scholarly journals Association of genetically predicted testosterone with thromboembolism, heart failure, and myocardial infarction: mendelian randomisation study in UK Biobank

BMJ ◽  
2019 ◽  
pp. l476 ◽  
Author(s):  
Shan Luo ◽  
Shiu Lun Au Yeung ◽  
Jie V Zhao ◽  
Stephen Burgess ◽  
C Mary Schooling
Keyword(s):  
Myocardial Infarction ◽  
Heart Failure ◽  
Genetic Variants ◽  
Controlled Trial ◽  
European Ancestry ◽  
Gene Region ◽  
Mendelian Randomisation ◽  
Uk Biobank ◽  
1000 Genomes ◽  
The Uk

Abstract Objective To determine whether endogenous testosterone has a causal role in thromboembolism, heart failure, and myocardial infarction. Design Two sample mendelian randomisation study using genetic variants as instrumental variables, randomly allocated at conception, to infer causality as additional randomised evidence. Setting Reduction by Dutasteride of Prostate Cancer Events (REDUCE) randomised controlled trial, UK Biobank, and CARDIoGRAMplusC4D 1000 Genomes based genome wide association study. Participants 3225 men of European ancestry aged 50-75 in REDUCE; 392 038 white British men and women aged 40-69 from the UK Biobank; and 171 875 participants of about 77% European descent, from CARDIoGRAMplusC4D 1000 Genomes based study for validation. Main outcome measures Thromboembolism, heart failure, and myocardial infarction based on self reports, hospital episodes, and death. Results Of the UK Biobank participants, 13 691 had thromboembolism (6208 men, 7483 women), 1688 had heart failure (1186, 502), and 12 882 had myocardial infarction (10 136, 2746). In men, endogenous testosterone genetically predicted by variants in the JMJD1C gene region was positively associated with thromboembolism (odds ratio per unit increase in log transformed testosterone (nmol/L) 2.09, 95% confidence interval 1.27 to 3.46) and heart failure (7.81, 2.56 to 23.8), but not myocardial infarction (1.17, 0.78 to 1.75). Associations were less obvious in women. In the validation study, genetically predicted testosterone (based on JMJD1C gene region variants) was positively associated with myocardial infarction (1.37, 1.03 to 1.82). No excess heterogeneity was observed among genetic variants in their associations with the outcomes. However, testosterone genetically predicted by potentially pleiotropic variants in the SHBG gene region had no association with the outcomes. Conclusions Endogenous testosterone was positively associated with thromboembolism, heart failure, and myocardial infarction in men. Rates of these conditions are higher in men than women. Endogenous testosterone can be controlled with existing treatments and could be a modifiable risk factor for thromboembolism and heart failure.

P3823Body mass index or waist and hip circumference as predictors of outcome in the UK biobank

2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
P Pellicori ◽  
B Stanley ◽  
S Iliodromiti ◽  
C A Celis-Morales ◽  
D M Lyall ◽  
...  
Keyword(s):  
Risk Factors ◽  
Myocardial Infarction ◽  
Heart Failure ◽  
Body Fat ◽  
Uk Biobank ◽  
Anthropometric Indices ◽  
All Cause Mortality ◽  
History Of ◽  
Cv Disease ◽  
The Uk

Abstract Background Controversies exist about the relationship between body habitus and mortality, especially for patients with cardiovascular disease. Purpose We evaluated the relations between different anthropometric indices and mortality amongst participants with and without cardiovascular (CV) risk factors, or established CV disease (stroke, myocardial infarction and/or heart failure), enrolled in the UK Biobank. Methods The UK Biobank is a large prospective study which, between 2006 and 2010, enrolled 502,620 participants aged 38–73 years. Participants filled questionnaires and had a medical history recorded, physical measurements done and biological samples taken. The UK Biobank is routinely linked to national death registries and updated on a quarterly basis. Data on death were coded according to the International Classification of Diseases, 10th Revision (ICD-10). The primary end-point was all-cause mortality (ACM) across three subgroups of men and women: those with, or without, one or more CV risk factors (smoking, diabetes and/or hypertension), and those with CV disease (history of stroke, myocardial infarction and/or heart failure) at recruitment. Presence, or absence, of CV risk factors and diagnoses of CV disease were self-reported by participants at enrolment. Associations between anthropometric indices (body mass index (BMI), waist circumference (WC), waist to hip ratio (WHiR), and waist to height ratio (WHeR)) and the risk of all-cause mortality were analysed using Cox regression models. Results After excluding those with history of cancer at baseline (n=45,222), 453,046 participants were included (median age: 58 (interquartile range: 50 - 63) years; 53% women), of whom 150,732 had at least one CV risk factor, and 17,884 established CV disease. During a median follow-up of 5 years, 6,319 participants died. Baseline BMI had a U-shaped relationship with ACM, with higher nadir-values for those with CV risk factors or CV disease, for both sexes (figure). WC, WHiR and WHeR (measures of central distribution of body fat) had more linear associations with ACM, regardless of CV risk factors, CV disease and sex. Conclusions For adults with or without CV risk factors or established CV disease, measures of central distribution of body fat are more strongly and more linearly associated with ACM than BMI. WC, or WHiR, rather than BMI, appear to be more appropriate variables for risk stratification.

