scholarly journals Identifying the potential role of insomnia on multimorbidity: A Mendelian randomization phenome-wide association study in UK Biobank

2022 ◽  
Author(s):  
Mark J Gibson ◽  
Deborah A Lawlor ◽  
Louise AC Millard
Keyword(s):  
Health Outcomes ◽  
Association Study ◽  
Genetic Risk ◽  
Association Studies ◽  
Causal Effects ◽  
Mendelian Randomisation ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Wide Range

Objectives: To identify the breadth of potential causal effects of insomnia on health outcomes and hence its possible role in multimorbidity. Design: Mendelian randomisation (MR) Phenome-wide association study (MR-PheWAS) with two-sample Mendelian randomisation follow-up. Setting: Individual data from UK Biobank and summary data from a number of genome-wide association studies. Participants: 336,975 unrelated white-British UK Biobank participants. Exposures: Standardised genetic risk of insomnia for the MR-PheWAS and genetically predicted insomnia for the two-sample MR follow-up, with insomnia instrumented by a genetic risk score (GRS) created from 129 single-nucleotide polymorphisms (SNPs). Main outcomes measures: 11,409 outcomes from UK Biobank extracted and processed by an automated pipeline (PHESANT). Potential causal effects (i.e., those passing a Bonferroni-corrected significance threshold) were followed up with two-sample MR in MR-Base, where possible. Results: 437 potential causal effects of insomnia were observed for a number of traits, including anxiety, stress, depression, mania, addiction, pain, body composition, immune, respiratory, endocrine, dental, musculoskeletal, cardiovascular and reproductive traits, as well as socioeconomic and behavioural traits. We were able to undertake two-sample MR for 71 of these 437 and found evidence of causal effects (with directionally concordant effect estimates across all analyses) for 25 of these. These included, for example, risk of anxiety disorders (OR=1.55 [95% confidence interval (CI): 1.30, 1.86] per category increase in insomnia), diseases of the oesophagus/stomach/duodenum (OR=1.32 [95% CI: 1.14, 1.53]) and spondylosis (OR=1.57 [95% CI: 1.22, 2.01]). Conclusion: Insomnia potentially causes a wide range of adverse health outcomes and behaviours. This has implications for developing interventions to prevent and treat a number of diseases in order to reduce multimorbidity and associated polypharmacy.

scholarly journals Phenome-wide association study (PheWAS) of colorectal cancer risk SNP effects on health outcomes in UK Biobank

2021 ◽  
Author(s):  
Xiaomeng Zhang ◽  
Xue Li ◽  
Yazhou He ◽  
Philip J. Law ◽  
Susan M. Farrington ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Health Outcomes ◽  
Association Study ◽  
Diverticular Disease ◽  
Genetic Predisposition ◽  
Association Studies ◽  
Sensitivity Analyses ◽  
Polygenic Risk Score ◽  
Genome Wide Association Studies ◽  
Uk Biobank

Abstract Background Associations between colorectal cancer (CRC) and other health outcomes have been reported, but these may be subject to biases, or due to limitations of observational studies. Methods We set out to determine whether genetic predisposition to CRC is also associated with the risk of other phenotypes. Under the phenome-wide association study (PheWAS) and tree-structured phenotypic model (TreeWAS), we studied 334,385 unrelated White British individuals (excluding CRC patients) from the UK Biobank cohort. We generated a polygenic risk score (PRS) from CRC genome-wide association studies as a measure of CRC risk. We performed sensitivity analyses to test the robustness of the results and searched the Danish Disease Trajectory Browser (DTB) to replicate the observed associations. Results Eight PheWAS phenotypes and 21 TreeWAS nodes were associated with CRC genetic predisposition by PheWAS and TreeWAS, respectively. The PheWAS detected associations were from neoplasms and digestive system disease group (e.g. benign neoplasm of colon, anal and rectal polyp and diverticular disease). The results from the TreeWAS corroborated the results from the PheWAS. These results were replicated in the observational data within the DTB. Conclusions We show that benign colorectal neoplasms share genetic aetiology with CRC using PheWAS and TreeWAS methods. Additionally, CRC genetic predisposition is associated with diverticular disease.

scholarly journals P238 RA and multimorbidity in UK Biobank: association with all-cause mortality and major adverse cardiac events

