the largest set of MS genome-wide association study (GWAS), genotyping 11,000 cases and 11,000 controls using 500,000 SNP chip. Primary results have elucidated associations to more than 100 gene variations (SNPs). Following this collaboration we are joining the Immunochip Consortium, where 1,000 Danish cases and 1,000 Danish controls participate in a large scale genetic analysis, investigating best genes/regions/SNPs in MS together with other international MS research groups and 9 other autoimmune diseases research groups, looking for shared autoimmune genes. The risk of MS has been increasing over the last 50 years, especially among women older than 40 years. On this background we have initiated a project looking at aspects of gender differences, including different treatment responses. Furthermore, we have initiated a large-scale vitamin D project, investigating gene variations within the vitamin D pathway, and the importance of vitamin D in clinical and immunological disease activity. In addition, we have collected more than 800 questionnaires from MS patients dealing in detail with lifestyle and environmental exposure for a project studying gene-environmental interactions.

Proper citation: Danish Multiple Sclerosis Biobank (RRID:SCR_000089) Copy   

•   Source: SciCrunch Registry

http://www.dna-network.ac.uk/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on October 6, 2011. A project to collect, store and study DNA samples from tens of thousands of healthy volunteers and patients with diseases of major public importance. It aims to identify genes that are risk factors for the conditions. The network consists of 13 collections led by different clinicians throughout the UK. At its heart is an archive infrastructure which manages the DNA and the information associated with it. The European Collection of Cell Cultures in Porton Down handles the blood, peripheral blood lymphocytes and EBV-transformed cell lines, while the Centre for Integrated Genomic Medical Research at Manchester University manages the DNA. These banked samples are available to UK and international researchers, who can examine data and set up collaborative work by registering at the DNA Network's website. The conditions for which samples are currently collected and stored are: Acute leukemia, Asthma and eczema, Late onset Alzheimer's disease, Breast cancer, Colorectal cancer, Coronary artery disease, Glomerulonephritis, Hypertension, Age-related macular degeneration, Multiple sclerosis, Parkinson's disease, Type 2 diabetes, Unipolar depression.

Proper citation: UK DNA Banking Network (RRID:SCR_010619) Copy   

•   Source: SciCrunch Registry

http://jjwanglab.org/gwasrap

GWASrap is a comprehensive web-based bioinformatics tool to systematically support variant representation, annotation and prioritization for data generated from genome-wide association studies (GWAS) and Next Generation Sequencing (NGS). Our web-based framework utilizes state-of-the-art web technologies to maximize user interaction and visualization of the results. For a given SNP dataset with its P-values, GWASrap will first provide a Circos-style plot to visualize any genetic variants at either the genome or chromosome level. The tool then combines different genomic features (SNP/CNV density, disease susceptibility loci, etc.) with comprehensive annotations that give the researcher an intuitive view of the functional significance of the different genomic regions. The detailed statistics of the underlying study are also displayed on the web page, including variant distribution in different functional categories, classic Manhattan plot and QQ plot. Users can perform interactive operations in the Manhattan panel, such as zooming in and out to search regions or markers of interest. The system can also display a comprehensive range of relevant information from variant genetic attributes to nearby genomic elements, such as enhancers or non-coding RNAs. Furthermore, researchers can obtain extensive functional predictions for various features including transcription factor-binding sites, miRNA and miRNA target sites, and their predicted changes caused by the genetic variants. Our system can re-prioritize genetic variants by combining the original statistical value and variant prioritization score based on a simple additive effect equation. Researchers can also re-evaluate the significance of a trait/disease-associated SNP (TAS) using the dynamic linkage disequilibrium (LD) panel or the tree-like network panel. The GWASrap supports input variants in different formats, not only common variants with a dbSNP rs ID but also rare variants from NGS data, which are represented by chromosome and locations. GWASrap provides a range of web services for data retrieving about the annotation information and effect prediction of each variant in dbSNP using the SOAP interface. The WSDL for each service is available in the API tab. Each service returns JSON string including all related information with key/value. GWASrap provides running results about some current published GWAS as well as a category view for each hot disease / trait. The dataset is brought from published database GWAS or curated from literature.

Proper citation: GWASrap (RRID:SCR_013144) Copy   

•   Source: SciCrunch Registry

http://www.polygenicpathways.co.uk

Database of disease genes and risk factors and of host pathogen/interactomes. Lists genes, pathways and environmental risk factors positively associated with diseases and conditions such as Alzheimer's disease, schizophrenia, multiple sclerosis, childhood obesity, anorexia nervosa, HIV-1/AIDS, and helicobacter pylori. Details of polymorphisms as well as negative/positive association data can be found via Useful links. Throughout the site are links to Entrez Gene and Pubmed.

Proper citation: Polygenic Pathways (RRID:SCR_006962) Copy   

•   Source: SciCrunch Registry

http://ranchobiosciences.com/gse13732/

Curated data set from a study that developed biomarkers that may predict development of Clinically Isolated Syndrome (CIS) into a full multiple sclerosis. Expression data was taken from 37 CIS patients and 28 healthy controls at baseline. 34 CIS patients and 10 healthy controls were resampled at a second time point, approximately one year later. Patients were followed clinically for up to two years to determine the TTC (time to conversion to MS).

Proper citation: GSE13732 (RRID:SCR_003648) Copy   

•   Source: SciCrunch Registry