scholarly journals Reproducibility in the UK Biobank of Genome-Wide Significant Signals Discovered in Earlier Genome-wide Association Studies

2020 ◽  
Author(s):  
Jack W. O’Sullivan ◽  
John P. A. Ioannidis
Keyword(s):  
Effect Size ◽  
Association Studies ◽  
Genome Wide Association ◽  
P Value ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Single Nucleotide ◽  
Genome Wide ◽  
The Uk ◽  
Open Question

AbstractWith the establishment of large biobanks, discovery of single nucleotide polymorphism (SNPs) that are associated with various phenotypes has been accelerated. An open question is whether SNPs identified with genome-wide significance in earlier genome-wide association studies (GWAS) are replicated also in later GWAS conducted in biobanks. To address this question, the authors examined a publicly available GWAS database and identified two, independent GWAS on the same phenotype (an earlier, “discovery” GWAS and a later, replication GWAS done in the UK biobank). The analysis evaluated 136,318,924 SNPs (of which 6,289 had reached p<5e-8 in the discovery GWAS) from 4,397,962 participants across nine phenotypes. The overall replication rate was 85.0% and it was lower for binary than for quantitative phenotypes (58.1% versus 94.8% respectively). There was a18.0% decrease in SNP effect size for binary phenotypes, but a 12.0% increase for quantitative phenotypes. Using the discovery SNP effect size, phenotype trait (binary or quantitative), and discovery p-value, we built and validated a model that predicted SNP replication with area under the Receiver Operator Curve = 0.90. While non-replication may often reflect lack of power rather than genuine false-positive findings, these results provide insights about which discovered associations are likely to be seen again across subsequent GWAS.

scholarly journals Reproducibility in the UK Biobank of Genome-Wide Significant Signals Discovered in Earlier Genome-Wide Association Studies

2021 ◽  
Author(s):  
Jack W. O’Sullivan ◽  
John P . A. Ioannidis
Keyword(s):  
Effect Size ◽  
Association Studies ◽  
Significant Snps ◽  
Genome Wide Association ◽  
P Value ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Genome Wide ◽  
The Uk ◽  
Open Question

Abstract With the establishment of large biobanks, discovery of single nucleotide polymorphism (SNPs) associated with various phenotypes has accelerated. An open question is whether genome-wide significant SNPs identified in earlier genome-wide association studies (GWAS) are replicated in later GWAS conducted in biobanks. To address this, we examined a publicly available GWAS database and identified two, independent GWAS on the same phenotype (an earlier, “discovery” GWAS and a later, “replication” GWAS done in UK biobank). The analysis evaluated 136,318,924 SNPs (of which 6,289 reached p<5e-8 in the discovery GWAS) from 4,397,962 participants across nine phenotypes. The overall replication rate was 85.0%; although lower for binary than quantitative phenotypes (58.1% versus 94.8% respectively). There was a 18.0% decrease in SNP effect size for binary phenotypes, but a 12.0% increase for quantitative phenotypes. Using the discovery SNP effect size, phenotype trait (binary or quantitative), and discovery p-value, we built and validated a model that predicted SNP replication with area under the Receiver Operator Curve = 0.90. While non-replication may reflect lack of power rather than genuine false-positives, these results provide insights about which discovered associations are likely to be replicated across subsequent GWAS.

scholarly journals Reproducibility in the UK biobank of genome-wide significant signals discovered in earlier genome-wide association studies

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jack W. O’Sullivan ◽  
John P. A. Ioannidis
Keyword(s):  
Effect Size ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Uk Biobank ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Genome Wide ◽  
The Uk

