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 Association of Physical Activity with Body Composition: A Mendelian Randomization Study

2021 ◽  
Author(s):  
Ferris Alaa Ramadan ◽  
Katherine Ellingson ◽  
Yann Klimentidis
Keyword(s):  
Physical Activity ◽  
Body Composition ◽  
Sedentary Behavior ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Sensitivity Analyses ◽  
Genome Wide Association Studies ◽  
Protective Effects ◽  
Dietary Interventions ◽  
The Uk

Background. Studies suggest that body composition can be improved through physical activity (PA) independently of dietary interventions. A separate line of evidence suggests that PA may reduce high-risk visceral adipose tissue (VAT), without clinically meaningful weight change. Genome-wide association studies have previously identified genetic markers associated with PA behaviors and may provide an opportunity to evaluate hypothesized causal relationships with body composition. Methods. We performed a Mendelian randomization (MR) study to test the incremental benefits of various PA exposures on body composition outcomes as assessed by anthropometric indices, lean body mass (LBM) (kg), body fat (%), and VAT (kg). Genetic instruments were identified for both self-reported and accelerometer-measured PA, including sedentary behavior. Outcomes included anthropometric and dual-energy X-ray absorptiometry measures of adiposity, extracted from the UK Biobank and the largest publicly available consortia. Multivariable MR (MVMR) included educational attainment as a covariate to address potential confounding. Sensitivity analyses were evaluated for weak instrument bias and pleiotropic effects.Results. We did not identify associations between genetically-predicted sedentary behavior (self-reported or accelerometer) and body composition outcomes in MVMR analyses. All analyses for self-reported moderate PA were null for body composition outcomes, including BMI, LBM and VAT. Genetically-predicted PA at higher intensities was protective against VAT in MR and MVMR analyses of both accelerometer-measured vigorous PA (MVMR β = -0.15, 95% Confidence Interval (CI): -0.24, -0.07, p<0.001) and self-reported participation in strenuous sports or other exercises (MVMR β = -0.27, 95%CI: -0.52, -0.01, p=0.034), and was robust across several sensitivity analyses. Conclusions. We did not identify evidence of a causal relationship between genetically-predicted PA and body composition, with the exception of a putatively protective effect of higher-intensity PA on VAT. Protective effects of PA against VAT may support prior evidence of biological pathways through which PA decreases risk of downstream cardiometabolic diseases.

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 Genetic liability to insomnia in relation to cardiovascular diseases: a Mendelian randomisation study

2021 ◽  
Author(s):  
Shuai Yuan ◽  
Amy M. Mason ◽  
Stephen Burgess ◽  
Susanna C. Larsson
Keyword(s):  
Cardiovascular Diseases ◽  
Association Studies ◽  
European Ancestry ◽  
Mendelian Randomisation ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Genetic Liability ◽  
Genome Wide ◽  
Increased Risk ◽  
The Uk

AbstractThe present study aimed to determine the associations between insomnia and cardiovascular diseases (CVDs) using Mendelian randomisation (MR) analysis. As instrumental variables, we used 208 independent single-nucleotide polymorphisms associated with insomnia at the genome-wide significance threshold in a meta-analysis of genome-wide association studies in the UK Biobank and 23andMe including a total of 397 959 self-reported insomnia cases and 933 057 non-cases. Summary-level data for nine CVDs were obtained from the UK Biobank including 367 586 individuals of European ancestry. After correction for multiple testing, genetic liability to insomnia was associated with higher odds of six CVDs, including peripheral arterial disease (odd ratio (OR) 1.22; 95% confidence interval (CI), 1.21, 1.33), heart failure (OR 1.21; 95% CI, 1.13, 1.30), coronary artery disease (OR 1.19; 95% CI, 1.14, 1.25), ischaemic stroke (OR 1.15; 95% CI, 1.06, 1.25), venous thromboembolism (OR 1.13; 95% CI, 1.07, 1.19) and atrial fibrillation (OR 1.10; 95% CI, 1.05, 1.15). There were suggestive associations for aortic valve stenosis (OR, 1.17; 95% CI, 1.04, 1.32) and haemorrhagic stroke (OR 1.14; 95% CI, 1.00, 1.29) but no association for abdominal aortic aneurysm (OR, 1.14, 95% CI, 0.98, 1.33). The patterns of associations remained with mild attenuation in multivariable MR analyses adjusting for genetically correlated phenotypes and potential mediators, including sleep duration, depression, body mass index, type 2 diabetes and smoking. The present MR study suggests potential causal associations of genetic liability to insomnia with increased risk of a broad range of CVDs.

