Genome-wide genetic data on ~500,000 UK Biobank participants

TLDR: The UK Biobank project is a large prospective cohort study of ~500,000 individuals from across the United Kingdom, aged between 40-69 at recruitment, and a set of analyses that reveal properties of the genetic data – such as population structure and relatedness – that can be important for downstream analyses are conducted.

Abstract: The UK Biobank project is a large prospective cohort study of ~500,000 individuals from across the United Kingdom, aged between 40-69 at recruitment. A rich variety of phenotypic and health-related information is available on each participant, making the resource unprecedented in its size and scope. Here we describe the genome-wide genotype data (~805,000 markers) collected on all individuals in the cohort and its quality control procedures. Genotype data on this scale offers novel opportunities for assessing quality issues, although the wide range of ancestries of the individuals in the cohort also creates particular challenges. We also conducted a set of analyses that reveal properties of the genetic data – such as population structure and relatedness – that can be important for downstream analyses. In addition, we phased and imputed genotypes into the dataset, using computationally efficient methods combined with the Haplotype Reference Consortium (HRC) and UK10K haplotype resource. This increases the number of testable variants by over 100-fold to ~96 million variants. We also imputed classical allelic variation at 11 human leukocyte antigen (HLA) genes, and as a quality control check of this imputation, we replicate signals of known associations between HLA alleles and many common diseases. We describe tools that allow efficient genome-wide association studies (GWAS) of multiple traits and fast phenome-wide association studies (PheWAS), which work together with a new compressed file format that has been used to distribute the dataset. As a further check of the genotyped and imputed datasets, we performed a test-case genome-wide association scan on a well-studied human trait, standing height.

Figures

Figure 1 | Summary of UK Biobank genotyping array content. This is a schematic representation of the different categories of content on the UK Biobank Axiom array. Numbers indicate the approximate count of markers within each category, ignoring any overlap. A more detailed description of the array content is available in [7].

Figure 7 | Distribution of information scores at autosomal markers in the imputed dataset. Top left shows the full distribution of the info scores. The remaining panels show distributions in tranches of minor allele frequency MAF > 5%, 1%<=MAF<5%, 0.1%<=MAF<1% , 0.01%<=MAF<0.1% and 0.001%<=MAF<0.01%.

Table 4 | Summary of related pairs (3rd degree or closer) for the full UK Biobank cohort. Counts are derived from the kinship coefficients as recommended by the authors of KING [42]. Note that parentoffspring and full sibling pairs have the same expected kinship coefficient (0.25) but can be easily distinguished by their IBS0 fraction. The count of monozygotic twins is after excluding samples identified as duplicates (see Supplementary Material).

Table 1 | The number of markers and samples by genotyping array at main stages of the UK Biobank genotyping experiment. “Data delivery from Affymetrix” refers to the data produced by Affymetrix after applying their filtering (see Supplementary Material). “Released data” refers to the released genotype data, after applying QC as described in Sections 2.1.4 and 2.1.5.

Figure 6 | Familial relatedness in the UK Biobank cohort. (A) Examples of family groups within the UK Biobank cohort. Points indicate participants, and lines between points indicate familial relatedness (3rd degree and closer) as inferred from the genetic data (see Methods). The colour and thickness of the lines indicate different relative classes, as shown in the key. An integer next to a network indicates the total number of family networks in the cohort with the same configuration, ignoring 3rd degree pairs. No integer means there is only the one shown. For example, there are 10 networks that comprise exactly 5 full siblings (two examples, which differ with respect to a 3rd degree relative, are shown on this plot); and there is only one network that comprises 6 full siblings (plus one 3rd degree relative who is related to all siblings). (B) Distribution of the exact number of relatives that

Table 3 | Failure rates for six marker-based quality tests. For all numbered tests a marker (or marker within a batch) was set to missing if the test yielded a p-value < 10-12, except in the case of Test 6, for which a marker was set to missing if the test yielded < 95% concordance. See Supplementary Material for details of each test. The total is not equal to the sum of all tests because it is possible for a marker to fail more than one test. Since the two arrays contain slightly different sets of markers, the total number of genotype calls used to compute the fractions is, Nukbb Lukbb + Nukbl Lukbl, where N and L refer to the numbers of markers and samples typed on the UK Biobank Axiom array (ukbb) and samples typed on the UK BiLEVE Axiom array (ukbl) within the Affymetrix data delivery (see Table S1). *The array effect test was applied across all batches and only for markers present on both arrays, so we simply report the total number of markers that failed this test. **The discordance test was applied across all batches, but not all markers are present on both arrays. The first value is the number of unique markers on the UK BiLEVE Axiom array that failed this test, and the second is for markers on the UK Biobank Axiom array.

