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    Impact of genetic risk loci for multiple sclerosis on expression of proximal genes in patients

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    ddy001.pdf
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    Type
    Article
    Authors
    James, Tojo
    Lindén, Magdalena
    Morikawa, Hiromasa cc
    Fernandes, Sunjay Jude
    Ruhrmann, Sabrina
    Huss, Mikael
    Brandi, Maya
    Piehl, Fredrik
    Jagodic, Maja
    Tegner, Jesper cc
    Khademi, Mohsen
    Olsson, Tomas
    Gomez-Cabrero, David cc
    Kockum, Ingrid
    KAUST Department
    Biological and Environmental Sciences and Engineering (BESE) Division
    Bioscience Program
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Date
    2018-01-08
    Online Publication Date
    2018-01-08
    Print Publication Date
    2018-03-01
    Permanent link to this record
    http://hdl.handle.net/10754/626756
    
    Metadata
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    Abstract
    Despite 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.
    Citation
    James 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.
    Sponsors
    We 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.
    Publisher
    Oxford University Press (OUP)
    Journal
    Human Molecular Genetics
    DOI
    10.1093/hmg/ddy001
    Additional Links
    https://academic.oup.com/hmg/advance-article/doi/10.1093/hmg/ddy001/4792999
    ae974a485f413a2113503eed53cd6c53
    10.1093/hmg/ddy001
    Scopus Count
    Collections
    Articles; Biological and Environmental Science and Engineering (BESE) Division; Bioscience Program; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

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