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 Assessing the contribution of rare-to-common protein-coding variants to circulating metabolic biomarker levels via 412,394 UK Biobank exome sequences

2021 ◽  
Author(s):  
Abhishek Nag ◽  
Lawrence Middleton ◽  
Ryan S Dhindsa ◽  
Dimitrios Vitsios ◽  
Eleanor M Wigmore ◽  
...  
Keyword(s):  
Gene Networks ◽  
Rare Variants ◽  
Association Studies ◽  
Low Frequency ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Protein Coding ◽  
The Uk ◽  
Metabolic Biomarkers ◽  
Coding Variants

Genome-wide association studies have established the contribution of common and low frequency variants to metabolic biomarkers in the UK Biobank (UKB); however, the role of rare variants remains to be assessed systematically. We evaluated rare coding variants for 198 metabolic biomarkers, including metabolites assayed by Nightingale Health, using exome sequencing in participants from four genetically diverse ancestries in the UKB (N=412,394). Gene-level collapsing analysis, that evaluated a range of genetic architectures, identified a total of 1,303 significant relationships between genes and metabolic biomarkers (p<1x10-8), encompassing 207 distinct genes. These include associations between rare non-synonymous variants in GIGYF1 and glucose and lipid biomarkers, SYT7 and creatinine, and others, which may provide insights into novel disease biology. Comparing to a previous microarray-based genotyping study in the same cohort, we observed that 40% of gene-biomarker relationships identified in the collapsing analysis were novel. Finally, we applied Gene-SCOUT, a novel tool that utilises the gene-biomarker association statistics from the collapsing analysis to identify genes having similar biomarker fingerprints and thus expand our understanding of gene networks.

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 Evidence for causal effects of lifetime smoking on risk for depression and schizophrenia: a Mendelian randomisation study

2019 ◽  
Vol 50 (14) ◽  
pp. 2435-2443 ◽  
Author(s):  
Robyn E. Wootton ◽  
Rebecca C. Richmond ◽  
Bobby G. Stuijfzand ◽  
Rebecca B. Lawn ◽  
Hannah M. Sallis ◽  
...  
Keyword(s):  
Causal Effect ◽  
Association Studies ◽  
Smoking Initiation ◽  
Smoking Behaviour ◽  
Positive Control ◽  
Mendelian Randomisation ◽  
Genome Wide Association Studies ◽  
Weak Evidence ◽  
Smoking Duration ◽  
The Uk

AbstractBackgroundSmoking prevalence is higher amongst individuals with schizophrenia and depression compared with the general population. Mendelian randomisation (MR) can examine whether this association is causal using genetic variants identified in genome-wide association studies (GWAS).MethodsWe conducted two-sample MR to explore the bi-directional effects of smoking on schizophrenia and depression. For smoking behaviour, we used (1) smoking initiation GWAS from the GSCAN consortium and (2) we conducted our own GWAS of lifetime smoking behaviour (which captures smoking duration, heaviness and cessation) in a sample of 462690 individuals from the UK Biobank. We validated this instrument using positive control outcomes (e.g. lung cancer). For schizophrenia and depression we used GWAS from the PGC consortium.ResultsThere was strong evidence to suggest smoking is a risk factor for both schizophrenia (odds ratio (OR) 2.27, 95% confidence interval (CI) 1.67–3.08, p < 0.001) and depression (OR 1.99, 95% CI 1.71–2.32, p < 0.001). Results were consistent across both lifetime smoking and smoking initiation. We found some evidence that genetic liability to depression increases smoking (β = 0.091, 95% CI 0.027–0.155, p = 0.005) but evidence was mixed for schizophrenia (β = 0.022, 95% CI 0.005–0.038, p = 0.009) with very weak evidence for an effect on smoking initiation.ConclusionsThese findings suggest that the association between smoking, schizophrenia and depression is due, at least in part, to a causal effect of smoking, providing further evidence for the detrimental consequences of smoking on mental health.