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1
!Wellcome!Trust!Center!for!Human!Genetics,!University!of!Oxford,!UK!
2
!Department!of!Statistics,!University!of!Oxford,!UK!
3
!Centre!for!Systems!Genomics!and!the!Schools!of!Mathematics!and!Statistics,!and!
BioSciences,!The!University!of!Melbourne,!Parkville,!Victoria,!Australia.!
4
!Murdoch!Children’s!Research!Institute,!Parkville,!Victoria,!Australia.!
5
!Department!of!Genetic!Medicine!and!Development,!University!of!Geneva,!1!Michel!
Servet,!Geneva,!CH1211,!Switzerland.!
6
!Swiss!Institute!of!Bioinformatics,!University!of!Geneva,!1!Michel!Servet,!Geneva,!
CH1211,!Switzerland.!
7
!Institute!of!Genetics!and!Genomics!in!Geneva,!University!of!Geneva,!1!Michel!
Servet,!Geneva,!CH1211,!Switzerland.!
8!
Illumina!Ltd,!Chesterford!Research!Park,!Little!Chesterford,!Essex,!CB10!1XL,!United!
Kingdom.!
9
!Nuffield!Department!of!Clinical!Neurosciences,!Division!of!Clinical!Neurology,!John!
Radcliffe!Hospital,!University!of!Oxford,!Oxford!OX3!9DU,!United!Kingdom.!
10!
UK!Biobank,!Units!1-4!Spectrum!Way,!Adswood,!Stockport,!Cheshire,!SK3!0SA,!UK!
11
!Big!Data!Institute,!Li!Ka!Shing!Centre!for!Health!Information!and!Discovery,!
University!of!Oxford,!Oxford!OX3!7LF,!United!Kingdom.!
^!Current!address:!Procter!&!Gamble,!Brussels,!Belgium!
!!
*!These!authors!contributed!equally!to!this!work.!
†!These!authors!jointly!directed!this!work.!
‡!To!whom!correspondence!should!be!addressed:!marchini@stats.ox.ac.uk!
!
!
!
! !
not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.
The copyright holder for this preprint (which wasthis version posted July 20, 2017. ; https://doi.org/10.1101/166298doi: bioRxiv preprint

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The!UK!Biobank!project!is!a!large!prospective!cohort!study!of!~500,000!individuals!
from!across!the!United!Kingdom,!aged!between!40-69!at!recruitment.!!A!rich!variety!
of!phenotypic!and!health-related!information!is!available!on!each!participant,!
making!the!resource!unprecedented!in!its!size!and!scope.!Here!we!describe!the!
genome-wide!genotype!data!(~805,000!markers)!collected!on!all!individuals!in!the!
cohort!and!its!quality!control!procedures.!Genotype!data!on!this!scale!offers!novel!
opportunities!for!assessing!quality!issues,!although!the!wide!range!of!ancestries!of!
the!individuals!in!the!cohort!also!creates!particular!challenges.!!We!also!conducted!a!
set!of!analyses!that!reveal!properties!of!the!genetic!data!–!such!as!population!
structure!and!relatedness!–!that!can!be!important!for!downstream!analyses.!In!
addition,!we!phased!and!imputed!genotypes!into!the!dataset,!using!computationally!
efficient!methods!combined!with!the!Haplotype!Reference!Consortium!(HRC)!and!
UK10K!haplotype!resource.!!This!increases!the!number!of!testable!variants!by!over!
100-fold!to!~96!million!variants.!We!also!imputed!classical!allelic!variation!at!11!
human!leukocyte!antigen!(HLA)!genes,!and!as!a!quality!control!check!of!this!
imputation,!we!replicate!signals!of!known!associations!between!HLA!alleles!and!
many!common!diseases.!!We!describe!tools!that!allow!efficient!genome-wide!
association!studies!(GWAS)!of!multiple!traits!and!fast!phenome-wide!association!
studies!(PheWAS),!which!work!together!with!a!new!compressed!file!format!that!has!
been!used!to!distribute!the!dataset.!!As!a!further!check!of!the!genotyped!and!
imputed!datasets,!we!performed!a!test-case!genome-wide!association!scan!on!a!
well-studied!human!trait,!standing!height.!
!
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UK!Biobank,!Genotypes,!Quality!control,!Population!structure,!Relatedness,!Phasing,!
Imputation,!HLA!Imputation,!GWAS,!PheWAS!
! !
not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.
The copyright holder for this preprint (which wasthis version posted July 20, 2017. ; https://doi.org/10.1101/166298doi: bioRxiv preprint

