scholarly journals Polygenic risk for schizophrenia and season of birth within the UK Biobank cohort

2018 ◽  
Vol 49 (15) ◽  
pp. 2499-2504 ◽  
Author(s):  
Valentina Escott-Price ◽  
Daniel J. Smith ◽  
Kimberley Kendall ◽  
Joey Ward ◽  
George Kirov ◽  
...  
Keyword(s):  
Environmental Exposure ◽  
Copy Number Variants ◽  
Season Of Birth ◽  
Uk Biobank ◽  
Month Of Birth ◽  
Risk Alleles ◽  
Gene Environment ◽  
Increased Risk ◽  
The Uk ◽  
Pathogenic Process

AbstractBackgroundThere is strong evidence that people born in winter and in spring have a small increased risk of schizophrenia. As this ‘season of birth’ effect underpins some of the most influential hypotheses concerning potentially modifiable risk exposures, it is important to exclude other possible explanations for the phenomenon.MethodsHere we sought to determine whether the season of birth effect reflects gene-environment confounding rather than a pathogenic process indexing environmental exposure. We directly measured, in 136 538 participants from the UK Biobank (UKBB), the burdens of common schizophrenia risk alleles and of copy number variants known to increase the risk for the disorder, and tested whether these were correlated with a season of birth.ResultsNeither genetic measure was associated with season or month of birth within the UKBB sample.ConclusionsAs our study was highly powered to detect small effects, we conclude that the season of birth effect in schizophrenia reflects a true pathogenic effect of environmental exposure.

scholarly journals Effects of genomic copy number variants penetrant for schizophrenia on cortical thickness and surface area in healthy individuals: analysis of the UK Biobank

2020 ◽  
pp. 1-8
Author(s):  
Xavier Caseras ◽  
George Kirov ◽  
Kimberley M. Kendall ◽  
Elliott Rees ◽  
Sophie E. Legge ◽  
...  
Keyword(s):  
Surface Area ◽  
Cortical Thickness ◽  
Copy Number ◽  
Copy Number Variants ◽  
Brain Anatomy ◽  
Carrier Status ◽  
Uk Biobank ◽  
Risk Alleles ◽  
The Uk ◽  
The Impact

Background Schizophrenia is a highly heritable disorder with undetermined neurobiological causes. Understanding the impact on brain anatomy of carrying genetic risk for the disorder will contribute to uncovering its neurobiological underpinnings. Aims To examine the effect of rare copy number variants (CNVs) associated with schizophrenia on brain cortical anatomy in a sample of unaffected participants from the UK Biobank. Method We used regression analyses to compare cortical thickness and surface area (total and across gyri) between 120 unaffected carriers of rare CNVs associated with schizophrenia and 16 670 participants without any pathogenic CNV. A measure of cortical thickness and surface area covariance across gyri was also compared between groups. Results Carrier status was associated with reduced surface area (β = −0.020 mm2, P < 0.001) and less robustly with increased cortical thickness (β = 0.015 mm, P = 0.035), and with increased covariance in thickness (carriers z = 0.31 v. non-carriers z = 0.22, P < 0.0005). Associations were mainly present in frontal and parietal areas and driven by a limited number of rare risk alleles included in our analyses (mainly 15q11.2 deletion for surface area and 16p13.11 duplication for thickness covariance). Conclusions Results for surface area conformed with previous clinical findings, supporting surface area reductions as an indicator of genetic liability for schizophrenia. Results for cortical thickness, though, argued against its validity as a potential risk marker. Increased structural thickness covariance across gyri also appears related to risk for schizophrenia. The heterogeneity found across the effects of rare risk alleles suggests potential different neurobiological gateways into schizophrenia's phenotype.

scholarly journals Medical consequences of pathogenic CNVs in adults: Analysis of the UK Biobank

2018 ◽  
Author(s):  
Karen Crawford ◽  
Matthew Bracher-Smith ◽  
Kimberley M Kendall ◽  
Elliott Rees ◽  
Antonio F Pardiñas ◽  
...  
Keyword(s):  
Statistical Significance ◽  
Copy Number Variants ◽  
Later Life ◽  
Uk Biobank ◽  
Bonferroni Correction ◽  
Medical Outcomes ◽  
Neurodevelopmental Outcomes ◽  
Minimal Impact ◽  
Increased Risk ◽  
The Uk

