Advancing human genetics research and drug discovery through exome sequencing of the UK Biobank

Szustakowski, Joseph D.; Balasubramanian, Suganthi; Kvikstad, Erika; Khalid, Shareef; Bronson, Paola G.; Sasson, Ariella; Wong, Emily H. M.; Liu, Daren; Davis, J. Wade; Haefliger, Carolina; Loomis, A. Katrina; Mikkilineni, Rajesh; Noh, Hyun Ji; Wadhawan, Samir; Bai, Xiaodong; Hawes, Alicia; Krasheninina, Olga; Ulloa, Ricardo H.; Lopez, A; Smith, Erin N.; Waring, Jeffrey F.; Whelan, Christopher D.; Tsai, Ellen; Overton, John D.; Salerno, William; Jacob, Howard J.; Szalma, Sándor; Runz, Heiko; Hinkle, Gregory; Nioi, Paul; Petrovski, Steve; Miller, Melissa R.; Baras, Aris; Mitnaul, Lyndon J.; Reid, Jeffrey G.

doi:10.1038/s41588-021-00885-0

Cited by 281 publications

(173 citation statements)

References 45 publications

Supporting

Mentioning

172

Contrasting

Order By: Relevance

“…Genome-wide association studies have uncovered thousands of common variants associated with human disease, but the contribution of rare variation to common disease remains relatively unexplored. The UK Biobank (UKB) contains detailed phenotypic data linked to medical records for approximately 500,000 participants, offering an unprecedented opportunity to evaluate the impact of rare variation on a broad collection of traits 1,2 . Here, we studied the relationships between rare protein-coding variants and 17,361 binary and 1,419 quantitative phenotypes using exome sequencing data from 269,171 UKB participants of European ancestry.…”

mentioning

confidence: 99%

“…The UKB offers an unprecedented opportunity to assess the contribution of both common and rare genetic variation to thousands of human traits and diseases 1,2,[9][10][11][12][13] . Testing for the association between rare variants and phenotypes is typically performed at the level variant or gene level.…”

mentioning

confidence: 99%

“…Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Waltham, MA, USA. 2 Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK. 3 Translational Science and Experimental Medicine, Research and Early Development, Respiratory and Immunology, BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden.…”

mentioning

confidence: 99%

See 2 more Smart Citations

Rare variant contribution to human disease in 281,104 UK Biobank exomes

Wang

Dhindsa

Carss

et al. 2021

Nature

Self Cite

326

441

View full text Add to dashboard Cite

Genome-wide association studies have uncovered thousands of common variants associated with human disease, but the contribution of rare variation to common disease remains relatively unexplored. The UK Biobank (UKB) contains detailed phenotypic data linked to medical records for approximately 500,000 participants, offering an unprecedented opportunity to evaluate the impact of rare variation on a broad collection of traits1,2. Here, we studied the relationships between rare protein-coding variants and 17,361 binary and 1,419 quantitative phenotypes using exome sequencing data from 269,171 UKB participants of European ancestry. Gene-based collapsing analyses revealed 1,703 statistically significant gene-phenotype associations for binary traits, with a median odds ratio of 12.4. Furthermore, 83% of these associations were undetectable via single variant association tests, emphasizing the power of gene-based collapsing analysis in the setting of high allelic heterogeneity. Gene-phenotype associations were also significantly enriched for loss-of-function-mediated traits and approved drug targets. Finally, we performed ancestry-specific and pan-ancestry collapsing analyses using exome sequencing data from 11,933 UKB participants of African, East Asian, or South Asian ancestry. Together, our results highlight a significant contribution of rare variants to common disease. Summary statistics are publicly available through an interactive portal (http://azphewas.com/).

show abstract

mentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

See 1 more Smart Citation

Rare variant contribution to human disease in 281,104 UK Biobank exomes

Wang

Dhindsa

Carss

et al. 2021

Nature

Self Cite

326

441

View full text Add to dashboard Cite

show abstract

“…3 and Fig. 4), we identified carriers of high-confidence loss-of-function SNP and indel variants (annotated using LOFTEE 55 ) among the 185,365 individuals with whole-exome sequencing data 27 in our analysis set. To increase power to assess phenotypic impacts of SNP and indel PTVs, we residualized phenotypes for polygenic predictions of the phenotype using array-typed SNPs (omitting those within 2Mb of the gene of interest) that we generated using BOLT-LMM '-predBetasFile' in 10-fold cross-validation (emulating linear mixed model association analysis) 57 .…”