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1" Introduction!............................................................................................................!4"
2" Results!....................................................................................................................!5"
2.1" High!quality!genotype!calling!on!novel!array!..................................................!5"
2.2" Ancestral!diversity!and!cryptic!relatedness!...................................................!18"
2.3" Phasing!and!Imputation!of!SNPs,!short!indels!and!CNVs!...............................!23"
2.4" Imputation!of!classical!HLA!alleles!.................................................................!26"
2.5" GWAS!for!standing!height!.............................................................................!28"
2.6" Multiple!trait!GWAS!and!PheWAS!.................................................................!31"
3" Data!provision!and!access!....................................................................................!31"
4" URLs!......................................................................................................................!32"
5" Author!contributions!............................................................................................!32"
6" Acknowledgements!..............................................................................................!32"
7" Conflicts!of!Interest!..............................................................................................!33"
8" References!............................................................................................................!33"
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not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.
The copyright holder for this preprint (which wasthis version posted July 20, 2017. ; https://doi.org/10.1101/166298doi: bioRxiv preprint

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The!UK!Biobank!project!is!a!large!prospective!cohort!study!of!~500,000!individuals!
from!across!the!United!Kingdom,!aged!between!40-69!at!recruitment![1].!!A!rich!
variety!of!phenotypic!and!health-related!information!is!available!on!each!participant,!
making!the!resource!unprecedented!in!its!size!and!scope.!The!data!contains!self-
reported!information,!including!basic!demographics,!diet,!and!exercise!habits;!
extensive!physical!and!cognitive!measurements;!with!other!sources!of!health-related!
information!such!as!medical!records!and!cancer!registers!being!integrated!and!
followed!up!over!the!course!of!the!participants’!lives![2].!The!baseline!information!
has,!and!will!be,!extended!in!a!number!of!ways![3].!For!example,!many!blood!and!
urine!biomarkers!are!being!measured;!and!medical!imaging!of!brain![4],!heart,!
bones,!carotid!arteries!and!abdominal!fat!is!being!carried!out!on!a!large!subset!
(~100,000)!of!participants![5].!
!
Understanding!the!role!that!genetics!plays!in!phenotypic!and!disease!variation,!and!
its!potential!interactions!with!other!factors,!provides!a!critical!route!to!a!better!
understanding!of!human!biology.!!It!is!anticipated!that!this!will!lead!to!more-
successful!drug!development![6]!,!and!potentially!to!more!efficient!and!personalised!
treatments!and!to!better!diagnoses.!As!such,!a!key!component!of!the!UK!Biobank!
resource!has!been!the!collection!of!genome-wide!genetic!data!on!every!participant!
using!a!purpose-designed!genotyping!array![7].!An!interim!release!of!genotype!data!
on!~150,000!UK!Biobank!participants!(May!2015)![8]!has!already!facilitated!
numerous!studies![9].!These!exploit!the!UK!Biobank’s!substantial!sample!size,!
extensive!phenotype!information,!and!genome-wide!genetic!information!to!study!
the!often!subtle!and!complex!effects!of!genetics!on!human!traits!and!disease,!and!its!
potential!interactions!with!other!factors![10-15].!!
!
In!this!paper!we!describe!the!genetic!dataset!on!the!full!~500,000!participants,!
together!with!a!range!of!quality!control!procedures,!which!have!been!undertaken!on!
the!genotype!data!in!the!hope!of!facilitating!its!wider!use.!!To!achieve!this!we!
designed!and!implemented!a!quality!control!(QC)!pipeline!that!addresses!challenges!
specific!to!the!experimental!design,!scale,!and!diversity!of!this!dataset.!!Raw!data!
from!the!genotyping!experiments!will!be!available!from!UK!Biobank.!!We!also!
conducted!a!set!of!analyses!that!reveal!properties!of!the!genetic!data!–!such!as!
population!structure!and!relatedness!–!that!can!be!important!for!downstream!
analyses.!!In!addition,!we!phased!and!imputed!genotypes!into!the!dataset,!using!
computationally!efficient!methods!combined!with!the!Haplotype!Reference!
Consortium!(HRC)![16]!and!UK10K!haplotype!resources![17].!!This!increases!the!
number!of!testable!variants!by!over!100-fold!to!~96!million!variants.!We!also!
imputed!classical!allelic!variation!at!11!human!leukocyte!antigen!(HLA)!genes,!and!as!
not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.
The copyright holder for this preprint (which wasthis version posted July 20, 2017. ; https://doi.org/10.1101/166298doi: bioRxiv preprint