Rheumatology ◽  
2020 ◽  
Vol 59 (Supplement_2) ◽  
Author(s):  
Barbara Nicholl ◽  
Ross McQueenie ◽  
Bhautesh Jani ◽  
Sara Macdonald ◽  
Colin McCowan ◽  
...  
Keyword(s):  
Health Outcomes ◽  
Major Adverse Cardiac Events ◽  
Uk Biobank ◽  
Cardiac Events ◽  
Long Term Conditions ◽  
Increased Risk ◽  
Adverse Cardiac Events ◽  
Wide Range ◽  
All Cause Mortality

Abstract Background Multimorbidity, the presence of ≥ 2 long-term conditions (LTCs) is common in people with rheumatoid arthritis (RA). However, most research in RA has focused on cardiovascular disease and depression as co-occurring morbidities, rather than multiple LTCs or a wide range of conditions. This study hypothesised that risk of all-cause mortality and major adverse cardiac events (MACE) would be greater in those with RA and ≥2 LTCs than those with RA only. Further, we explored which individual LTCs were associated with increased risk of mortality and MACE. Methods Data from UK Biobank, a cohort of over 500,000 adults aged 37-73 years across England, Scotland and Wales was analysed. RA and 42 other LTCs of interest were self-reported by participants in a questionnaire and nurse-led interview. Information on sociodemographic (age, gender, socioeconomic status) and lifestyle factors (smoking status, BMI, alcohol frequency, physical activity) were also gathered. Rheumatoid factor levels were also determined. MACE and mortality were classified using linked hospitalisations and mortality register data (median follow up time 9 years). Data were analysed using age-adjusted Cox’s proportional hazard modelling to calculate risk of all-cause mortality or MACE, adjusted for variables listed above. Predictor variable: no RA no LTCs (reference group), only RA, RA + 1-3LTCs, RA + ≥4LTCs. Finally, the relationship between comorbidity with individual LTCs (of the 42 studied) and both health outcomes was considered. Results 5,658 (1.1%) of participants in UK Biobank self-reported RA (69.8% female, mean age 59 years). 74.7% of participants reported at least one LTC in addition to RA (1-3 LTCs 64.3%, ≥4 LTCs 10.4%), compared to 63.8% of participants without RA. 7.7% (N = 437) of participants with RA died and 5.9% (n = 331) had MACE events during the follow-up period. There was a dose response relationship in RA between LTC category and all-cause mortality and MACE risk. Only RA: mortality HR 1.42, 95% CI 1.08, 1.87, MACE HR 1.61 95% CI 1.20, 2.18; RA + 1-3LTCs: mortality HR 1.99 95% CI 1.74, 2.27, MACE HR 1.89, 95% CI 1.61, 2.20; RA + ≥4LTCs: mortality HR 3.34, 95% CI 2.64, 4.22; MACE HR 3.45, 95% CI 2.66, 4.49) compared to those with no RA no LTCs (results presented from fully adjusted models). Of the 42 individual LTCs considered, comorbid osteoporosis was the most concerning; participants with both RA and osteoporosis had a two-fold increased risk of all-cause mortality (HR 2.20, 95% CI 1.55, 3.12) and three-fold increased risk of MACE outcomes (HR 3.17, 95% CI 2.17, 4.64) compared to those with neither condition. Conclusion Participants with RA and multimorbidity or comorbidity, particularly osteoporosis, are at increased risk of adverse health outcomes. These results have important clinical relevance for the monitoring and optimal management of RA across the healthcare system. Disclosures B. Nicholl None. R. McQueenie None. B. Jani None. S. Macdonald None. C. McCowan None. J. Canning None. F. Mair None. S. Siebert None.