scholarly journals Genotype-by-environment interactions inferred from genetic effects on phenotypic variability in the UK Biobank

2019 ◽  
Author(s):  
Huanwei Wang ◽  
Futao Zhang ◽  
Jian Zeng ◽  
Yang Wu ◽  
Kathryn E. Kemper ◽  
...  
Keyword(s):  
Environmental Factors ◽  
Genetic Variants ◽  
Phenotypic Variability ◽  
Environmental Data ◽  
European Ancestry ◽  
Environment Interaction ◽  
Uk Biobank ◽  
Genotype By Environment ◽  
A Genome ◽  
The Uk

AbstractGenotype-by-environment interaction (GEI) is a fundamental component in understanding complex trait variation. However, it remains challenging to identify genetic variants with GEI effects in humans largely because of the small effect sizes and the difficulty of monitoring environmental fluctuations. Here, we demonstrate that GEI can be inferred from genetic variants associated with phenotypic variability in a large sample without the need of measuring environmental factors. We performed a genome-wide variance quantitative trait locus (vQTL) analysis of ~5.6 million variants on 348,501 unrelated individuals of European ancestry for 13 quantitative traits in the UK Biobank, and identified 75 significant vQTLs with P<2.0×10−9 for 9 traits, especially for those related to obesity. Direct GEI analysis with five environmental factors showed that the vQTLs were strongly enriched with GEI effects. Our results indicate pervasive GEI effects for obesity-related traits and demonstrate the detection of GEI without environmental data.

Plasma adiponectin and risk of asthma: observational analysis, genetic Mendelian randomisation and meta-analysis

Thorax ◽  
2021 ◽  
pp. thoraxjnl-2021-217675
Author(s):  
Maria Booth Nielsen ◽  
Børge G Nordestgaard ◽  
Marianne Benn ◽  
Yunus Çolak
Keyword(s):  
General Population ◽  
Population Study ◽  
Genetic Variants ◽  
Meta Analysis ◽  
High Plasma ◽  
Mendelian Randomisation ◽  
Uk Biobank ◽  
General Population Study ◽  
Plasma Adiponectin ◽  
The Uk

BackgroundAdiponectin, an adipocyte-secreted protein-hormone with inflammatory properties, has a potentially important role in the development and progression of asthma. Unravelling whether adiponectin is a causal risk factor for asthma is an important issue to clarify as adiponectin could be a potential novel drug target for the treatment of asthma.ObjectiveWe tested the hypothesis that plasma adiponectin is associated observationally and causally (using genetic variants as instrumental variables) with risk of asthma.MethodsIn the Copenhagen General Population Study, we did an observational analysis in 28 845 individuals (2278 asthma cases) with plasma adiponectin measurements, and a genetic one-sample Mendelian randomisation analysis in 94 868 individuals (7128 asthma cases) with 4 genetic variants. Furthermore, in the UK Biobank, we did a genetic two-sample Mendelian randomisation analysis in 462 933 individuals (53 598 asthma cases) with 12 genetic variants. Lastly, we meta-analysed the genetic findings.ResultsWhile a 1 unit log-transformed higher plasma adiponectin in the Copenhagen General Population Study was associated with an observational OR of 1.65 (95% CI 1.29 to 2.08) for asthma, the corresponding genetic causal OR was 1.03 (95% CI 0.75 to 1.42). The genetic causal OR for asthma in the UK Biobank was 1.00 (95% CI 0.99 to 1.00). Lastly, genetic meta-analysis confirmed lack of association between genetically high plasma adiponectin and causal OR for asthma.ConclusionObservationally, high plasma adiponectin is associated with increased risk of asthma; however, genetic evidence could not support a causal association between plasma adiponectin and asthma.

