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      Genome wide analysis for mouth ulcers identifies associations at immune regulatory loci

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          Abstract

          Mouth ulcers are the most common ulcerative condition and encompass several clinical diagnoses, including recurrent aphthous stomatitis (RAS). Despite previous evidence for heritability, it is not clear which specific genetic loci are implicated in RAS. In this genome-wide association study ( n = 461,106) heritability is estimated at 8.2% (95% CI: 6.4%, 9.9%). This study finds 97 variants which alter the odds of developing non-specific mouth ulcers and replicate these in an independent cohort ( n = 355,744) (lead variant after meta-analysis: rs76830965, near IL12A, OR 0.72 (95% CI: 0.71, 0.73); P = 4.4e−483). Additional effect estimates from three independent cohorts with more specific phenotyping and specific study characteristics support many of these findings. In silico functional analyses provide evidence for a role of T cell regulation in the aetiology of mouth ulcers. These results provide novel insight into the pathogenesis of a common, important condition.

          Abstract

          Oral ulcerations are sores of the mucous membrane of the mouth and highly prevalent in the population. Here, in a genome-wide association study, the authors identify 97 loci associated with mouth ulcers highlighting genes involved in T cell-mediated immunity and T H1 responses.

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          Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support.

          Research electronic data capture (REDCap) is a novel workflow methodology and software solution designed for rapid development and deployment of electronic data capture tools to support clinical and translational research. We present: (1) a brief description of the REDCap metadata-driven software toolset; (2) detail concerning the capture and use of study-related metadata from scientific research teams; (3) measures of impact for REDCap; (4) details concerning a consortium network of domestic and international institutions collaborating on the project; and (5) strengths and limitations of the REDCap system. REDCap is currently supporting 286 translational research projects in a growing collaborative network including 27 active partner institutions.
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            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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              The UK Biobank resource with deep phenotyping and genomic data

              The UK Biobank project is a prospective cohort study with deep genetic and phenotypic data collected on approximately 500,000 individuals from across the United Kingdom, aged between 40 and 69 at recruitment. The open resource is unique in its size and scope. A rich variety of phenotypic and health-related information is available on each participant, including biological measurements, lifestyle indicators, biomarkers in blood and urine, and imaging of the body and brain. Follow-up information is provided by linking health and medical records. Genome-wide genotype data have been collected on all participants, providing many opportunities for the discovery of new genetic associations and the genetic bases of complex traits. Here we describe the centralized analysis of the genetic data, including genotype quality, properties of population structure and relatedness of the genetic data, and efficient phasing and genotype imputation that increases the number of testable variants to around 96 million. Classical allelic variation at 11 human leukocyte antigen genes was imputed, resulting in the recovery of signals with known associations between human leukocyte antigen alleles and many diseases.
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                Author and article information

                Contributors
                N.J.Timpson@bristol.ac.uk
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                5 March 2019
                5 March 2019
                2019
                : 10
                : 1052
                Affiliations
                [1 ]ISNI 0000 0004 1936 7603, GRID grid.5337.2, Medical Research Council Integrative Epidemiology Unit, Department of Population Health Sciences, Bristol Medical School, , University of Bristol, ; Bristol, BS8 2BN UK
                [2 ]ISNI 0000 0004 1936 7603, GRID grid.5337.2, Bristol Dental School, , University of Bristol, ; Bristol, BS1 2LY UK
                [3 ]ISNI 0000 0001 2294 1395, GRID grid.1049.c, Department of Psychiatric Genetics, , QIMR Berghofer Medical Research Institute, ; Brisbane, 4006 Queensland Australia
                [4 ]GRID grid.420283.f, Research, 23andMe, Inc, ; Mountain View, 94041 CA USA
                [5 ]ISNI 0000 0001 2294 1395, GRID grid.1049.c, Department of Genetic Epidemiology, , QIMR Berghofer Medical Research Institute, ; Brisbane, 4006 Queensland Australia
                [6 ]ISNI 0000 0001 0930 2361, GRID grid.4514.4, Genetic and Molecular Epidemiology Unit, Department of Clinical Sciences, , Lund University, ; Malmö, 221 00 Sweden
                [7 ]ISNI 0000 0001 1034 3451, GRID grid.12650.30, Department of Public Health & Clinical Medicine, , Umeå University, ; Umeå, 901 87 Sweden
                [8 ]ISNI 000000041936754X, GRID grid.38142.3c, Department of Nutrition, Harvard T.H. Chan School of Public Health, , Harvard University, ; Boston, 02115 MA USA
                Author information
                http://orcid.org/0000-0003-3756-040X
                http://orcid.org/0000-0001-7793-7326
                http://orcid.org/0000-0002-3887-2598
                http://orcid.org/0000-0002-3506-160X
                http://orcid.org/0000-0002-9004-364X
                http://orcid.org/0000-0001-7623-328X
                http://orcid.org/0000-0001-7328-4233
                http://orcid.org/0000-0003-2514-0889
                http://orcid.org/0000-0003-4069-8020
                Article
                8923
                10.1038/s41467-019-08923-6
                6400940
                30602773
                4e52f2b8-15d8-484f-a42e-ac7d36b18789
                © The Author(s) 2019

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 12 October 2018
                : 5 February 2019
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