AbstractWith the establishment of large biobanks, discovery of single nucleotide variants (SNVs, also known as single nucleotide polymorphisms (SNVs)) associated with various phenotypes has accelerated. An open question is whether genome-wide significant SNVs identified in earlier genome-wide association studies (GWAS) are replicated in later GWAS conducted in biobanks. To address this, we examined a publicly available GWAS database and identified two, independent GWAS on the same phenotype (an earlier, “discovery” GWAS and a later, “replication” GWAS done in the UK biobank). The analysis evaluated 136,318,924 SNVs (of which 6289 reached P < 5e−8 in the discovery GWAS) from 4,397,962 participants across nine phenotypes. The overall replication rate was 85.0%; although lower for binary than quantitative phenotypes (58.1% versus 94.8% respectively). There was a 18.0% decrease in SNV effect size for binary phenotypes, but a 12.0% increase for quantitative phenotypes. Using the discovery SNV effect size, phenotype trait (binary or quantitative), and discovery P value, we built and validated a model that predicted SNV replication with area under the Receiver Operator Curve = 0.90. While non-replication may reflect lack of power rather than genuine false-positives, these results provide insights about which discovered associations are likely to be replicated across subsequent GWAS.

scholarly journals The evolution of skin pigmentation associated variation in West Eurasia

2020 ◽  
Author(s):  
Dan Ju ◽  
Iain Mathieson
Keyword(s):  
Genetic Variants ◽  
Association Studies ◽  
Skin Pigmentation ◽  
Directional Selection ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Genome Wide ◽  
Light Skin ◽  
The Uk

AbstractSkin pigmentation is a classic example of a polygenic trait that has experienced directional selection in humans. Genome-wide association studies have identified well over a hundred pigmentation-associated loci, and genomic scans in present-day and ancient populations have identified selective sweeps for a small number of light pigmentation-associated alleles in Europeans. It is unclear whether selection has operated on all the genetic variation associated with skin pigmentation as opposed to just a small number of large-effect variants. Here, we address this question using ancient DNA from 1158 individuals from West Eurasia covering a period of 40,000 years combined with genome-wide association summary statistics from the UK Biobank. We find a robust signal of directional selection in ancient West Eurasians on skin pigmentation variants ascertained in the UK Biobank, but find this signal is driven mostly by a limited number of large-effect variants. Consistent with this observation, we find that a polygenic selection test in present-day populations fails to detect selection with the full set of variants; rather, only the top five show strong evidence of selection. Our data allow us to disentangle the effects of admixture and selection. Most notably, a large-effect variant at SLC24A5 was introduced to Europe by migrations of Neolithic farming populations but continued to be under selection post-admixture. This study shows that the response to selection for light skin pigmentation in West Eurasia was driven by a relatively small proportion of the variants that are associated with present-day phenotypic variation.SignificanceSome of the genes responsible for the evolution of light skin pigmentation in Europeans show signals of positive selection in present-day populations. Recently, genome-wide association studies have highlighted the highly polygenic nature of skin pigmentation. It is unclear whether selection has operated on all of these genetic variants or just a subset. By studying variation in over a thousand ancient genomes from West Eurasia covering 40,000 years we are able to study both the aggregate behavior of pigmentation-associated variants and the evolutionary history of individual variants. We find that the evolution of light skin pigmentation in Europeans was driven by frequency changes in a relatively small fraction of the genetic variants that are associated with variation in the trait today.

scholarly journals A meta-analysis of the genome-wide association studies on two genetically correlated phenotypes (self-reported headache and self-reported migraine) identifies four new risk loci for headaches (N=397,385)

2021 ◽  
Author(s):  
Weihua Meng ◽  
Parminder Reel ◽  
Charvi Nangia ◽  
Aravind Rajendrakumar ◽  
Harry Hebert ◽  
...  
Keyword(s):  
Association Studies ◽  
Meta Analysis ◽  
The Self ◽  
Genome Wide Association ◽  
P Value ◽  
Clinical Settings ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Genetic Mechanisms ◽  
The Uk