scholarly journals Large-Scale, Genome-Wide Gene-Diet Interaction Testing for HbA1c Using Derived Dietary Patterns in the UK Biobank

2020 ◽  
Vol 4 (Supplement_2) ◽  
pp. 1280-1280
Author(s):  
Kenneth Westerman ◽  
Ye Chen ◽  
Han Chen ◽  
Jose Florez ◽  
Joanne Cole ◽  
...  
Keyword(s):  
Principal Components ◽  
Dietary Patterns ◽  
Genetic Variants ◽  
Interaction Analysis ◽  
European Ancestry ◽  
Uk Biobank ◽  
Genome Wide ◽  
A Genome ◽  
Gene Level ◽  
The Uk

Abstract Objectives Gene-diet interaction analysis can inform the development of precision nutrition for diabetes by uncovering genetic variants whose effects on glycemic traits vary across dietary behaviors. However, due to noise in dietary datasets and the low statistical power inherent in interaction analysis, there is a lack of confident, well-replicated gene-diet interactions for glycemic traits. Emerging computationally-efficient software tools have made it feasible to conduct well-powered, genome-wide interaction analysis in hundreds of thousands of individuals. Here, our objective was to conduct a genome-wide gene-diet interaction analysis for glycated hemoglobin (HbA1c; a measure of hyperglycemia), leveraging the large sample size of the UK Biobank cohort and data-driven dietary patterns to discover genetic variants whose effect is modulated by diet. Methods Food frequency questionnaires were previously used to derive empirical dietary patterns using principal components analysis (FFQ-PCs) in the UK Biobank. FFQ-PCs were used in genome-wide interaction analysis for HbA1c levels in unrelated, non-diabetic individuals of European ancestry (N = 331,610), adjusting for age, sex, and 10 genetic principal components. P-values were calculated for both the interaction (P-int) and a joint test (significance of the variant-HbA1c association combining the main and interaction effects) and the MAGMA tool was used to calculate gene-level enrichment statistics. Results Preliminary results from the first two FFQ-PCs confirmed known genetic loci for HbA1c using the joint test, such as at G6PC2 and GCK. Though no interaction tests reached genome-wide significance, suggestive signals (P-int &lt; 1e-5) emerged at the variant level (including one near TPSD1, which codes for a tryptase and has been linked to red blood cell traits) and the gene level (such as for GTF3C2, which has previously been shown to interact with sleep in impacting lipid traits). Conclusions We have conducted the largest genome-wide study of gene-diet interactions for glycemic traits to-date and identified regions in the genome whose effect on HbA1c may be modulated by dietary intake, suggesting that this approach has the potential to reveal new insights into the genetics of glycemic traits and inform individualized dietary guidelines for diabetes prevention and management. Funding Sources NHLBI.

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 Polygenic modulation of lipoprotein(a)-associated cardiovascular risk

2020 ◽  
Author(s):  
Mark Trinder ◽  
Liam R. Brunham
Keyword(s):  
Myocardial Infarction ◽  
Cardiovascular Risk ◽  
Genetic Variants ◽  
Uk Biobank ◽  
Lower Quintile ◽  
Lipoprotein A ◽  
Common Genetic Variants ◽  
Artery Disease ◽  
The Uk ◽  
Genomic Risk

ABSTRACTAimsElevated levels of lipoprotein(a) are one of the strongest inherited risk factors for coronary artery disease (CAD). However, there is variability in cardiovascular risk among individuals with elevated lipoprotein(a). The sources of this variability are incompletely understood. We assessed the effects of a genomic risk score (GRS) for CAD on risk of myocardial infarction among individuals with elevated lipoprotein(a).MethodsWe calculated CAD GRSs for 408,896 individuals of British white ancestry from the UK Biobank using 6.27 million common genetic variants. Lipoprotein(a) levels were measured in 310,020 individuals. The prevalence and risk of myocardial infarction versus CAD GRS percentiles were compared for individuals with and without elevated lipoprotein(a) defined as ≥120 or 168 nmol/L (≈50 or 70 mg/dL, respectively).ResultsIndividuals with elevated lipoprotein(a) displayed significantly greater CAD GRSs than individuals without elevated lipoprotein(a), which was largely dependent on the influence of genetic variants within or near the LPA gene. Continuous levels of CAD GRS percentile were significantly associated with risk of myocardial infarction for individuals with elevated lipoprotein(a). Notably, the risk of myocardial infarction for males with elevated lipoprotein(a) levels, but a CAD GRS percentile in the lower quintile (<20th percentile), was less than the overall risk of myocardial infarction for males with non-elevated lipoprotein(a) levels (hazard ratio [95% CI]: 0.79 [0.64-0.97], p=0.02). Similar results were observed for females.ConclusionThese data suggest that CAD genomic scores influence cardiovascular risk among individuals with elevated lipoprotein(a) and may aid in identifying candidates for preventive therapies.