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 Causal Associations Between Educational Attainment and 14 Urological and Reproductive Health Outcomes: A Mendelian Randomization Study

2021 ◽  
Vol 9 ◽  
Author(s):  
Menghua Wang ◽  
Zhongyu Jian ◽  
Xiaoshuai Gao ◽  
Chi Yuan ◽  
Xi Jin ◽  
...  
Keyword(s):  
Reproductive Health ◽  
Educational Attainment ◽  
Health Outcomes ◽  
Lower Risk ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Causal Effects ◽  
Genome Wide Association Studies ◽  
Bonferroni Correction ◽  
The Impact

Background: The impact of educational attainment (EA) on multiple urological and reproductive health outcomes has been explored in observational studies. Here we used Mendelian randomization (MR) to investigate whether EA has causal effects on 14 urological and reproductive health outcomes.Methods: We obtained summary statistics for EA and 14 urological and reproductive health outcomes from genome-wide association studies (GWAS). MR analyses were applied to explore the potential causal association between EA and them. Inverse variance weighted was the primary analytical method.Results: Genetically predicted one standard deviation (SD) increase in EA was causally associated with a higher risk of prostate cancer [odds ratio (OR) 1.14, 95% confidence interval (CI) 1.05–1.25, P = 0.003] and a reduced risk of kidney stone (OR 0.73, 95% CI 0.62–0.87, P < 0.001) and cystitis (OR 0.76, 95% CI 0.67–0.86, P < 0.001) after Bonferroni correction. EA was also suggestively correlated with a lower risk of prostatitis (OR 0.76, 95% CI 0.59–0.98, P = 0.037) and incontinence (OR 0.64, 95% CI 0.47–0.87, P = 0.004). For the bioavailable testosterone levels and infertility, sex-specific associations were observed, with genetically determined increased EA being related to higher levels of testosterone in men (β 0.07, 95% CI 0.04–0.10, P < 0.001), lower levels of testosterone in women (β −0.13, 95% CI−0.16 to−0.11, P < 0.001), and a lower risk of infertility in women (OR 0.74, 95% CI 0.64–0.86, P < 0.001) but was not related to male infertility (OR 0.79, 95% CI 0.52–1.20, P = 0.269) after Bonferroni correction. For bladder cancer, kidney cancer, testicular cancer, benign prostatic hyperplasia, and erectile dysfunction, no causal effects were observed.Conclusions: EA plays a vital role in urological diseases, especially in non-oncological outcomes and reproductive health. These findings should be verified in further studies when GWAS data are sufficient.

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 Personality, lifestyle and job satisfaction: causal association between neuroticism and job satisfaction using Mendelian randomisation in the UK biobank cohort

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Gull Rukh ◽  
Junhua Dang ◽  
Gaia Olivo ◽  
Diana-Maria Ciuculete ◽  
Mathias Rask-Andersen ◽  
...  
Keyword(s):  
Physical Activity ◽  
Job Satisfaction ◽  
Association Studies ◽  
Sensitivity Analyses ◽  
Mendelian Randomisation ◽  
Genome Wide Association Studies ◽  
Single Variable ◽  
Causal Association ◽  
Uk Biobank ◽  
The Uk

AbstractJob-related stress has been associated with poor health outcomes but little is known about the causal nature of these findings. We employed Mendelian randomisation (MR) approach to investigate the causal effect of neuroticism, education, and physical activity on job satisfaction. Trait-specific genetic risk score (GRS) based on recent genome wide association studies were used as instrumental variables (IV) using the UK Biobank cohort (N = 315,536). Both single variable and multivariable MR analyses were used to determine the effect of each trait on job satisfaction. We observed a clear evidence of a causal association between neuroticism and job satisfaction. In single variable MR, one standard deviation (1 SD) higher genetically determined neuroticism score (4.07 units) was associated with −0.31 units lower job satisfaction (95% confidence interval (CI): −0.38 to −0.24; P = 9.5 × 10−20). The causal associations remained significant after performing sensitivity analyses by excluding invalid genetic variants from GRSNeuroticism (β(95%CI): −0.28(−0.35 to −0.21); P = 3.4 x 10−15). Education (0.02; −0.08 to 0.12; 0.67) and physical activity (0.08; −0.34 to 0.50; 0.70) did not show any evidence for causal association with job satisfaction. When genetic instruments for neuroticism, education and physical activity were included together, the association of neuroticism score with job satisfaction was reduced by only −0.01 units, suggesting an independent inverse causal association between neuroticism score (P = 2.7 x 10−17) and job satisfaction. Our findings show an independent causal association between neuroticism score and job satisfaction. Physically active lifestyle may help to increase job satisfaction despite presence of high neuroticism scores. Our study highlights the importance of considering the confounding effect of negative personality traits for studies on job satisfaction.

