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

2017 ◽  
Author(s):  
Clare Bycroft ◽  
Colin Freeman ◽  
Desislava Petkova ◽  
Gavin Band ◽  
Lloyd T. Elliott ◽  
...  
Keyword(s):  
Quality Control ◽  
Allelic Variation ◽  
Association Studies ◽  
Genetic Data ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genotype Data ◽  
Uk Biobank ◽  
Genome Wide ◽  
Wide Range

AbstractThe 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.

scholarly journals Genome-wide association study of liking of physical activity in the UK Biobank

2021 ◽  
Author(s):  
Yann C. Klimentidis ◽  
Michelle Newell ◽  
Matthijs D. van der Zee ◽  
Victoria L. Bland ◽  
Sebastian May-Wilson ◽  
...  
Keyword(s):  
Physical Activity ◽  
Genome Wide Association Study ◽  
Association Studies ◽  
Genome Wide Association ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Genome Wide ◽  
Wide Range ◽  
The Uk

A lack of physical activity (PA) is one of the most pressing health issues facing society today. Our individual propensity for PA is partly influenced by genetic factors. Stated liking of various PA behaviors may capture additional dimensions of PA behavior that are not captured by other measures, and contribute to our understanding of the genetics of PA behavior. Here, in over 157,000 individuals from the UK Biobank, we sought to complement and extend previous findings on the genetics of PA behavior by performing genome-wide association studies of self-reported liking of several PA-related behaviors plus an additional derived trait of overall PA-liking. We identified a total of 19 unique genome-wide significant loci across all traits, only four of which overlap with loci previously identified for PA behavior. The PA-liking traits were genetically correlated with self-reported (rg: 0.38 to 0.80) and accelerometry-derived (rg: 0.26 to 0.49) PA measures, and with a wide range of health-related traits and dietary behaviors. Replication in the Netherlands Twin Register (NTR; n>7,300) and the TwinsUK (n>1,300) study revealed directionally consistent associations. Polygenic risk scores (PRS) were then trained in UKB for each PA-liking trait and for self-reported PA behavior. The PA-liking PRS significantly predicted the same liking trait in NTR. The PRS for liking of going to the gym predicted PA behavior in NTR (r2 = 0.40%) nearly as well as the one constructed based on self-reported PA behavior (r2 = 0.42%). Combining the two PRS into a single model increased the r2 to 0.59%, suggesting that although these PRS correlate with each other, they are also capturing distinct dimensions of PA behavior. In conclusion, we have identified the first loci associated with PA-liking, and extended and refined our understanding of the genetic basis of PA behavior.

scholarly journals GWAS of three molecular traits highlights core genes and pathways alongside a highly polygenic background

2020 ◽  
Author(s):  
Nasa Sinnott-Armstrong ◽  
Sahin Naqvi ◽  
Manuel Rivas ◽  
Jonathan K Pritchard
Keyword(s):  
Complex Traits ◽  
Genetic Basis ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Biological Processes ◽  
Uk Biobank ◽  
The Core ◽  
Genome Wide ◽  
Core Genes

SummaryGenome-wide association studies (GWAS) have been used to study the genetic basis of a wide variety of complex diseases and other traits. However, for most traits it remains difficult to interpret what genes and biological processes are impacted by the top hits. Here, as a contrast, we describe UK Biobank GWAS results for three molecular traits—urate, IGF-1, and testosterone—that are biologically simpler than most diseases, and for which we know a great deal in advance about the core genes and pathways. Unlike most GWAS of complex traits, for all three traits we find that most top hits are readily interpretable. We observe huge enrichment of significant signals near genes involved in the relevant biosynthesis, transport, or signaling pathways. We show how GWAS data illuminate the biology of variation in each trait, including insights into differences in testosterone regulation between females and males. Meanwhile, in other respects the results are reminiscent of GWAS for more-complex traits. In particular, even these molecular traits are highly polygenic, with most of the variance coming not from core genes, but from thousands to tens of thousands of variants spread across most of the genome. Given that diseases are often impacted by many distinct biological processes, including these three, our results help to illustrate why so many variants can affect risk for any given disease.

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.

Genetic Data Analysis

2021 ◽  
pp. 358-372
Author(s):  
M. Shamila ◽  
Amit Kumar Tyagi
Keyword(s):  
Data Analysis ◽  
Association Studies ◽  
Single Gene ◽  
Genetic Data ◽  
Building Blocks ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Human Beings ◽  
Genome Wide ◽  
Genetic Data Analysis

Genome-wide association studies (GWAS) or genetic data analysis is used to discover common genetic factors which influence the health of human beings and become a part of a disease. The concept of using genomics has increased in recent years, especially in e-healthcare. Today there is huge improvement required in this field or genomics. Note that the terms genomics and genetics are not similar terms here. Basically, the human genome is made up of DNA, which consists of four different chemical building blocks (called bases and abbreviated A, T, C, and G). Based on this, we differentiate each and every human being living on earth. The term ‘genetics' originated from the Greek word ‘genetikos'. It means ‘origin'. In simple terms, genetics can be defined as a branch of biology, which deals with the study of the functionalities and composition of a single gene in an organism. There are mainly three branches of genetics, which include classical genetics, molecular genetics, and population genetics.

scholarly journals GWASTools: an R/Bioconductor package for quality control and analysis of genome-wide association studies

2012 ◽  
Vol 28 (24) ◽  
pp. 3329-3331 ◽  
Author(s):  
S. M. Gogarten ◽  
T. Bhangale ◽  
M. P. Conomos ◽  
C. A. Laurie ◽  
C. P. McHugh ◽  
...  
Keyword(s):  
Quality Control ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Bioconductor Package ◽  
Genome Wide

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.

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