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      Genome-wide analyses of 200,453 individuals yield new insights into the causes and consequences of clonal hematopoiesis

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          Abstract

          Clonal hematopoiesis (CH), the clonal expansion of a blood stem cell and its progeny driven by somatic driver mutations, affects over a third of people, yet remains poorly understood. Here we analyze genetic data from 200,453 UK Biobank participants to map the landscape of inherited predisposition to CH, increasing the number of germline associations with CH in European-ancestry populations from 4 to 14. Genes at new loci implicate DNA damage repair ( PARP1, ATM, CHEK2), hematopoietic stem cell migration/homing ( CD164) and myeloid oncogenesis ( SETBP1). Several associations were CH-subtype-specific including variants at TCL1A and CD164 that had opposite associations with DNMT3A- versus TET2-mutant CH, the two most common CH subtypes, proposing key roles for these two loci in CH development. Mendelian randomization analyses showed that smoking and longer leukocyte telomere length are causal risk factors for CH and that genetic predisposition to CH increases risks of myeloproliferative neoplasia, nonhematological malignancies, atrial fibrillation and blood epigenetic ageing.

          Abstract

          Analysis of whole-exome sequencing data from 200,453 UK Biobank participants identifies loci associated with clonal hematopoiesis and highlights causal links between clonal hematopoiesis and other traits.

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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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            The mutational constraint spectrum quantified from variation in 141,456 humans

            Genetic variants that inactivate protein-coding genes are a powerful source of information about the phenotypic consequences of gene disruption: genes that are crucial for the function of an organism will be depleted of such variants in natural populations, whereas non-essential genes will tolerate their accumulation. However, predicted loss-of-function variants are enriched for annotation errors, and tend to be found at extremely low frequencies, so their analysis requires careful variant annotation and very large sample sizes 1 . Here we describe the aggregation of 125,748 exomes and 15,708 genomes from human sequencing studies into the Genome Aggregation Database (gnomAD). We identify 443,769 high-confidence predicted loss-of-function variants in this cohort after filtering for artefacts caused by sequencing and annotation errors. Using an improved model of human mutation rates, we classify human protein-coding genes along a spectrum that represents tolerance to inactivation, validate this classification using data from model organisms and engineered human cells, and show that it can be used to improve the power of gene discovery for both common and rare diseases.
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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
                siddhartha.kar@bristol.ac.uk
                pmquiros@ispasturias.es
                gsv20@cam.ac.uk
                Journal
                Nat Genet
                Nat Genet
                Nature Genetics
                Nature Publishing Group US (New York )
                1061-4036
                1546-1718
                14 July 2022
                14 July 2022
                2022
                : 54
                : 8
                : 1155-1166
                Affiliations
                [1 ]GRID grid.5337.2, ISNI 0000 0004 1936 7603, MRC Integrative Epidemiology Unit, , University of Bristol, ; Bristol, UK
                [2 ]GRID grid.5337.2, ISNI 0000 0004 1936 7603, Section of Translational Epidemiology, Division of Population Health Sciences, Bristol Medical School, , University of Bristol, ; Bristol, UK
                [3 ]GRID grid.5335.0, ISNI 0000000121885934, Department of Haematology, Wellcome-MRC Cambridge Stem Cell Institute, , Jeffrey Cheah Biomedical Centre, University of Cambridge, ; Cambridge, UK
                [4 ]GRID grid.10306.34, ISNI 0000 0004 0606 5382, Wellcome Sanger Institute, , Wellcome Genome Campus, Hinxton, ; Cambridge, UK
                [5 ]GRID grid.511562.4, Instituto de Investigación Sanitaria del Principado de Asturias (ISPA), ; Oviedo, Spain
                [6 ]GRID grid.5335.0, ISNI 0000000121885934, BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, , Strangeways Research Laboratory, University of Cambridge, ; Cambridge, UK
                [7 ]GRID grid.417815.e, ISNI 0000 0004 5929 4381, Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, ; Cambridge, UK
                [8 ]GRID grid.24029.3d, ISNI 0000 0004 0383 8386, Department of Haematology, , Cambridge University Hospitals NHS Foundation Trust, ; Cambridge, UK
                [9 ]GRID grid.24029.3d, ISNI 0000 0004 0383 8386, Division of Cardiovascular Medicine, Department of Medicine, , Cambridge University Hospitals NHS Foundation Trust, ; Cambridge, UK
                [10 ]GRID grid.410678.c, ISNI 0000 0000 9374 3516, Department of Medicine, , University of Melbourne, Austin Health, ; Melbourne, Victoria Australia
                [11 ]GRID grid.5335.0, ISNI 0000000121885934, MRC Biostatistics Unit, , University of Cambridge, ; Cambridge, UK
                Author information
                http://orcid.org/0000-0002-2314-1426
                http://orcid.org/0000-0002-7793-6291
                http://orcid.org/0000-0001-5365-8760
                http://orcid.org/0000-0003-4337-8022
                Article
                1121
                10.1038/s41588-022-01121-z
                9355874
                35835912
                5c7549f5-6002-4fef-a9ed-b086ac5b4c6e
                © The Author(s) 2022

                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
                : 19 October 2021
                : 6 June 2022
                Funding
                Funded by: FundRef https://doi.org/10.13039/100005189, Leukemia and Lymphoma Society (Leukemia & Lymphoma Society);
                Award ID: RTF6006-19
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/100004440, Wellcome Trust (Wellcome);
                Award ID: WT098051
                Award ID: WT098051
                Award ID: 204623/Z/16/Z
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100000690, Research Councils UK (RCUK);
                Award ID: MR/T043202/1
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100004587, Ministry of Economy and Competitiveness | Instituto de Salud Carlos III (Institute of Health Carlos III);
                Award ID: Miguel Servet Program (CP20/00130)
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100000289, Cancer Research UK (CRUK);
                Award ID: C18281/A29019
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100000274, British Heart Foundation (BHF);
                Funded by: FundRef https://doi.org/10.13039/501100000272, DH | National Institute for Health Research (NIHR);
                Award ID: BRC-1215-20014
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s), under exclusive licence to Springer Nature America, Inc. 2022

                Genetics
                genetics research,haematological diseases,genome-wide association studies
                Genetics
                genetics research, haematological diseases, genome-wide association studies

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