Headache is one of the commonest complaints that doctors need to address in clinical settings. The genetic mechanisms of different types of headache are not well understood. In this study, we performed a meta-analysis of genome-wide association studies (GWAS) on the self-reported headache phenotype from the UK Biobank cohort and the self-reported migraine phenotype from the 23andMe resource using the metaUSAT for genetically correlated phenotypes (N=397,385). We identified 38 loci for headaches, of which 34 loci have been reported before and 4 loci were newly identified. The LRP1-STAT6-SDR9C7 region in chromosome 12 was the most significantly associated locus with a leading P value of 1.24 x 10-62 of rs11172113. The ONECUT2 gene locus in chromosome 18 was the strongest signal among the 4 new loci with a P value of 1.29 x 10-9 of rs673939. Our study demonstrated that the genetically correlated phenotypes of self-reported headache and self-reported migraine can be meta-analysed together in theory and in practice to boost study power to identify more new variants for headaches. This study has paved way for a large GWAS meta-analysis study involving cohorts of different, though genetically correlated headache phenotypes.

scholarly journals Genome-wide association study of circulating liver enzymes reveals an expanded role for manganese transporter SLC30A10 in liver health

2020 ◽  
Author(s):  
Lucas D. Ward ◽  
Ho-Chou Tu ◽  
Chelsea Quenneville ◽  
Alexander O. Flynn-Carroll ◽  
Margaret M. Parker ◽  
...  
Keyword(s):  
Extrahepatic Bile Duct ◽  
Association Studies ◽  
Genome Wide Association ◽  
Detectable Effect ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Extrahepatic Bile Duct Cancer ◽  
Genome Wide ◽  
Liver Health ◽  
The Uk

AbstractTo better understand molecular pathways underlying liver health and disease, we performed genome-wide association studies (GWAS) on circulating levels of alanine aminotransferase (ALT) and aspartate aminotransferase (AST) across 408,300 subjects from four ethnic groups in the UK Biobank, focusing on variants associating with both enzymes. Of these variants, the strongest effect is a rare (MAF in White British = 0.12%) missense variant in the gene encoding manganese efflux transporter SLC30A10, Thr95Ile (rs188273166), associating with a 5.9% increase in ALT and a 4.2% increase in AST. Carriers have higher prevalence of all-cause liver disease (OR = 1.70; 95% CI = 1.24 to 2.34) and higher prevalence of extrahepatic bile duct cancer (OR = 23.8; 95% CI = 9.1 to 62.1) compared to non-carriers. Over 4% of the cases of extrahepatic cholangiocarcinoma in the UK Biobank carry SLC30A10 Thr95Ile. Unlike variants in SLC30A10 known to cause the recessive syndrome hypermanganesemia with dystonia-1 (HMNDYT1), the Thr95Ile variant has a detectable effect even in the heterozygous state. Also unlike HMNDYT1-causing variants, Thr95Ile results in a protein that is properly trafficked to the plasma membrane when expressed in HeLa cells. These results suggest that coding variation in SLC30A10 impacts liver health in more individuals than the small population of HMNDYT1 patients.

Body size and composition and site-specific cancers in UK Biobank: a Mendelian randomisation study

2020 ◽  
Author(s):  
Mathew Vithayathil ◽  
Paul Carter ◽  
Siddhartha Kar ◽  
Amy M. Mason ◽  
Stephen Burgess ◽  
...  
Keyword(s):  
Instrumental Variables ◽  
Association Studies ◽  
Genome Wide Association ◽  
Mendelian Randomisation ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Site Specific ◽  
Genome Wide ◽  
Increased Risk ◽  
The Uk

