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dc.contributor.authorJames, Tojo
dc.contributor.authorLindén, Magdalena
dc.contributor.authorMorikawa, Hiromasa
dc.contributor.authorFernandes, Sunjay Jude
dc.contributor.authorRuhrmann, Sabrina
dc.contributor.authorHuss, Mikael
dc.contributor.authorBrandi, Maya
dc.contributor.authorPiehl, Fredrik
dc.contributor.authorJagodic, Maja
dc.contributor.authorTegner, Jesper
dc.contributor.authorKhademi, Mohsen
dc.contributor.authorOlsson, Tomas
dc.contributor.authorGomez-Cabrero, David
dc.contributor.authorKockum, Ingrid
dc.date.accessioned2018-01-15T06:10:40Z
dc.date.available2018-01-15T06:10:40Z
dc.date.issued2018-01-08
dc.identifier.citationJames T, Lindén M, Morikawa H, Fernandes SJ, Ruhrmann S, et al. (2018) Impact of genetic risk loci for multiple sclerosis on expression of proximal genes in patients. Human Molecular Genetics. Available: http://dx.doi.org/10.1093/hmg/ddy001.
dc.identifier.issn0964-6906
dc.identifier.issn1460-2083
dc.identifier.doi10.1093/hmg/ddy001
dc.identifier.urihttp://hdl.handle.net/10754/626756
dc.description.abstractDespite advancements in genetic studies, it is difficult to understand and characterize the functional relevance of disease-associated genetic variants, especially in the context of a complex multifactorial disease such as Multiple Sclerosis (MS). Since a large proportion of expression quantitative trait loci (eQTLs) are context-specific, we performed RNA-Seq in peripheral blood mononuclear cells (PBMCs) from MS patients (n=145) to identify eQTLs in regions centered on 109 MS risk SNPs and seven associated HLA variants. We identified 77 statistically significant eQTL associations, including pseudogenes and non-coding RNAs. Thirty-eight out of 40 testable eQTL effects were colocalised with the disease association signal. Since many eQTLs are tissue specific, we aimed to detail their significance in different cell types. Approximately 70% of the eQTLs were replicated and characterized in at least one major PBMC derived cell type. Furthermore, 40% of eQTLs were found to be more pronounced in MS patients compared to noninflammatory neurological diseases patients. In addition, we found two SNPs to be significantly associated with the proportions of three different cell types. Mapping to enhancer histone marks and predicted transcription factor binding sites added additional functional evidence for eight eQTL regions. As an example, we found that rs71624119, shared with three other autoimmune diseases and located in a primed enhancer (H3K4me1) with potential binding for STAT transcription factors, significantly associates with ANKRD55 expression. This study provides many novel and validated targets for future functional characterization of MS and other diseases.
dc.description.sponsorshipWe thank all patients who have been willing to contribute with their blood samples and make this study possible. We acknowledge International Multiple Sclerosis Genetics consortium (IMSGC) for supplying genotypes from ImmunoChip and MS replication chip used in this study. We acknowledge the Science for Life Laboratory in Stockholm for bioinformatic support in the form of a collaborative project. The computations were performed on resources provided by SNIC through Uppsala Multidisciplinary Center for Advanced Computational Science (UPPMAX) under project b2011139. We thank the Julian Knight group for sharing genotype and expression data from primary B cells and monocytes. We are grateful to Shahin Aeinehband for performing a part of the cell sorting, and to Izaura Lima Bomfim and Jenny Link for HLA imputation. This work was supported by grants from the Knut and Alice Wallenberg Foundation and the Swedish Association of Persons with Neurological Disabilities (Neuroförbundet), and an Astra Zeneca Science for Life grant.
dc.publisherOxford University Press (OUP)
dc.relation.urlhttps://academic.oup.com/hmg/advance-article/doi/10.1093/hmg/ddy001/4792999
dc.rightsThis is a pre-copyedited, author-produced PDF of an article accepted for publication in Human Molecular Genetics following peer review. The version of record is available online at: https://academic.oup.com/hmg/advance-article/doi/10.1093/hmg/ddy001/4792999.
dc.titleImpact of genetic risk loci for multiple sclerosis on expression of proximal genes in patients
dc.typeArticle
dc.contributor.departmentBiological and Environmental Sciences and Engineering (BESE) Division
dc.contributor.departmentBioscience Program
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.identifier.journalHuman Molecular Genetics
dc.eprint.versionPost-print
dc.contributor.institutionCenter for Molecular Medicine, L8:05, 171 76, Stockholm, Karolinska Institutet, Sweden
dc.contributor.institutionNeuroimmunology Unit, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
dc.contributor.institutionExperimental Rheumatology Unit, Department of Medicine, Solna, Karolinska Institutet, Stockholm, Sweden
dc.contributor.institutionUnit of Computational Medicine, Department of Medicine, Solna, Karolinska Institutet, Stockholm, Sweden
dc.contributor.institutionDepartment of Biochemistry and Biophysics, Science for Life Laboratory, Stockholm University, Stockholm, Sweden
dc.contributor.institutionScience for Life Laboratory, Karolinska Institutet, Stockholm, Sweden
dc.contributor.institutionTranslational Bioinformatics Unit, Navarrabiomed, Complejo Hospitalario de Navarra (CHN), Universidad Publica de Navarra (UPNA), IdiSNA. Pamplona. Spain.
dc.contributor.institutionMucosal & Salivary Biology Division, King's College London Dental Institute, London, United Kingdom
kaust.personTegner, Jesper
refterms.dateFOA2019-01-08T00:00:00Z
dc.date.published-online2018-01-08
dc.date.published-print2018-03-01


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