AbstractBackgroundGenomic copy number variants (CNVs) increase risk for early-onset neurodevelopmental disorders but their impact on medical outcomes in later life is poorly understood. The UK Biobank, with half a million well-phenotyped adults, presents an opportunity to study the medical consequences of CNV in middle and old age.MethodsWe called 54 CNVs associated with clinical phenotypes or genomic disorders, including their reciprocal deletions or duplications, in all Biobank participants. We used logistic regression analysis to test CNVs for associations with 58 common medical phenotypes.FindingsCNV carriers had an increased risk of developing 37 of the 58 phenotypes at nominal levels of statistical significance, with 19 associations surviving Bonferroni correction (p<8·6×10−4). Tests of each of the 54 CNVs for association with each of the 58 phenotypes identified 18 associations that survived Bonferroni correction (p<1·6×10−5) and a further 57 that were associated at a false discovery rate (FDR) threshold of 0·1. Thirteen CNVs had three or more significant associations at FDR=0·1, with the largest number of phenotypes (N=15) found for deletions at 16p11·2. The most common CNVs (frequency 0·5-0·7%) have no or minimal impact on medical outcomes in adults.InterpretationSome of the 54 tested CNVs have profound effects on physical health, even in people who have largely escaped early neurodevelopmental outcomes. Our work provides clinicians with a morbidity map of potential outcomes among carriers of these CNVs.FundingMRC UK, Wellcome Trust UK

scholarly journals Estimating the effective sample size in association studies of quantitative traits

2021 ◽  
Author(s):  
Andrey Ziyatdinov ◽  
Jihye Kim ◽  
Dmitry Prokopenko ◽  
Florian Privé ◽  
Fabien Laporte ◽  
...  
Keyword(s):  
Statistical Power ◽  
Quantitative Traits ◽  
Mixed Model ◽  
Association Studies ◽  
Effective Sample Size ◽  
Environment Interaction ◽  
Uk Biobank ◽  
Gene Environment Interaction ◽  
Gene Environment ◽  
The Uk

Abstract The effective sample size (ESS) is a metric used to summarize in a single term the amount of correlation in a sample. It is of particular interest when predicting the statistical power of genome-wide association studies (GWAS) based on linear mixed models. Here, we introduce an analytical form of the ESS for mixed-model GWAS of quantitative traits and relate it to empirical estimators recently proposed. Using our framework, we derived approximations of the ESS for analyses of related and unrelated samples and for both marginal genetic and gene-environment interaction tests. We conducted simulations to validate our approximations and to provide a quantitative perspective on the statistical power of various scenarios, including power loss due to family relatedness and power gains due to conditioning on the polygenic signal. Our analyses also demonstrate that the power of gene-environment interaction GWAS in related individuals strongly depends on the family structure and exposure distribution. Finally, we performed a series of mixed-model GWAS on data from the UK Biobank and confirmed the simulation results. We notably found that the expected power drop due to family relatedness in the UK Biobank is negligible.

scholarly journals Socioeconomic Inequalities and Ethnicity Are Associated with a Positive COVID-19 Test among Cancer Patients in the UK Biobank Cohort

Cancers ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 1514
Author(s):  
Shing Fung Lee ◽  
Maja Nikšić ◽  
Bernard Rachet ◽  
Maria-Jose Sanchez ◽  
Miguel Angel Luque-Fernandez
Keyword(s):  
Cancer Patients ◽  
Socioeconomic Inequalities ◽  
Uk Biobank ◽  
Incident Cancer ◽  
Increased Risk ◽  
Exposure Variable ◽  
Independent Risk Factors ◽  
The Uk ◽  
Deprived Areas

We explored the role of socioeconomic inequalities in COVID-19 incidence among cancer patients during the first wave of the pandemic. We conducted a case-control study within the UK Biobank cohort linked to the COVID-19 tests results available from 16 March 2020 until 23 August 2020. The main exposure variable was socioeconomic status, assessed using the Townsend Deprivation Index. Among 18,917 participants with an incident malignancy in the UK Biobank cohort, 89 tested positive for COVID-19. The overall COVID-19 incidence was 4.7 cases per 1000 incident cancer patients (95%CI 3.8–5.8). Compared with the least deprived cancer patients, those living in the most deprived areas had an almost three times higher risk of testing positive (RR 2.6, 95%CI 1.1–5.8). Other independent risk factors were ethnic minority background, obesity, unemployment, smoking, and being diagnosed with a haematological cancer for less than five years. A consistent pattern of socioeconomic inequalities in COVID-19 among incident cancer patients in the UK highlights the need to prioritise the cancer patients living in the most deprived areas in vaccination planning. This socio-demographic profiling of vulnerable cancer patients at increased risk of infection can inform prevention strategies and policy improvements for the coming pandemic waves.

