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      Identification of novel locus associated with coronary artery aneurysms and validation of loci for susceptibility to Kawasaki disease

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          Abstract

          Kawasaki disease (KD) is a paediatric vasculitis associated with coronary artery aneurysms (CAA). Genetic variants influencing susceptibility to KD have been previously identified, but no risk alleles have been validated that influence CAA formation. We conducted a genome-wide association study (GWAS) for CAA in KD patients of European descent with 200 cases and 276 controls. A second GWAS for susceptibility pooled KD cases with healthy paediatric controls from vaccine trials in the UK ( n = 1609). Logistic regression mixed models were used for both GWASs. The susceptibility GWAS was meta-analysed with 400 KD cases and 6101 controls from a previous European GWAS, these results were further meta-analysed with Japanese GWASs at two putative loci. The CAA GWAS identified an intergenic region of chromosome 20q13 with multiple SNVs showing genome-wide significance. The risk allele of the most associated SNV (rs6017006) was present in 13% of cases and 4% of controls; in East Asian 1000 Genomes data, the allele was absent or rare. Susceptibility GWAS with meta-analysis with previously published European data identified two previously associated loci ( ITPKC and FCGR2A). Further meta-analysis with Japanese GWAS summary data from the CASP3 and FAM167A genomic regions validated these loci in Europeans showing consistent effects of the top SNVs in both populations. We identified a novel locus for CAA in KD patients of European descent. The results suggest that different genes determine susceptibility to KD and development of CAA and future work should focus on the function of the intergenic region on chromosome 20q13.

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          A global reference for human genetic variation

          The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies.
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            A 3D map of the human genome at kilobase resolution reveals principles of chromatin looping.

            We use in situ Hi-C to probe the 3D architecture of genomes, constructing haploid and diploid maps of nine cell types. The densest, in human lymphoblastoid cells, contains 4.9 billion contacts, achieving 1 kb resolution. We find that genomes are partitioned into contact domains (median length, 185 kb), which are associated with distinct patterns of histone marks and segregate into six subcompartments. We identify ∼10,000 loops. These loops frequently link promoters and enhancers, correlate with gene activation, and show conservation across cell types and species. Loop anchors typically occur at domain boundaries and bind CTCF. CTCF sites at loop anchors occur predominantly (>90%) in a convergent orientation, with the asymmetric motifs "facing" one another. The inactive X chromosome splits into two massive domains and contains large loops anchored at CTCF-binding repeats. Copyright © 2014 Elsevier Inc. All rights reserved.
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              GCTA: a tool for genome-wide complex trait analysis.

              For most human complex diseases and traits, SNPs identified by genome-wide association studies (GWAS) explain only a small fraction of the heritability. Here we report a user-friendly software tool called genome-wide complex trait analysis (GCTA), which was developed based on a method we recently developed to address the "missing heritability" problem. GCTA estimates the variance explained by all the SNPs on a chromosome or on the whole genome for a complex trait rather than testing the association of any particular SNP to the trait. We introduce GCTA's five main functions: data management, estimation of the genetic relationships from SNPs, mixed linear model analysis of variance explained by the SNPs, estimation of the linkage disequilibrium structure, and GWAS simulation. We focus on the function of estimating the variance explained by all the SNPs on the X chromosome and testing the hypotheses of dosage compensation. The GCTA software is a versatile tool to estimate and partition complex trait variation with large GWAS data sets.
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                Author and article information

                Contributors
                clivehoggart@gmail.com
                Journal
                Eur J Hum Genet
                Eur J Hum Genet
                European Journal of Human Genetics
                Springer International Publishing (Cham )
                1018-4813
                1476-5438
                26 March 2021
                26 March 2021
                : 1-11
                Affiliations
                [1 ]GRID grid.7445.2, ISNI 0000 0001 2113 8111, Section of Paediatric Infectious Disease, Department of Infectious Disease, , Imperial College London, ; London, UK
                [2 ]GRID grid.59734.3c, ISNI 0000 0001 0670 2351, Department of Genetics and Genomic Sciences, , Icahn School of Medicine at Mount Sinai, ; New York, NY USA
                [3 ]GRID grid.266100.3, ISNI 0000 0001 2107 4242, Department of Pediatrics, , University of California San Diego, ; La Jolla, CA USA
                [4 ]GRID grid.4991.5, ISNI 0000 0004 1936 8948, Oxford Vaccine Group, Department of Paediatrics, NIHR Oxford Biomedical Research Centre, , University of Oxford, ; Oxford, UK
                [5 ]GRID grid.8991.9, ISNI 0000 0004 0425 469X, London School of Hygiene and Tropical Medicine, ; London, UK
                [6 ]GRID grid.416107.5, ISNI 0000 0004 0614 0346, Murdoch Children’s Research Institute, , Royal Children’s Hospital Melbourne, ; Parkville, VIC Australia
                [7 ]GRID grid.83440.3b, ISNI 0000000121901201, Institute of Child Health, , University College London, ; London, UK
                [8 ]GRID grid.266100.3, ISNI 0000 0001 2107 4242, Department of Biomedical Informatics, , University of California San Diego, ; La Jolla, CA USA
                [9 ]GRID grid.286440.c, ISNI 0000 0004 0383 2910, Rady Children’s Hospital San Diego, ; San Diego, CA USA
                [10 ]GRID grid.410552.7, ISNI 0000 0004 0628 215X, Department of Paediatrics and Adolescent Medicine, , Tyks University Hospital, ; Turku, Finland
                [11 ]GRID grid.7177.6, ISNI 0000000084992262, Department of Pediatric Immunology, Rheumatology & Infectious Diseases, Emma Children’s Hospital, Amsterdam University Medical Centre, , University of Amsterdam, ; Amsterdam, The Netherlands
                [12 ]GRID grid.7177.6, ISNI 0000000084992262, Sanquin Research and Landsteiner Laboratory, Department of Blood Cell Research, Academic Medical Centre, , University of Amsterdam, ; Amsterdam, The Netherlands
                Author information
                http://orcid.org/0000-0002-0482-0052
                http://orcid.org/0000-0002-3149-2699
                http://orcid.org/0000-0001-7826-1516
                http://orcid.org/0000-0002-3389-5715
                http://orcid.org/0000-0002-6902-9886
                http://orcid.org/0000-0002-8304-4302
                Article
                838
                10.1038/s41431-021-00838-5
                7994355
                33772158
                b869f246-6cb6-42e9-94cf-559a11f3f24a
                © The Author(s) 2021

                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
                : 29 August 2020
                : 13 February 2021
                : 18 February 2021
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100004737, National Health Research Institutes (NHRI);
                Award ID: WMNP_P69099
                Award ID: WMNP_P69099
                Award ID: WMNP_P69099
                Award ID: WMNP_P69099
                Award ID: WMNP_P69099
                Award Recipient :
                Funded by: Gordon and Marilyn Macklin Foundation
                Funded by: the European Union’s Seventh Framework programme under grant agreement No. 279185 (EUCLIDS)
                Funded by: the European Union’s Seventh Framework programme under grant agreement No. 279185 (EUCLIDS), the Javon Charitable Trust, the Children of St Mary’s Intensive Care Kawasaki Disease Research Fund
                Categories
                Article

                Genetics
                genetics research,vasculitis,aneurysm
                Genetics
                genetics research, vasculitis, aneurysm

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