ABSTRACTObjectivesTo investigate the casual role of body mass index, body fat composition and height in cancer.DesignTwo stage mendelian randomisation studySettingPrevious genome wide association studies and the UK BiobankParticipantsGenetic instrumental variables for body mass index (BMI), fat mass index (FMI), fat free mass index (FFMI) and height from previous genome wide association studies and UK Biobank. Cancer outcomes from 367 586 participants of European descent from the UK Biobank.Main outcome measuresOverall cancer risk and 22 site-specific cancers risk for genetic instrumental variables for BMI, FMI, FFMI and height.ResultsGenetically predicted BMI (per 1 kg/m2) was not associated with overall cancer risk (OR 0.99; 95% confidence interval (CI) 0-98-1.00, p=0.105). Elevated BMI was associated with increased risk of stomach cancer (OR 1.15, 95% (CI) 1.05-1.26; p=0.003) and melanoma (OR 0.96, 95% CI 0.92-1.00; p=0.044). For sex-specific cancers, BMI was positively associated with uterine cancer (OR 1.08, 95% CI 1.01-1.14; p=0.015) but inversely associated with breast (OR 0.95, 95% CI 0.92-0.98; p=0.001), prostate (OR 0.95, 95% CI 0.92-0.99; p=0.007) and testicular cancer (OR 0.89, 95% CI 0.81-0.98; p=0.017). Elevated FMI (per 1 kg/m2) was associated with gastrointestinal cancer (stomach cancer OR 4.23, 95% CI 1.18-15.13, p=0.027; colorectal cancer OR 1.94, 95% CI 1.23-3.07; p=0.004). Increased height (per 1 standard deviation, approximately 6.5cm) was associated with increased risk of overall cancer (OR 1.06; 95% 1.04-1.09; p = 2.97×10-8) and most site-specific cancers with the strongest estimates for kidney, non-Hodgkin lymphoma, colorectal, lung, melanoma and breast cancer.ConclusionsThere is little evidence for BMI as a casual risk factor for cancer. BMI may have a causal role for sex-specific cancers, although with inconsistent directions of effect, and FMI for gastrointestinal malignancies. Elevated height is a risk factor for overall cancer and multiple site cancers.

scholarly journals Fine-scale population structure in the UK Biobank: implications for genome-wide association studies

2020 ◽  
Vol 29 (16) ◽  
pp. 2803-2811
Author(s):  
James P Cook ◽  
Anubha Mahajan ◽  
Andrew P Morris
Keyword(s):  
Population Structure ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Fine Scale ◽  
Uk Biobank ◽  
Genome Wide ◽  
Scale Population ◽  
The Uk ◽  
The Impact

Abstract The UK Biobank is a prospective study of more than 500 000 participants, which has aggregated data from questionnaires, physical measures, biomarkers, imaging and follow-up for a wide range of health-related outcomes, together with genome-wide genotyping supplemented with high-density imputation. Previous studies have highlighted fine-scale population structure in the UK on a North-West to South-East cline, but the impact of unmeasured geographical confounding on genome-wide association studies (GWAS) of complex human traits in the UK Biobank has not been investigated. We considered 368 325 white British individuals from the UK Biobank and performed GWAS of their birth location. We demonstrate that widely used approaches to adjust for population structure, including principal component analysis and mixed modelling with a random effect for a genetic relationship matrix, cannot fully account for the fine-scale geographical confounding in the UK Biobank. We observe significant genetic correlation of birth location with a range of lifestyle-related traits, including body-mass index and fat mass, hypertension and lung function, even after adjustment for population structure. Variants driving associations with birth location are also strongly associated with many of these lifestyle-related traits after correction for population structure, indicating that there could be environmental factors that are confounded with geography that have not been adequately accounted for. Our findings highlight the need for caution in the interpretation of lifestyle-related trait GWAS in UK Biobank, particularly in loci demonstrating strong residual association with birth location.

scholarly journals Genome-wide association study identifies 44 independent genomic loci for self-reported adult hearing difficulty in the UK Biobank cohort

2019 ◽  
Author(s):  
Helena RR. Wells ◽  
Maxim B. Freidin ◽  
Fatin N. Zainul Abidin ◽  
Antony Payton ◽  
Piers Dawes ◽  
...  
Keyword(s):  
Hearing Loss ◽  
Genome Wide Association Study ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Age Related ◽  
Genome Wide ◽  
Hearing Difficulty ◽  
The Uk

