Cristopher V. Van Hout, Ioanna Tachmazidou, Joshua D. Backman, Joshua D. Hoffman, Daren Liu, Ashutosh K. Pandey, Claudia Gonzaga-Jauregui, Shareef Khalid, Bin Ye, Nilanjana Banerjee, Alexander H. Li, Colm O'Dushlaine, Anthony Marcketta, Jeffrey Staples, Claudia Schurmann, Alicia Hawes, Evan Maxwell, Leland Barnard, Alexander Lopez, John Penn, Lukas Habegger, Andrew L. Blumenfeld, Xiaodong Bai, Sean O'Keeffe, Ashish Yadav, Kavita Praveen, Marcus Jones, William J. Salerno, Wendy K. Chung, Ida Surakka, Cristen J. Willer, Kristian Hveem, Joseph B. Leader, David J. Carey, David H. Ledbetter, Lon Cardon, George D. Yancopoulos, Aris Economides, Giovanni Coppola, Alan R. Shuldiner, Suganthi Balasubramanian, Michael Cantor, Matthew R. Nelson, John Whittaker, Jeffrey G. Reid, Jonathan Marchini, John D. Overton, Robert A. Scott, Goncalo R. Abecasis, Laura M. Yerges-Armstrong, Aris Baras
- The UK Biobank is a prospective study of 502,543 individuals, combining extensive phenotypic and genotypic data with streamlined access for researchers around the world(1). Here we describe the release of exome-sequence data for the first 49,960 study participants, revealing approximately 4 million coding variants (of which around 98.6% have a frequency of less than 1%). The data include 198,269 autosomal predicted loss-of-function (LOF) variants, a more than 14-fold increase compared to the imputed sequence. Nearly all genes (more than 97%) had at least one carrier with a LOF variant, and most genes (more than 69%) had at least ten carriers with a LOF variant. We illustrate the power of characterizing LOF variants in this population through association analyses across 1,730 phenotypes. In addition to replicating established associations, we found novel LOF variants with large effects on disease traits, includingPIEZO1on varicose veins,COL6A1on corneal resistance,MEPEon bone density, andIQGAP2andGMPRon blood cell traits. We furtherThe UK Biobank is a prospective study of 502,543 individuals, combining extensive phenotypic and genotypic data with streamlined access for researchers around the world(1). Here we describe the release of exome-sequence data for the first 49,960 study participants, revealing approximately 4 million coding variants (of which around 98.6% have a frequency of less than 1%). The data include 198,269 autosomal predicted loss-of-function (LOF) variants, a more than 14-fold increase compared to the imputed sequence. Nearly all genes (more than 97%) had at least one carrier with a LOF variant, and most genes (more than 69%) had at least ten carriers with a LOF variant. We illustrate the power of characterizing LOF variants in this population through association analyses across 1,730 phenotypes. In addition to replicating established associations, we found novel LOF variants with large effects on disease traits, includingPIEZO1on varicose veins,COL6A1on corneal resistance,MEPEon bone density, andIQGAP2andGMPRon blood cell traits. We further demonstrate the value of exome sequencing by surveying the prevalence of pathogenic variants of clinical importance, and show that 2% of this population has a medically actionable variant. Furthermore, we characterize the penetrance of cancer in carriers of pathogenicBRCA1andBRCA2variants. Exome sequences from the first 49,960 participants highlight the promise of genome sequencing in large population-based studies and are now accessible to the scientific community. <br /> Exome sequences from the first 49,960 participants in the UK Biobank highlight the promise of genome sequencing in large population-based studies and are now accessible to the scientific community.…
MetadatenVerfasserangaben: | Cristopher V. Van HoutORCiD, Ioanna Tachmazidou, Joshua D. Backman, Joshua D. Hoffman, Daren Liu, Ashutosh K. Pandey, Claudia Gonzaga-Jauregui, Shareef Khalid, Bin Ye, Nilanjana Banerjee, Alexander H. Li, Colm O'Dushlaine, Anthony Marcketta, Jeffrey Staples, Claudia SchurmannGND, Alicia Hawes, Evan Maxwell, Leland Barnard, Alexander Lopez, John Penn, Lukas Habegger, Andrew L. Blumenfeld, Xiaodong Bai, Sean O'Keeffe, Ashish Yadav, Kavita Praveen, Marcus Jones, William J. Salerno, Wendy K. Chung, Ida SurakkaORCiD, Cristen J. WillerORCiD, Kristian Hveem, Joseph B. LeaderORCiD, David J. Carey, David H. LedbetterORCiD, Lon Cardon, George D. Yancopoulos, Aris EconomidesORCiD, Giovanni Coppola, Alan R. Shuldiner, Suganthi BalasubramanianORCiD, Michael Cantor, Matthew R. Nelson, John Whittaker, Jeffrey G. ReidORCiD, Jonathan MarchiniORCiD, John D. Overton, Robert A. ScottORCiD, Goncalo R. Abecasis, Laura M. Yerges-ArmstrongORCiD, Aris BarasORCiD |
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DOI: | https://doi.org/10.1038/s41586-020-2853-0 |
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ISSN: | 0028-0836 |
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ISSN: | 1476-4687 |
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Pubmed ID: | https://pubmed.ncbi.nlm.nih.gov/33087929 |
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Titel des übergeordneten Werks (Englisch): | Nature : the international weekly journal of science |
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Verlag: | Macmillan Publishers Limited |
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Verlagsort: | London |
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Publikationstyp: | Wissenschaftlicher Artikel |
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Sprache: | Englisch |
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Datum der Erstveröffentlichung: | 21.10.2020 |
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Erscheinungsjahr: | 2020 |
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Urhebende Körperschaft: | Regeneron Genetics Ctr |
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Datum der Freischaltung: | 08.02.2023 |
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Freies Schlagwort / Tag: | BRCA1; breast-cancer; clinical exome; gene; metaanalysis; mutations; recommendations; risk; susceptibility; variants, |
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Band: | 586 |
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Ausgabe: | 7831 |
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Seitenanzahl: | 9 |
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Erste Seite: | 749 |
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Letzte Seite: | 756 |
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Organisationseinheiten: | Digital Engineering Fakultät / Hasso-Plattner-Institut für Digital Engineering GmbH |
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DDC-Klassifikation: | 0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 000 Informatik, Informationswissenschaft, allgemeine Werke |
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Peer Review: | Referiert |
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Publikationsweg: | Open Access / Hybrid Open-Access |
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Lizenz (Deutsch): | CC-BY - Namensnennung 4.0 International |
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