scholarly journals Is Environmental and Occupational Particulate Air Pollution Exposure Related to Type-2 Diabetes and Dementia? A Cross-Sectional Analysis of the UK Biobank

2020 ◽  
Vol 17 (24) ◽  
pp. 9581
Author(s):  
Eirini Dimakakou ◽  
Helinor J. Johnston ◽  
George Streftaris ◽  
John W. Cherrie
Keyword(s):  
Air Pollution ◽  
Occupational Exposure ◽  
Environmental Exposure ◽  
Uk Biobank ◽  
Job Exposure Matrix ◽  
Cross Sectional ◽  
Particulate Air Pollution ◽  
The Uk ◽  
Sectional Analysis

Human exposure to particulate air pollution (e.g., PM2.5) can lead to adverse health effects, with compelling evidence that it can increase morbidity and mortality from respiratory and cardiovascular disease. More recently, there has also been evidence that long-term environmental exposure to particulate air pollution is associated with type-2 diabetes mellitus (T2DM) and dementia. There are many occupations that may expose workers to airborne particles and that some exposures in the workplace are very similar to environmental particulate pollution. We conducted a cross-sectional analysis of the UK Biobank cohort to verify the association between environmental particulate air pollution (PM2.5) exposure and T2DM and dementia, and to investigate if occupational exposure to particulates that are similar to those found in environmental air pollution could increase the odds of developing these diseases. The UK Biobank dataset comprises of over 500,000 participants from all over the UK. Environmental exposure variables were used from the UK Biobank. To estimate occupational exposure both the UK Biobank’s data and information from a job exposure matrix, specifically developed for UK Biobank (Airborne Chemical Exposure–Job Exposure Matrix (ACE JEM)), were used. The outcome measures were participants with T2DM and dementia. In appropriately adjusted models, environmental exposure to PM2.5 was associated with an odds ratio (OR) of 1.02 (95% CI 1.00 to 1.03) per unit exposure for developing T2DM, while PM2.5 was associated with an odds ratio of 1.06 (95% CI 0.96 to 1.16) per unit exposure for developing dementia. These environmental results align with existing findings in the published literature. Five occupational exposures (dust, fumes, diesel, mineral, and biological dust in the most recent job estimated with the ACE JEM) were investigated and the risks for most exposures for T2DM and for all the exposures for dementia were not significantly increased in the adjusted models. This was confirmed in a subgroup of participants where a full occupational history was available allowed an estimate of workplace exposures. However, when not adjusting for gender, some of the associations become significant, which suggests that there might be a bias between the occupational assessments for men and women. The results of the present study do not provide clear evidence of an association between occupational exposure to particulate matter and T2DM or dementia.

scholarly journals Associations of cigarette smoking with gray and white matter in the UK Biobank

2019 ◽  
Author(s):  
Joshua Gray ◽  
Matthew Thompson ◽  
Chelsie Benca-Bachman ◽  
Max Michael Owens ◽  
Mikela Murphy ◽  
...  
Keyword(s):  
White Matter ◽  
Cigarette Smoking ◽  
Gray Matter ◽  
Brain Structure ◽  
Mean Diffusivity ◽  
Medial Lemniscus ◽  
Uk Biobank ◽  
Matter Volume ◽  
Increased Risk ◽  
The Uk

Chronic cigarette smoking is associated with increased risk for myriad health consequences including cognitive decline and dementia, but research on the link between smoking and brain structure is nascent. We assessed the relationship of cigarette smoking (ever smoked, cigarettes per day, and duration) with gray and white matter using the UK Biobank cohort (gray matter N = 19,615; white matter N = 17,760), adjusting for numerous demographic and health confounders. Ever smoked and duration were associated with smaller total gray matter volume. Ever smoked was associated with reduced volume of the right VIIIa cerebellum, as well as elevated white matter hyperintensity volumes. Smoking duration was associated with reduced total white matter volume. With regard to specific tracts, ever smoked was associated with reduced fractional anisotropy in the left cingulate gyrus part of the cingulum, left posterior thalamic radiation, and bilateral superior thalamic radiation and increased mean diffusivity in the middle cerebellar peduncle, right medial lemniscus, bilateral posterior thalamic radiation, and bilateral superior thalamic radiation. Overall, we found significant associations of cigarette exposure with global measures of gray and white matter. Furthermore, we found select associations of ever smoked, but not cigarettes per day or duration, with specific gray and white matter regions. These findings inform our understanding of the connections between smoking and variation in brain structure and clarify potential mechanisms of risk for common neurological sequelae.

scholarly journals Diabetes, glycated haemoglobin and the risk of myocardial infarction in women and men: a prospective cohort study of the UK Biobank

