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      Transcriptome-Wide Association Study for Inflammatory Bowel Disease Reveals Novel Candidate Susceptibility Genes in Specific Colon Subsites and Tissue Categories

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          Abstract

          Background and Aims

          Genome-wide association studies [GWAS] for inflammatory bowel disease [IBD] have identified 240 risk variants. However, the benefit of understanding the genetic architecture of IBD remains to be exploited. Transcriptome-wide association studies [TWAS] associate gene expression with genetic susceptibility to disease, providing functional insight into risk loci. In this study, we integrate relevant datasets for IBD and perform a TWAS to nominate novel genes implicated in IBD genetic susceptibility.

          Methods

          We applied elastic net regression to generate gene expression prediction models for the University of Barcelona and University of Virginia RNA sequencing project [BarcUVa-Seq] and correlated expression and disease association research [CEDAR] datasets. Together with Genotype-Tissue Expression project [GTEx] data, and GWAS results from about 60 000 individuals, we employed Summary-PrediXcan and Summary-MultiXcan for single and joint analyses of TWAS results, respectively.

          Results

          BarcUVa-Seq TWAS revealed 39 novel genes whose expression in the colon is associated with IBD genetic susceptibility. They included expression markers for specific colon cell types. TWAS meta-analysis including all tissues/cell types provided 186 novel candidate susceptibility genes. Additionally, we identified 78 novel susceptibility genes whose expression is associated with IBD exclusively in immune (N = 19), epithelial (N = 25), mesenchymal (N = 22) and neural (N = 12) tissue categories. Associated genes were involved in relevant molecular pathways, including pathways related to known IBD therapeutics, such as tumour necrosis factor signalling.

          Conclusion

          These findings provide insight into tissue-specific molecular processes underlying IBD genetic susceptibility. Associated genes could be candidate targets for new therapeutics and should be prioritized in functional studies.

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          Most cited references37

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          Is Open Access

          Second-generation PLINK: rising to the challenge of larger and richer datasets

          PLINK 1 is a widely used open-source C/C++ toolset for genome-wide association studies (GWAS) and research in population genetics. However, the steady accumulation of data from imputation and whole-genome sequencing studies has exposed a strong need for even faster and more scalable implementations of key functions. In addition, GWAS and population-genetic data now frequently contain probabilistic calls, phase information, and/or multiallelic variants, none of which can be represented by PLINK 1's primary data format. To address these issues, we are developing a second-generation codebase for PLINK. The first major release from this codebase, PLINK 1.9, introduces extensive use of bit-level parallelism, O(sqrt(n))-time/constant-space Hardy-Weinberg equilibrium and Fisher's exact tests, and many other algorithmic improvements. In combination, these changes accelerate most operations by 1-4 orders of magnitude, and allow the program to handle datasets too large to fit in RAM. This will be followed by PLINK 2.0, which will introduce (a) a new data format capable of efficiently representing probabilities, phase, and multiallelic variants, and (b) extensions of many functions to account for the new types of information. The second-generation versions of PLINK will offer dramatic improvements in performance and compatibility. For the first time, users without access to high-end computing resources can perform several essential analyses of the feature-rich and very large genetic datasets coming into use.
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            UniProt: the universal protein knowledgebase in 2021

            (2020)
            Abstract The aim of the UniProt Knowledgebase is to provide users with a comprehensive, high-quality and freely accessible set of protein sequences annotated with functional information. In this article, we describe significant updates that we have made over the last two years to the resource. The number of sequences in UniProtKB has risen to approximately 190 million, despite continued work to reduce sequence redundancy at the proteome level. We have adopted new methods of assessing proteome completeness and quality. We continue to extract detailed annotations from the literature to add to reviewed entries and supplement these in unreviewed entries with annotations provided by automated systems such as the newly implemented Association-Rule-Based Annotator (ARBA). We have developed a credit-based publication submission interface to allow the community to contribute publications and annotations to UniProt entries. We describe how UniProtKB responded to the COVID-19 pandemic through expert curation of relevant entries that were rapidly made available to the research community through a dedicated portal. UniProt resources are available under a CC-BY (4.0) license via the web at https://www.uniprot.org/.
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              Is Open Access

              The NHGRI-EBI GWAS Catalog of published genome-wide association studies, targeted arrays and summary statistics 2019

              Abstract The GWAS Catalog delivers a high-quality curated collection of all published genome-wide association studies enabling investigations to identify causal variants, understand disease mechanisms, and establish targets for novel therapies. The scope of the Catalog has also expanded to targeted and exome arrays with 1000 new associations added for these technologies. As of September 2018, the Catalog contains 5687 GWAS comprising 71673 variant-trait associations from 3567 publications. New content includes 284 full P-value summary statistics datasets for genome-wide and new targeted array studies, representing 6 × 109 individual variant-trait statistics. In the last 12 months, the Catalog's user interface was accessed by ∼90000 unique users who viewed >1 million pages. We have improved data access with the release of a new RESTful API to support high-throughput programmatic access, an improved web interface and a new summary statistics database. Summary statistics provision is supported by a new format proposed as a community standard for summary statistics data representation. This format was derived from our experience in standardizing heterogeneous submissions, mapping formats and in harmonizing content. Availability: https://www.ebi.ac.uk/gwas/.
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                Author and article information

                Contributors
                (View ORCID Profile)
                (View ORCID Profile)
                (View ORCID Profile)
                Journal
                Journal of Crohn's and Colitis
                Oxford University Press (OUP)
                1873-9946
                1876-4479
                February 01 2022
                February 23 2022
                July 21 2021
                February 01 2022
                February 23 2022
                July 21 2021
                : 16
                : 2
                : 275-285
                Affiliations
                [1 ]Oncology Data Analytics Program, Catalan Institute of Oncology (ICO), L’Hospitalet de Llobregat, Barcelona, Spain
                [2 ]ONCOBELL Program, Bellvitge Biomedical Research Institute (IDIBELL), L’Hospitalet de Llobregat, Barcelona, Spain
                [3 ]Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain
                [4 ]Department of Clinical Sciences, Faculty of Medicine, University of Barcelona, Barcelona, Spain
                [5 ]Gastroenterology Department, Bellvitge University Hospital, L’Hospitalet de Llobregat, Spain
                [6 ]Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
                [7 ]Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA
                Article
                10.1093/ecco-jcc/jjab131
                34286847
                6889af29-c2be-4aea-a2d9-014b4ac4d66e
                © 2021

                https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model

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