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Author

Alan Young

Other affiliations: Clinical Trial Service Unit
Bio: Alan Young is an academic researcher from University of Oxford. The author has contributed to research in topics: Biobank & Genome-wide association study. The author has an hindex of 3, co-authored 3 publications receiving 5962 citations. Previous affiliations of Alan Young include Clinical Trial Service Unit.

Papers
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Journal ArticleDOI
TL;DR: The UK Biobank is described, a large population-based prospective study, established to allow investigation of the genetic and non-genetic determinants of the diseases of middle and old age.
Abstract: Cathie Sudlow and colleagues describe the UK Biobank, a large population-based prospective study, established to allow investigation of the genetic and non-genetic determinants of the diseases of middle and old age.

6,114 citations

Journal ArticleDOI
11 Oct 2018-Nature
TL;DR: Deep phenotype and genome-wide genetic data from 500,000 individuals from the UK Biobank is described, describing population structure and relatedness in the cohort, and imputation to increase the number of testable variants to 96 million.
Abstract: The UK Biobank project is a prospective cohort study with deep genetic and phenotypic data collected on approximately 500,000 individuals from across the United Kingdom, aged between 40 and 69 at recruitment. The open resource is unique in its size and scope. A rich variety of phenotypic and health-related information is available on each participant, including biological measurements, lifestyle indicators, biomarkers in blood and urine, and imaging of the body and brain. Follow-up information is provided by linking health and medical records. Genome-wide genotype data have been collected on all participants, providing many opportunities for the discovery of new genetic associations and the genetic bases of complex traits. Here we describe the centralized analysis of the genetic data, including genotype quality, properties of population structure and relatedness of the genetic data, and efficient phasing and genotype imputation that increases the number of testable variants to around 96 million. Classical allelic variation at 11 human leukocyte antigen genes was imputed, resulting in the recovery of signals with known associations between human leukocyte antigen alleles and many diseases.

4,489 citations

Journal ArticleDOI
TL;DR: Preliminary evidence is provided to suggest that repeated 24-h dietary assessment via the Internet is acceptable to the public and a feasible strategy for large population-based studies.
Abstract: Although dietary intake over a single 24-h period may be atypical of an individual's habitual pattern, multiple 24-h dietary assessments can be representative of habitual intake and help in assessing seasonal variation. Web-based questionnaires are convenient for the participant and result in automatic data capture for study investigators. This study reports on the acceptability of repeated web-based administration of the Oxford WebQ--a 24-h recall of frequency from a set food list suitable for self-completion from which energy and nutrient values can be automatically generated. As part of the UK Biobank study, four invitations to complete the Oxford WebQ were sent by email over a 16-month period. Overall, 176 012 (53% of those invited) participants completed the online version of the Oxford WebQ at least once and 66% completed it more than once, although only 16% completed it on all four occasions. The response rate for any one round of invitations varied between 34 and 26%. On most occasions, the Oxford WebQ was completed on the same day that they received the invitation, although this was less likely if sent on a weekend. Participants who completed the Oxford WebQ tended to be white, female, slightly older, less deprived and more educated, which is typical of health-conscious volunteer-based studies. These findings provide preliminary evidence to suggest that repeated 24-h dietary assessment via the Internet is acceptable to the public and a feasible strategy for large population-based studies.

84 citations


Cited by
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Journal ArticleDOI
11 Oct 2018-Nature
TL;DR: Deep phenotype and genome-wide genetic data from 500,000 individuals from the UK Biobank is described, describing population structure and relatedness in the cohort, and imputation to increase the number of testable variants to 96 million.
Abstract: The UK Biobank project is a prospective cohort study with deep genetic and phenotypic data collected on approximately 500,000 individuals from across the United Kingdom, aged between 40 and 69 at recruitment. The open resource is unique in its size and scope. A rich variety of phenotypic and health-related information is available on each participant, including biological measurements, lifestyle indicators, biomarkers in blood and urine, and imaging of the body and brain. Follow-up information is provided by linking health and medical records. Genome-wide genotype data have been collected on all participants, providing many opportunities for the discovery of new genetic associations and the genetic bases of complex traits. Here we describe the centralized analysis of the genetic data, including genotype quality, properties of population structure and relatedness of the genetic data, and efficient phasing and genotype imputation that increases the number of testable variants to around 96 million. Classical allelic variation at 11 human leukocyte antigen genes was imputed, resulting in the recovery of signals with known associations between human leukocyte antigen alleles and many diseases.

