Dataset Information

Exome sequencing and characterization of 49,960 individuals in the UK Biobank.

ABSTRACT: The UK Biobank is a prospective study of 502,543 individuals, combining extensive phenotypic and genotypic data with streamlined access for researchers around the world¹. 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, including PIEZO1 on varicose veins, COL6A1 on corneal resistance, MEPE on bone density, and IQGAP2 and GMPR on 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 pathogenic BRCA1 and BRCA2 variants. 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.

SUBMITTER: Van Hout CV

PROVIDER: S-EPMC7759458 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Exome sequencing and characterization of 49,960 individuals in the UK Biobank.

Van Hout Cristopher V CV Tachmazidou Ioanna I Backman Joshua D JD Hoffman Joshua D JD Liu Daren D Pandey Ashutosh K AK Gonzaga-Jauregui Claudia C Khalid Shareef S Ye Bin B Banerjee Nilanjana N Li Alexander H AH O'Dushlaine Colm C Marcketta Anthony A Staples Jeffrey J Schurmann Claudia C Hawes Alicia A Maxwell Evan E Barnard Leland L Lopez Alexander A Penn John J Habegger Lukas L Blumenfeld Andrew L AL Bai Xiaodong X O'Keeffe Sean S Yadav Ashish A Praveen Kavita K Jones Marcus M Salerno William J WJ Chung Wendy K WK Surakka Ida I Willer Cristen J CJ Hveem Kristian K Leader Joseph B JB Carey David J DJ Ledbetter David H DH Cardon Lon L Yancopoulos George D GD Economides Aris A Coppola Giovanni G Shuldiner Alan R AR Balasubramanian Suganthi S Cantor Michael M Nelson Matthew R MR Whittaker John J Reid Jeffrey G JG Marchini Jonathan J Overton John D JD Scott Robert A RA Abecasis Gonçalo R GR Yerges-Armstrong Laura L Baras Aris A

Nature 20201021 7831

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<sup>1</sup>. 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 t ...[more]

PMID: 33087929

Similar Datasets

Project description:BackgroundThe genealogical histories of individuals within populations are of interest to studies aiming both to uncover detailed pedigree information and overall quantitative population demographic histories. However, the analysis of quantitative details of individual genealogical histories has faced challenges from incomplete available pedigree records and an absence of objective and quantitative details in pedigree information. Although complete pedigree information for most individuals is difficult to track beyond a few generations, it is possible to describe a person's genealogical history using their genetic relatives revealed by identity by descent (IBD) segments-long genomic segments shared by two individuals within a population, which are identical due to inheritance from common ancestors. When modern biobanks collect genotype information for a significant fraction of a population, dense genetic connections of a person can be traced using such IBD segments, offering opportunities to characterize individuals in the context of the underlying populations. Here, we conducted an individual-centric analysis of IBD segments among the UK Biobank participants that represent 0.7% of the UK population.ResultsWe made a high-quality call set of IBD segments over 5 cM among all 500,000 UK Biobank participants. On average, one UK individual shares IBD segments with 14,000 UK Biobank participants, which we refer to as "relatives." Using these segments, approximately 80% of a person's genome can be imputed. We subsequently propose genealogical descriptors based on the genetic connections of relative cohorts of individuals sharing at least one IBD segment and show that such descriptors offer important information about one's genetic makeup, personal genealogical history, and social behavior. Through analysis of relative counts sharing segments at different lengths, we identified a group, potentially British Jews, who has a distinct pattern of familial expansion history. Finally, using the enrichment of relatives in one's neighborhood, we identified regional variations of personal preference favoring living closer to one's extended families.ConclusionsOur analysis revealed genetic makeup, personal genealogical history, and social behaviors at the population scale, opening possibilities for further studies of individual's genetic connections in biobank data.

Project description:BackgroundThe UK Biobank study provides a unique opportunity to study the causes and consequences of disease. We aimed to use the UK Biobank data to study the well-established, but poorly understood, association between low birthweight and type 2 diabetes.MethodsWe used logistic regression to calculate the odds ratio for participants' risk of type 2 diabetes given a one standard deviation increase in birthweight. To test for an association between parental diabetes and birthweight, we performed linear regression of self-reported parental diabetes status against birthweight. We performed path and mediation analyses to test the hypothesis that birthweight partly mediates the association between parental diabetes and participant type 2 diabetes status.ResultsOf the UK Biobank participants, 277 261 reported their birthweight. Of 257 715 individuals of White ethnicity and singleton pregnancies, 6576 had type 2 diabetes, 19 478 reported maternal diabetes (but not paternal), 20 057 reported paternal diabetes (but not maternal) and 2754 participants reported both parents as having diabetes. Lower birthweight was associated with type 2 diabetes in the UK Biobank participants. A one kilogram increase in birthweight was associated with a lower risk of type 2 diabetes (odds ratio: 0.74; 95% CI: 0.71, 0.76; P = 2 × 10(-57)). Paternal diabetes was associated with lower birthweight (45 g lower; 95% CI: 36, 54; P = 2 × 10(-23)) relative to individuals with no parental diabetes. Maternal diabetes was associated with higher birthweight (59 g increase; 95% CI: 50, 68; P = 3 × 10(-37)). Participants' lower birthweight was a mediator of the association between reported paternal diabetes and participants' type 2 diabetes status, explaining 1.1% of the association, and participants' higher birthweight was a mediator of the association between reported maternal diabetes and participants' type 2 diabetes status, explaining 1.2% of the association.ConclusionsData from the UK Biobank provides the strongest evidence by far that paternal diabetes is associated with lower birthweight, whereas maternal diabetes is associated with increased birthweight. Our findings with paternal diabetes are consistent with a role for the same genetic factors influencing foetal growth and type 2 diabetes.

Dataset Information

Exome sequencing and characterization of 49,960 individuals in the UK Biobank.

Publications

Exome sequencing and characterization of 49,960 individuals in the UK Biobank.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets