Medical relevance of protein-truncating variants across 337,205 individuals in the UK Biobank study

DeBoever, Christopher; Tanigawa, Yosuke; Lindholm, Maléne E.; McInnes, Gregory; Lavertu, Adam; Ingelsson, Erik; Chang, Chris; Ashley, Euan A.; Bustamante, Carlos D.; Daly, Mark J.; Rivas, Manuel A.

doi:10.1038/s41467-018-03910-9

Cited by 113 publications

(126 citation statements)

References 76 publications

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“…We annotated variants using the VEP LOFTEE plugin (https://github.com/konradjk/loftee) and variant quality control by comparing allele frequencies in the UK Biobank and gnomAD (gnomad.exomes.r2.0.1.sites.vcf.gz) as previously described 28 . We focused on variants outside of major histocompatibility complex (MHC) region (chr6:2547779736448354) and performed LDpruning using PLINK with "indep 50 5 2" as previously described 28,65 . The LDpruned sets are used for targeted PheWAS analysis described below.…”

Section: Genotype and Phenotype Datamentioning

confidence: 99%

Genetics of 38 blood and urine biomarkers in the UK Biobank

Sinnott-Armstrong

Tanigawa

Amar

et al. 2019

Preprint

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Clinical laboratory tests are a critical component of the continuum of care and provide a means for rapid diagnosis and monitoring of chronic disease. In this study, we systematically evaluated the genetic basis of 38 blood and urine laboratory tests measured in 358,072 participants in the UK Biobank and identified 1,857 independent loci associated with at least one laboratory test, including 488 largeeffect protein truncating, missense, and copynumber variants. We tested these loci for enrichment in specific single cell types in kidney, liver, and pancreas relevant to disease aetiology. We then causally linked the biomarkers to medically relevant phenotypes through genetic correlation and Mendelian randomization. Finally, we developed polygenic risk scores (PRS) for each biomarker and built multiPRS models using all 38 PRSs simultaneously. We found substantially improved prediction of incidence in FinnGen (n=135,500) with the multiPRS relative to singledisease PRSs for renal failure, myocardial infarction, liver fat percentage, and alcoholic cirrhosis. Together, our results show the genetic basis of these biomarkers, which tissues contribute to the biomarker function, the causal influences of the biomarkers, and how we can use this to predict disease. 45 50 55 60 65 70 75 80 85 90 95 100

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Section: Genotype and Phenotype Datamentioning

confidence: 99%

Genetics of 38 blood and urine biomarkers in the UK Biobank

Sinnott-Armstrong

Tanigawa

Amar

et al. 2019

Preprint

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“…The MHC region was excluded. Data were preprocessed as explained in 24 with a small change: we excluded variants with a MAF < 5%. 70 phenotypes (traits and diseases) were selected for the analysis, see Supplementary Table 1 .…”

Section: Methodsmentioning

confidence: 99%

Constraint-based analysis for causal discovery in population-based biobanks

Amar

Ashley

Rivas

2019

Preprint

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Availability of large genetic databases has led to the development of powerful causal inference methods that use genetic variables as instruments to estimate causal effects. Such methods typically make many assumptions about the underlying causal graphical model, are limited in the patterns they search for in the data, and there is no guide for systematic analysis of a large database. Here, we present cGAUGE, a new pipeline for causal Graphical Analysis Using GEnetics that utilizes large changes in the significance of local conditional independencies between the genetic instruments and the phenotypes. We detect cases where causal inference can be performed with minimal risk of horizontal pleiotropy. Moreover, we search for new graphical patterns to reveal novel information about the underlying causal diagram that is not covered by extant methods, including new direct links, colliders, and evidence for confounding.We present theoretical justification, simulations, and apply our pipeline to 70 complex phenotypes from 337,198 subjects from the UK Biobank. Our results cover 102 detected causal relationships, of which some are new and many are expected. For example, we detect a direct causal link from high cholesterol to angina and a feedback loop between angina and myocardial infarction. We also corroborate a recent observational link between asthma and Crohn's disease. Finally, we detect important features of the causal network structure including several causal hubs such as intelligence and waist circumference.

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“…For British individuals (n = 337,151) in UK Biobank as described elsewhere 8 , we applied genome-wide association analysis for directly genotyped variants were applied to Goldmann-correlated intraocular pressure described more detailed earlier 10 (right, UK Biobank Field ID 5255, Global Biobank Engine phenotype ID: INI5255) and glaucoma (Global Biobank Engine phenotype ID: HC276, which is previously defined as a part of "high confidence" disease outcome phenotypes by combining disease diagnoses from the UK National Health Service Hospital Episode Statistics with self-reported diagnoses questionnaire 8 ), using generalized linear model association analysis implemented in PLINK v2.00aLM (2 April 2019) with age, sex, types of genotyping array, and the first 4 genotype principal components as described elsewhere 11,27 .…”

Section: Genome-wide Association Analysis In Uk Biobankmentioning

confidence: 99%

“…Here we leverage two population biobanks that provide complementarity for glaucoma gene discovery. First, UK Biobank has obtained intraocular pressure (IOP) measurements in approximately 128,000 individuals in addition to case-control status for glaucoma from hospital in-patient and verbal questionnaire data in over 500,000 individuals 7,8 . Second, FinnGen has directly genotyped and aggregated disease outcomes in over 135,000 individuals from Finland, an isolated population with recent bottlenecks that offers an unprecedented advantage for studying rare variants in complex diseases 9 .…”

Section: Introductionmentioning

confidence: 99%

Rare protein-altering variants in ANGPTL7 lower intraocular pressure and protect against glaucoma

Tanigawa

Wainberg

Karjalainen

et al. 2019

Preprint

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Protein-altering variants that are protective against human disease provide in vivo validation of therapeutic targets. Here we use genotyping data in UK Biobank and FinnGen to conduct a search for protein-altering variants conferring lower intraocular pressure (IOP) and protection against glaucoma. Through protein-altering variant association analysis we find a missense variant in UK Biobank (rs28991009 (MAF=0.8%) genotyped in 81,527 individuals with measured IOP and an independent set of 4,269 glaucoma patients and 251,355 controls) that significantly lowers IOP (β = −0.73 mmHg for heterozygotes, −2.96 mmHg for homozygotes, P = 1 × 10−13) and is associated with 34% reduced risk of glaucoma (P = 0.005). In FinnGen, we identify an ANGPTL7 missense variant at a greater than 50-fold increased frequency in Finland compared with other populations (rs147660927, p.Arg220Cys, MAF Finland = 4.1%), which was genotyped in 5,177 glaucoma patients and 130,461 controls and is associated with 30% lower glaucoma risk (P = 1 × 10−9). We further find three rarer variants in UK Biobank, including a protein-truncating variant, which confer a strong composite lowering of IOP (P = 0.002), suggesting the protective mechanism likely resides in the loss of an interaction or function. Our results support inhibition or down-regulation of ANGPTL7 as a therapeutic strategy for glaucoma

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Medical relevance of protein-truncating variants across 337,205 individuals in the UK Biobank study

Cited by 113 publications

References 76 publications

Genetics of 38 blood and urine biomarkers in the UK Biobank

Genetics of 38 blood and urine biomarkers in the UK Biobank

Constraint-based analysis for causal discovery in population-based biobanks

Rare protein-altering variants in ANGPTL7 lower intraocular pressure and protect against glaucoma

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