4,489 citations

Journal ArticleDOI
TL;DR: FUMA is a web-based bioinformatics tool that uses a combination of positional, eQTL and chromatin interaction mapping to prioritize likely causal variants and genes and directly aid in generating hypotheses that are testable in functional experiments aimed at proving causal relations.
Abstract: A main challenge in genome-wide association studies (GWAS) is to pinpoint possible causal variants. Results from GWAS typically do not directly translate into causal variants because the majority of hits are in non-coding or intergenic regions, and the presence of linkage disequilibrium leads to effects being statistically spread out across multiple variants. Post-GWAS annotation facilitates the selection of most likely causal variant(s). Multiple resources are available for post-GWAS annotation, yet these can be time consuming and do not provide integrated visual aids for data interpretation. We, therefore, develop FUMA: an integrative web-based platform using information from multiple biological resources to facilitate functional annotation of GWAS results, gene prioritization and interactive visualization. FUMA accommodates positional, expression quantitative trait loci (eQTL) and chromatin interaction mappings, and provides gene-based, pathway and tissue enrichment results. FUMA results directly aid in generating hypotheses that are testable in functional experiments aimed at proving causal relations.

2,092 citations

Journal ArticleDOI
TL;DR: Genome-wide polygenic risk scores derived from GWAS data for five common diseases can identify subgroups of the population with risk approaching or exceeding that of a monogenic mutation.
Abstract: A key public health need is to identify individuals at high risk for a given disease to enable enhanced screening or preventive therapies. Because most common diseases have a genetic component, one important approach is to stratify individuals based on inherited DNA variation1. Proposed clinical applications have largely focused on finding carriers of rare monogenic mutations at several-fold increased risk. Although most disease risk is polygenic in nature2-5, it has not yet been possible to use polygenic predictors to identify individuals at risk comparable to monogenic mutations. Here, we develop and validate genome-wide polygenic scores for five common diseases. The approach identifies 8.0, 6.1, 3.5, 3.2, and 1.5% of the population at greater than threefold increased risk for coronary artery disease, atrial fibrillation, type 2 diabetes, inflammatory bowel disease, and breast cancer, respectively. For coronary artery disease, this prevalence is 20-fold higher than the carrier frequency of rare monogenic mutations conferring comparable risk6. We propose that it is time to contemplate the inclusion of polygenic risk prediction in clinical care, and discuss relevant issues.

1,962 citations

Journal ArticleDOI
TL;DR: UK Biobank is not representative of the sampling population; there is evidence of a “healthy volunteer” selection bias; valid assessment of exposure-disease relationships may be widely generalizable and does not require participants to be Representative of the population at large.
Abstract: The UK Biobank cohort is a population-based cohort of 500,000 participants recruited in the United Kingdom (UK) between 2006 and 2010. Approximately 9.2 million individuals aged 40-69 years who lived within 25 miles (40 km) of one of 22 assessment centers in England, Wales, and Scotland were invited to enter the cohort, and 5.5% participated in the baseline assessment. The representativeness of the UK Biobank cohort was investigated by comparing demographic characteristics between nonresponders and responders. Sociodemographic, physical, lifestyle, and health-related characteristics of the cohort were compared with nationally representative data sources. UK Biobank participants were more likely to be older, to be female, and to live in less socioeconomically deprived areas than nonparticipants. Compared with the general population, participants were less likely to be obese, to smoke, and to drink alcohol on a daily basis and had fewer self-reported health conditions. At age 70-74 years, rates of all-cause mortality and total cancer incidence were 46.2% and 11.8% lower, respectively, in men and 55.5% and 18.1% lower, respectively, in women than in the general population of the same age. UK Biobank is not representative of the sampling population; there is evidence of a "healthy volunteer" selection bias. Nonetheless, valid assessment of exposure-disease relationships may be widely generalizable and does not require participants to be representative of the population at large.

1,896 citations