Age-related hearing impairment (ARHI) is the most common sensory impairment in the aging population; a third of individuals are affected by disabling hearing loss by the age of 651. ARHI is a multifactorial condition caused by both genetic and environmental factors, with estimates of heritability between 35% and 55%2–4. The genetic risk factors and underlying biological pathology of ARHI are largely unknown, meaning that targets for new therapies remain elusive. We performed genome-wide association studies (GWAS) for two self-reported hearing phenotypes, hearing difficulty (HDiff) and hearing aid use (HAid), using over 250,000 UK Biobank5 volunteers aged between 40-69 years. We identified 44 independent genome-wide significant loci (P<5E-08), 33 of which have not previously been associated with any form of hearing loss. Gene sets from these loci are enriched in auditory processes such as synaptic activities, nervous system processes, inner ear morphology and cognition. Immunohistochemistry for protein localisation in adult mouse cochlea indicate metabolic, sensory and neuronal functions for NID2, CLRN2 and ARHGEF28 identified in the GWAS. These results provide new insight into the genetic landscape underlying susceptibility to ARHI.

scholarly journals PS-202-Genome-wide association studies of abdominal MRI scans identifies loci associated with liver fat and liver iron in the UK Biobank

2019 ◽  
Vol 70 (1) ◽  
pp. e135
Author(s):  
Henry Wilman ◽  
Constantinos Parisinos ◽  
Matt Kelly ◽  
Stefan Neubauer ◽  
Louise Thomas ◽  
...  
Keyword(s):  
Association Studies ◽  
Genome Wide Association ◽  
Liver Fat ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Liver Iron ◽  
Genome Wide ◽  
Abdominal Mri ◽  
Mri Scans ◽  
The Uk

scholarly journals Summary statistics knockoff inference empowers identification of putative causal variants in genome-wide association studies

2021 ◽  
Author(s):  
Zihuai He ◽  
Linxi Liu ◽  
Michael E. Belloy ◽  
Yann Le Guen ◽  
Aaron Sossin ◽  
...  
Keyword(s):  
Genome Sequencing ◽  
Association Studies ◽  
Meta Analysis ◽  
Genome Wide Association ◽  
Superior Performance ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Genome Wide ◽  
Causal Variants ◽  
The Uk

AbstractRecent advances in genome sequencing and imputation technologies provide an exciting opportunity to comprehensively study the contribution of genetic variants to complex phenotypes. However, our ability to translate genetic discoveries into mechanistic insights remains limited at this point. In this paper, we propose an efficient knockoff-based method, GhostKnockoff, for genome-wide association studies (GWAS) that leads to improved power and ability to prioritize putative causal variants relative to conventional GWAS approaches. The method requires only Z-scores from conventional GWAS and hence can be easily applied to enhance existing and future studies. The method can also be applied to meta-analysis of multiple GWAS allowing for arbitrary sample overlap. We demonstrate its performance using empirical simulations and two applications: (1) analysis of 1,403 binary phenotypes from the UK Biobank data in 408,961 samples of European ancestry, and (2) a meta-analysis for Alzheimer’s disease (AD) comprising nine overlapping large-scale GWAS, whole-exome and whole-genome sequencing studies. The UK Biobank analysis demonstrates superior performance of the proposed method compared to conventional GWAS in both statistical power (2.05-fold more discoveries) and localization of putative causal variants at each locus (46% less proxy variants due to linkage disequilibrium). The AD meta-analysis identified 55 risk loci (including 31 new loci) with ~70% of the proximal genes at these loci showing suggestive signal in downstream single-cell transcriptomic analyses. Our results demonstrate that GhostKnockoff can identify putatively functional variants with weaker statistical effects that are missed by conventional association tests.

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