LPA and APOE are associated with statin selection in the UK Biobank

2020 ◽  
Author(s):  
Adam Lavertu ◽  
Gregory McInnes ◽  
Yosuke Tanigawa ◽  
Russ B Altman ◽  
Manuel A. Rivas
Keyword(s):  
Statin Therapy ◽  
High Intensity ◽  
Drug Response ◽  
Association Studies ◽  
Low Density Lipoprotein ◽  
Density Lipoprotein ◽  
Treatment Decisions ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
The Uk

AbstractGenetics plays a key role in drug response, affecting efficacy and toxicity. Pharmacogenomics aims to understand how genetic variation influences drug response and develop clinical guidelines to aid clinicians in personalized treatment decisions informed by genetics. Although pharmacogenomics has not been broadly adopted into clinical practice, genetics influences treatment decisions regardless. Physicians adjust patient care based on observed response to medication, which may occur as a result of genetic variants harbored by the patient. Here we seek to understand the genetics of drug selection in statin therapy, a class of drugs widely used for high cholesterol treatment. Genetics are known to play an important role in statin efficacy and toxicity, leading to significant changes in patient outcome. We performed genome-wide association studies (GWAS) on statin selection among 59,198 participants in the UK Biobank and found that variants known to influence statin efficacy are significantly associated with statin selection. Specifically, we find that carriers of variants in APOE and LPA that are known to decrease efficacy of treatment are more likely to be on atorvastatin, a stronger statin. Additionally, carriers of the APOE and LPA variants are more likely to be on a higher intensity dose (a dose that reduces low-density lipoprotein cholesterol by greater than 40%) of atorvastatin than non-carriers (APOE: p(high intensity) = 0.16, OR = 1.7, P = 1.64 × 10−4, LPA: p(high intensity) = 0.17, OR = 1.4, P = 1.14 × 10−2). These findings represent the largest genetic association study of statin selection and statin dose association to date and provide evidence for the role of LPA and APOE in statin response, furthering the possibility of personalized statin therapy.

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 Population stratification in GWAS meta-analysis should be standardized to the best available reference datasets

2020 ◽  
Author(s):  
Aliya Sarmanova ◽  
Tim Morris ◽  
Daniel John Lawson
Keyword(s):  
Population Stratification ◽  
Association Studies ◽  
Meta Analysis ◽  
Principal Component ◽  
Underlying Structure ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
External Reference ◽  
Major Disadvantage ◽  
The Uk

AbstractPopulation stratification has recently been demonstrated to bias genetic studies even in relatively homogeneous populations such as within the British Isles. A key component to correcting for stratification in genome-wide association studies (GWAS) is accurately identifying and controlling for the underlying structure present in the sample. Meta-analysis across cohorts is increasingly important for achieving very large sample sizes, but comes with the major disadvantage that each individual cohort corrects for different population stratification. Here we demonstrate that correcting for structure against an external reference adds significant value to meta-analysis. We treat the UK Biobank as a collection of smaller studies, each of which is geographically localised. We provide software to standardize an external dataset against a reference, provide the UK Biobank principal component loadings for this purpose, and demonstrate the value of this with an analysis of the geographically sampled ALSPAC cohort.

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