5!
!
a!QC!check!of!this!imputation,!we!replicate!signals!of!known!associations!between!
HLA!alleles!and!many!common!diseases.!!We!describe!tools!that!allow!efficient!
genome-wide!association!studies!(GWAS)!of!multiple!traits!and!fast!phenome-wide!
association!studies!(PheWAS),!which!work!together!with!a!new!compressed!file!
format!that!has!been!used!to!distribute!the!dataset.!!As!a!further!check!of!the!
genotyped!and!imputed!datasets,!we!performed!a!test-case!genome-wide!
association!scan!on!a!well-studied!human!trait,!standing!height.!!
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The!data!release!contains!genotypes!of!488,377!UK!Biobank!participants.!!These!
were!assayed!using!two!very!similar!genotyping!arrays.!!A!subset!of!49,950!
participants!involved!in!the!UK!Biobank!Lung!Exome!Variant!Evaluation!(UK!BiLEVE)!
study!were!genotyped!using!the!Applied!Biosystems™!UK!BiLEVE!Axiom™!Array!by!
Affymetrix
1
!(807,411!markers),!which!is!described!elsewhere![15].!!Following!this,!
438,427!participants!were!genotyped!using!the!closely-related!Applied!Biosystems™!
UK!Biobank!Axiom™!Array!(825,927!markers).!!Both!arrays!were!purpose-designed!
specifically!for!the!UK!Biobank!genotyping!project!and!share!95%!of!marker!content!
[7].!!The!marker!content!of!the!UK!Biobank!Axiom™!array!was!chosen!to!capture!
genome-wide!genetic!variation!(single!nucleotide!polymorphism!(SNPs)!and!short!
insertions!and!deletions!(indels)),!and!is!summarised!in!@(+Q8"*>.!!Many!markers!
were!included!because!of!known!associations!with,!or!possible!roles!in,!phenotypic!
variation,!particularly!disease.!A!notable!example!is!the!inclusion!of!two!variants,!
rs429358!and!rs7412,!which!define!the!isoforms!of!the!apolipoprotein!E!(APoE)!gene!
known!to!be!associated!with!risk!of!Alzheimer’s!disease![7]!and!other!conditions.!!
Neither!marker!is!easy!to!type!using!array!technologies;!as!a!consequence!of!this!
they!have!not!always!been!assayed!on!earlier!arrays.!!The!array!also!includes!coding!
variants!across!a!range!of!minor!allele!frequencies!(MAFs),!including!rare!markers!
(<1%!MAF);!and!markers!that!provide!good!genome-wide!coverage!for!imputation!in!
European!populations!in!the!common!(>5%)!and!low!frequency!(1-5%)!MAF!ranges.!
Further!details!of!the!array!design!are!in![7].!!
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not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.
The copyright holder for this preprint (which wasthis version posted July 20, 2017. ; https://doi.org/10.1101/166298doi: bioRxiv preprint

Frequently asked questions

Q1. What are the contributions mentioned in the paper "Genome-wide genetic data on ~500,000 uk biobank participants" ?

The UK Biobank dataset this paper is a large prospective cohort study of ~500,000 individuals from across the United Kingdom, aged between 40-69 at recruitment.