scholarly journals EraSOR: Erase Sample Overlap in polygenic score analyses

2021 ◽  
Author(s):  
Shing Wan Choi ◽  
Timothy Shin Heng Mak ◽  
Clive J. Hoggart ◽  
Paul F. O'Reilly
Keyword(s):  
Association Studies ◽  
Polygenic Risk Score ◽  
Genome Wide Association Studies ◽  
Summary Statistics ◽  
Uk Biobank ◽  
Type 1 Error ◽  
Wide Range ◽  
Close Relatedness ◽  
Target Data

Background: Polygenic risk score (PRS) analyses are now routinely applied in biomedical research, with great hope that they will aid in our understanding of disease aetiology and contribute to personalized medicine. The continued growth of multi-cohort genome-wide association studies (GWASs) and large-scale biobank projects has provided researchers with a wealth of GWAS summary statistics and individual-level data suitable for performing PRS analyses. However, as the size of these studies increase, the risk of inter-cohort sample overlap and close relatedness increases. Ideally sample overlap would be identified and removed directly, but this is typically not possible due to privacy laws or consent agreements. This sample overlap, whether known or not, is a major problem in PRS analyses because it can lead to inflation of type 1 error and, thus, erroneous conclusions in published work. Results: Here, for the first time, we report the scale of the sample overlap problem for PRS analyses by generating known sample overlap across sub-samples of the UK Biobank data, which we then use to produce GWAS and target data to mimic the effects of inter-cohort sample overlap. We demonstrate that inter-cohort overlap results in a significant and often substantial inflation in the observed PRS-trait association, coefficient of determination (R2) and false-positive rate. This inflation can be high even when the absolute number of overlapping individuals is small if this makes up a notable fraction of the target sample. We develop and introduce EraSOR (Erase Sample Overlap and Relatedness), a software for adjusting inflation in PRS prediction and association statistics in the presence of sample overlap or close relatedness between the GWAS and target samples. A key component of the EraSOR approach is inference of the degree of sample overlap from the intercept of a bivariate LD score regression applied to the GWAS and target data, making it powered in settings where both have sample sizes over 1,000 individuals. Through extensive benchmarking using UK Biobank and HapGen2 simulated genotype-phenotype data, we demonstrate that PRSs calculated using EraSOR-adjusted GWAS summary statistics are robust to inter-cohort overlap in a wide range of realistic scenarios and are even robust to high levels of residual genetic and environmental stratification. Conclusion: The results of all PRS analyses for which sample overlap cannot be definitively ruled out should be considered with caution given high type 1 error observed in the presence of even low overlap between base and target cohorts. Given the strong performance of EraSOR in eliminating inflation caused by sample overlap in PRS studies with large (>5k) target samples, we recommend that EraSOR be used in all future such PRS studies to mitigate the potential effects of inter-cohort overlap and close relatedness.

scholarly journals Frequent Daytime Napping is Detrimental to Human Health: A phenotype-wide Mendelian Randomization Study

2020 ◽  
Author(s):  
Lanlan Chen ◽  
Aowen Tian ◽  
Zhipeng Liu ◽  
Miaoran Zhang ◽  
Xingchen Pan ◽  
...  
Keyword(s):  
Health Outcomes ◽  
Human Health ◽  
Mendelian Randomization ◽  
Wide Spectrum ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Major Depressive ◽  
Genome Wide ◽  
The Uk

ABSTRACTBackgroundIt remains controversial whether daytime napping is beneficial for human health.ObjectiveTo examine the causal relationship between daytime napping and the risk for various human diseases.DesignPhenotype-wide Mendelian randomization study.SettingNon-UK Biobank cohorts reported in published genome-wide association studies (GWAS) provided the outcome phenotypes in the discovery stage. The UK Biobank cohort provided the outcome phenotypes in the validation stage.ParticipantsThe UK Biobank GWAS included 361,194 European-ancestry residents in the UK. Non-UKBB GWAS included various numbers of participants.ExposureSelf-reported daytime napping frequency.Main outcome measureA wide-spectrum of human health outcomes including obesity, major depressive disorder, and high cholesterol.MethodsWe examined the causal relationship between daytime napping frequency in the UK Biobank as exposure and a panel of 1,146 health outcomes reported in genome-wide association studies (GWAS), using a two-sample Mendelian randomization analysis. The significant findings were further validated in the UK Biobank health outcomes of 4,203 human traits and diseases. The causal effects were estimated using a fixed-effect inverse variance weighted model. MR-Egger intercept test was applied to detect horizontal pleiotropy, along with Cochran’s Q test to assess heterogeneity among the causal effects of IVs.FindingsThere were significant causal relationships between daytime napping frequency and a wide spectrum of human health outcomes. In particular, we validated that frequent daytime napping increased the risks of major depressive disorder, obesity and abnormal lipid profile.InterpretationThe current study showed that frequent daytime napping mainly had adverse impacts on physical and mental health. Cautions should be taken for health recommendations on daytime napping. Further studies are necessary to precisely define the best daytime napping strategies.