Section: Follow-up Analyses At Highlighted Locimentioning

confidence: 99%

Influences of rare copy number variation on human complex traits

Hujoel

Sherman

Barton

et al. 2021

Preprint

View full text Add to dashboard Cite

The human genome contains hundreds of thousands of regions exhibiting copy number variation (CNV). However, the phenotypic effects of most such polymorphisms are unknown because only larger CNVs (spanning tens of kilobases) have been ascertainable from the SNP-array data generated by large biobanks. We developed a new computational approach that leverages abundant haplotype-sharing in biobank cohorts to more sensitively detect CNVs co-inherited within extended SNP haplotypes. Applied to UK Biobank, this approach achieved 6-fold increased CNV detection sensitivity compared to previous analyses, accounting for approximately half of all rare gene inactivation events produced by genomic structural variation. This extensive CNV call set enabled the most comprehensive analysis to date of associations between CNVs and 56 quantitative traits, identifying 269 independent associations (P < 5 x 10-8) - involving 97 loci - that rigorous statistical fine-mapping analyses indicated were likely to be causally driven by CNVs. Putative target genes were identifiable for nearly half of the loci, enabling new insights into dosage-sensitivity of these genes and implicating several novel gene-trait relationships. CNVs at several loci created extended allelic series including deletions or duplications of distal enhancers that associated with much stronger phenotypic effects than SNPs within these regulatory elements. These results demonstrate the ability of haplotype-informed analysis to empower structural variant detection and provide insights into the genetic basis of human complex traits.

show abstract

“…For this study, we used 200,624 Whole Exome Sequencing datasets from the UK Biobank 200k release generated using the IDT xGen Exome Research Panel v1.0 including supplemental probes and sequenced with dual-indexed 75x75 bp paired-end reads on the Illumina NovaSeq 6000 platform using S2 and S4 flow cells (168). We used the aligned CRAM files from the OQFE pipeline which aligned and duplicate-marked all raw sequencing data (FASTQs) against the full GRCh38 reference in an alt-aware manner as described in the original FE manuscript (169). These aligned sequence datasets were used as the primary input in the CNest pipeline (Details below) for exome-wide copy number estimation and CNV calling.…”

Section: Sample Cohort and Phenotypesmentioning

confidence: 99%

CNest: A Novel Copy Number Association Discovery Method Uncovers 862 New Associations from 200,629 Whole Exome Sequence Datasets in the UK Biobank

Fitzgerald

Birney

2021

Preprint

View full text Add to dashboard Cite

Copy number variation (CNV) has long been known to influence human traits having a rich history of research into common and rare genetic disease and although CNV is accepted as an important class of genomic variation, progress on copy number (CN) phenotype associations from Next Generation Sequencing data (NGS) has been limited, in part, due to the relative difficulty in CNV detection and an enrichment for large numbers of false positives. To date most successful CN genome wide association studies (CN-GWAS) have focused on using predictive measures of dosage intolerance or gene burden tests to gain sufficient power for detecting CN effects. Here we present a novel method for large scale CN analysis from NGS data generating robust CN estimates and allowing CN-GWAS to be performed genome wide in discovery mode. We provide a detailed analysis in the large scale UK BioBank resource and a specifically designed software package for deriving CN estimates from NGS data that are robust enough to be used for CN-GWAS. We use these methods to perform genome wide CN-GWAS analysis across 78 human traits discovering 862 genetic associations that are likely to contribute strongly to trait distributions based solely on their CN or by acting in concert with other genetic variation. Finally, we undertake an analysis comparing CNV and SNP association signals across the same traits and samples, defining specific CNV association classes based on whether they could be detected using standard SNP-GWAS in the UK Biobank.

show abstract

Advancing human genetics research and drug discovery through exome sequencing of the UK Biobank

Cited by 281 publications

References 45 publications

Rare variant contribution to human disease in 281,104 UK Biobank exomes

Rare variant contribution to human disease in 281,104 UK Biobank exomes

Influences of rare copy number variation on human complex traits

CNest: A Novel Copy Number Association Discovery Method Uncovers 862 New Associations from 200,629 Whole Exome Sequence Datasets in the UK Biobank

Contact Info

Product

Resources

About