2020 ◽  
Author(s):  
Marit de Jong ◽  
Mark Woodward ◽  
Sanne A.E Peters
Keyword(s):  
Myocardial Infarction ◽  
Sex Differences ◽  
Glycated Haemoglobin ◽  
Incidence Rates ◽  
Undiagnosed Diabetes ◽  
Uk Biobank ◽  
Diabetes Status ◽  
Increased Risk ◽  
The Uk ◽  
Diagnosed Diabetes

<b>Objective:</b> Diabetes has shown to be a stronger risk factor for myocardial infarction (MI) in women than men. Whether sex differences exist across the glycaemic spectrum is unknown. We investigated sex differences in the associations of diabetes status and glycated haemoglobin (HbA1c) with the risk of MI. <br> <b>Research Design and Methods:</b> Data were used from 471,399 (56% women) individuals without cardiovascular disease (CVD) included in the UK Biobank. Sex-specific incidence rates were calculated by diabetes status and across levels of HbA1c, using Poisson regression. Cox proportional hazards analyses estimated sex-specific hazard ratios (HR) and women-to-men ratios by diabetes status and HbA1c for MI during a mean follow-up of 9 years. <br> <b>Results:</b> Women had lower incidence rates of MI than men, regardless of diabetes status or HbA1c level. Compared with individuals without diabetes, prediabetes, undiagnosed diabetes, and previously diagnosed diabetes were associated with increased risk of MI in both sexes. Previously diagnosed diabetes was more strongly associated with MI in women (HR 2∙33 [95%CI 1∙96;2∙78]) than men (1∙81 [1∙63;2∙02]), with a women-to-men ratio of HRs of 1∙29 (1∙05;1∙58). Each 1% higher HbA1c, independent of diabetes status, was associated with an 18% greater risk of MI in both women and men.<br> <b>Conclusions:</b> Although the incidence of MI was higher in men than women, the presence of diabetes is associated with a greater excess relative risk of MI in women. However, each 1% higher HbA1c was associated with an 18% greater risk of MI in both women and men.<br> <br>

scholarly journals Diabetes, glycated haemoglobin and the risk of myocardial infarction in women and men: a prospective cohort study of the UK Biobank

2020 ◽  
Author(s):  
Marit de Jong ◽  
Mark Woodward ◽  
Sanne A.E Peters
Keyword(s):  
Myocardial Infarction ◽  
Sex Differences ◽  
Glycated Haemoglobin ◽  
Incidence Rates ◽  
Undiagnosed Diabetes ◽  
Uk Biobank ◽  
Diabetes Status ◽  
Increased Risk ◽  
The Uk ◽  
Diagnosed Diabetes

<b>Objective:</b> Diabetes has shown to be a stronger risk factor for myocardial infarction (MI) in women than men. Whether sex differences exist across the glycaemic spectrum is unknown. We investigated sex differences in the associations of diabetes status and glycated haemoglobin (HbA1c) with the risk of MI. <br> <b>Research Design and Methods:</b> Data were used from 471,399 (56% women) individuals without cardiovascular disease (CVD) included in the UK Biobank. Sex-specific incidence rates were calculated by diabetes status and across levels of HbA1c, using Poisson regression. Cox proportional hazards analyses estimated sex-specific hazard ratios (HR) and women-to-men ratios by diabetes status and HbA1c for MI during a mean follow-up of 9 years. <br> <b>Results:</b> Women had lower incidence rates of MI than men, regardless of diabetes status or HbA1c level. Compared with individuals without diabetes, prediabetes, undiagnosed diabetes, and previously diagnosed diabetes were associated with increased risk of MI in both sexes. Previously diagnosed diabetes was more strongly associated with MI in women (HR 2∙33 [95%CI 1∙96;2∙78]) than men (1∙81 [1∙63;2∙02]), with a women-to-men ratio of HRs of 1∙29 (1∙05;1∙58). Each 1% higher HbA1c, independent of diabetes status, was associated with an 18% greater risk of MI in both women and men.<br> <b>Conclusions:</b> Although the incidence of MI was higher in men than women, the presence of diabetes is associated with a greater excess relative risk of MI in women. However, each 1% higher HbA1c was associated with an 18% greater risk of MI in both women and men.<br> <br>

Associations of ophthalmic and systemic conditions with incident dementia in the UK Biobank