scholarly journals Obesity as a cause of kidney disease - insights from Mendelian randomisation studies

2020 ◽  
Author(s):  
Xiaoguang Xu ◽  
James M. Eales ◽  
Xiao Jiang ◽  
Eleanor Sanderson ◽  
David Scannali ◽  
...  
Keyword(s):  
Waist Circumference ◽  
Kidney Disease ◽  
Renal Disease ◽  
Association Studies ◽  
Mendelian Randomisation ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Health Index ◽  
Genome Wide ◽  
Kidney Health

Objective: To examine if modifiable anthropometric indices of obesity exert putatively causal effects on different measures of kidney health and disease. Design: Conventional observational and Mendelian randomisation study. Setting: UK Biobank and international genome-wide association studies. Participants: Approximately 300,000 participants of white-British ancestry from UK Biobank and up to 480,000 participants of predominantly European ancestry from genome-wide association studies. Main outcome measures: Estimated glomerular filtration, blood urea nitrogen, kidney health index, chronic kidney disease, hypertensive renal disease, renal failure, acute renal failure, other disorders of kidney and ureters, IgA nephropathy and diabetic nephropathy. Results: The Mendelian randomisation analysis indicated that increasing values of genetically predicted body mass index (BMI) and waist circumference were causally linked to changes in renal function indices including reduced estimated glomerular filtration and increased blood urea nitrogen in UK Biobank individuals. These associations were replicated using data from CKDGen Consortium individuals. One standard deviation increase in genetically-predicted BMI and waist circumference decreased the relative odds of kidney health index by 14% and 18% (OR=0·86 ; 95%CI: 0·82-0·92 ; P=9·18×10-6 for BMI and OR=0·82 ; 95%CI: 0·75-0·90 ; P=2·12×10-5 for waist circumference, respectively). Approximately 13-16% of the causal effect of obesity indices on kidney health was mediated by blood pressure. Obesity increased the risk of both acute and chronic kidney disease of several aetiologies including hypertensive renal disease and diabetic nephropathy. Conclusions: These findings indicate that obesity is causally linked to indices of renal health and the risk of different kidney diseases. This evidence substantiates the value of weight loss as a strategy of preventing and/or counteracting a decline in kidney health as well as decreasing the risk of renal disease.

scholarly journals Systematic single-variant and gene-based association testing of 3,700 phenotypes in 281,850 UK Biobank exomes

2021 ◽  
Author(s):  
Konrad Karczewski ◽  
Matthew Solomonson ◽  
Katherine R Chao ◽  
Julia K Goodrich ◽  
Grace Tiao ◽  
...  
Keyword(s):  
Sequence Data ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Genetic Associations ◽  
Allelic Series ◽  
Association Analyses ◽  
Wide Range ◽  
The Uk ◽  
The Impact

Genome-wide association studies have successfully discovered thousands of common variants associated with human diseases and traits, but the landscape of rare variation in human disease has not been explored at scale. Exome sequencing studies of population biobanks provide an opportunity to systematically evaluate the impact of rare coding variation across a wide range of phenotypes to discover genes and allelic series relevant to human health and disease. Here, we present results from systematic association analyses of 3,700 phenotypes using single-variant and gene tests of 281,850 individuals in the UK Biobank with exome sequence data. We find that the discovery of genetic associations is tightly linked to frequency as well as correlated with metrics of deleteriousness and natural selection. We highlight biological findings elucidated by these data and release the dataset as a public resource alongside a browser framework for rapidly exploring rare variant association results.

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