2021 ◽  
pp. bjophthalmol-2021-319508
Author(s):  
Xianwen Shang ◽  
Zhuoting Zhu ◽  
Yu Huang ◽  
Xueli Zhang ◽  
Wei Wang ◽  
...  
Keyword(s):  
Heart Disease ◽  
Age Related Macular Degeneration ◽  
Hospital Inpatient ◽  
Uk Biobank ◽  
Age Related ◽  
Incident Dementia ◽  
Increased Risk ◽  
The Uk ◽  
Systemic Condition

AimsTo examine independent and interactive associations of ophthalmic and systemic conditions with incident dementia.MethodsOur analysis included 12 364 adults aged 55–73 years from the UK Biobank cohort. Participants were assessed between 2006 and 2010 at baseline and were followed up until the early of 2021. Incident dementia was ascertained using hospital inpatient, death records and self-reported data.ResultsOver 1 263 513 person-years of follow-up, 2304 cases of incident dementia were documented. The multivariable-adjusted HRs (95% CI) for dementia associated with age-related macular degeneration (AMD), cataract, diabetes-related eye disease (DRED) and glaucoma at baseline were 1.26 (1.05 to 1.52), 1.11 (1.00 to 1.24), 1.61 (1.30 to 2.00) and (1.07 (0.92 to 1.25), respectively. Diabetes, heart disease, stroke and depression at baseline were all associated with an increased risk of dementia. Of the combination of AMD and a systemic condition, AMD-diabetes was associated with the highest risk for incident dementia (HR (95% CI): 2.73 (1.79 to 4.17)). Individuals with cataract and a systemic condition were 1.19–2.29 times more likely to develop dementia compared with those without cataract and systemic conditions. The corresponding number for DRED and a systemic condition was 1.50–3.24. Diabetes, hypertension, heart disease, depression and stroke newly identified during follow-up mediated the association between cataract and incident dementia as well as the association between DRED and incident dementia.ConclusionsAMD, cataract and DRED but not glaucoma are associated with an increased risk of dementia. Individuals with both ophthalmic and systemic conditions are at higher risk of dementia compared with those with an ophthalmic or systemic condition only.

Abstract P147: Genome Wide Assessment of Shared Genetic Architecture Between Rheumatoid Arthritis and Cardiovascular Diseases Using the UK Biobank Data

Circulation ◽  
2020 ◽  
Vol 141 (Suppl_1) ◽  
Author(s):  
Yanjun Guo ◽  
Wonil Chung ◽  
Zhilei Shan ◽  
Liming Liang
Keyword(s):  
Cardiovascular Diseases ◽  
Genetic Correlation ◽  
Multiple Testing ◽  
Mendelian Randomization ◽  
Meta Analysis ◽  
Uk Biobank ◽  
Increased Risk ◽  
The Uk ◽  
Cardiovascular Traits ◽  
Shared Genetic

Background: Patients with RA have a 2-10 folds increased risk of cardiovascular diseases (CVD) and CVD accounts for almost 50% of the excess mortality in patients with RA when compared with general population, but the mechanisms underlying such associations are largely unknown. Methods: We examined the genetic correlation, causality, and shared genetic variants between RA (Ncase=6,756, Ncontrol=452,476) and CVD (Ncase=44,246, Ncontrol=414,986) using LD Score regression (LDSC), generalized summary-data-based Mendelian Randomization (GSMR), and cross-trait meta-analysis in the UK Biobank Data. Results: In the present study, RA was significantly genetically correlated with MI, angina, CHD, and CVD after correcting for multiple testing (Rg ranges from 0.40 to 0.43, P<0.05/5). Interestingly, when stratified by frequent usage of aspirin and paracetamol, we observed increased genetic correlation between RA and CVD for participants without aspirin usage ( Rg increased to 0.54 [95%CI: 0.54, 0.78] for angina; P value=6.69х10 -6 ), and for participants with usage of paracetamol ( Rg increased to 0.75 [95%CI: 0.20, 1.29] for MI; P value=8.90х10 -3 ). Cross-trait meta-analysis identified 9 independent loci that were shared between RA and at least one of the genetically correlated CVD traits including PTPN22 at chr1p13.2 , BCL2L11 at chr2q13 , and CCR3 at chr3p21.31 ( P single trait <1х10 -3 and P meta <5х10 -8 ) highlighting potential shared etiology between them which include accelerating atherosclerosis and upregulating oxidative stress and vascular permeability. Finally, Mendelian randomization analyses observed inconsistent instrumental effects and were unable to conclude the causality and directionality between RA and CVD. Conclusion: Our results supported positive genetic correlation between RA and multiple cardiovascular traits, and frequent usage of aspirin and paracetamol may modify their associations, but instrumental analyses were unable to conclude the causality and directionality between them.

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