scholarly journals Interactions Between Sugar-Sweetened Beverage Consumption and Genetic Variants in the ChREBP Locus on Lipoprotein Concentrations in the UK Biobank: A Replication Study

2020 ◽  
Vol 4 (Supplement_2) ◽  
pp. 1255-1255
Author(s):  
Melanie Guirette ◽  
Danielle Haslam ◽  
Gina Peloso ◽  
Achilleas Pitsillides ◽  
Caren Smith ◽  
...  
Keyword(s):  
Genetic Variants ◽  
Meta Analysis ◽  
Density Lipoprotein ◽  
High Linkage Disequilibrium ◽  
European Ancestry ◽  
Uk Biobank ◽  
Study Objective ◽  
Sugar Sweetened Beverage ◽  
Sweetened Beverage ◽  
The Uk

Abstract Objectives A meta-analysis of 11 CHARGE cohorts (N = 63,599) suggested that genetic variants within or near the CHREBP locus may modify the associations between sugar sweetened beverage (SSB) consumption and high-density lipoprotein cholesterol (HDL-C) and triglyceride (TG) concentrations. The study objective was to replicate these findings in a large independent cohort. Methods Blood lipids and 24-hour recalls were available for 57,794 adults of European ancestry in the UK Biobank (2006-‘10). SSBs included “squash” and “fizzy” drinks derived from a single 24-hr recall. A total of 875 SNPs within or near the CHREBP locus were identified and included in this analysis. Associations between these SNPs and HDL-C and TG concentrations were quantified among participants who did not report SSB consumption (non-consumers, n = 45,866), reported ≥0.5 servings/day of SSB (consumers, n = 11,928), and a subset of consumers who reported ≥2 servings/day of SSB (high consumers, n = 3742). Interaction between SSB and selected SNPs on HDL-C and TG concentrations was evaluated by examining the difference in beta coefficients between strata. Results were considered statistically significant at a Bonferroni-corrected pinteract &lt; 0.0001 (0.05/499 effective tests). Results A significant interaction between SSB consumption and TBL2-rs71556729 on HDL-C concentration previously observed in the meta-analysis was replicated in UK Biobank. However, we observed a stronger interaction for a SNP in high linkage disequilibrium (R2 = 0.93) FZD9-rs34821369 (MAF = 0.03, pinteract = 8.2E-05) with TBL2-rs71556729 (MAF = 0.03, pinteract = 0.0004). Among only SSB consumers, each additional minor G allele at FZD9-rs34821369 was associated with mean HDL-C concentrations 1.63 mg/dL (SE = 0.53, P = 0.002) higher than those with the major T allele. Conclusions Our results suggest that adults with the minor allele at FZD9-rs34821369 may be protected against SSB-induced low HDL-C concentrations. These results are consistent the findings from a prior meta-analysis of 11 cohorts. Funding Sources NIH, AHA, USDA-ARS. This research has been conducted using the UK Biobank Resource (Application Number 35,835).

scholarly journals Genotype-by-environment interactions inferred from genetic effects on phenotypic variability in the UK Biobank

2019 ◽  
Vol 5 (8) ◽  
pp. eaaw3538 ◽  
Author(s):  
Huanwei Wang ◽  
Futao Zhang ◽  
Jian Zeng ◽  
Yang Wu ◽  
Kathryn E. Kemper ◽  
...  
Keyword(s):  
Environmental Factors ◽  
Genetic Variants ◽  
Phenotypic Variability ◽  
Environmental Data ◽  
European Ancestry ◽  
Environment Interaction ◽  
Uk Biobank ◽  
Genotype By Environment ◽  
A Genome ◽  
The Uk

Genotype-by-environment interaction (GEI) is a fundamental component in understanding complex trait variation. However, it remains challenging to identify genetic variants with GEI effects in humans largely because of the small effect sizes and the difficulty of monitoring environmental fluctuations. Here, we demonstrate that GEI can be inferred from genetic variants associated with phenotypic variability in a large sample without the need of measuring environmental factors. We performed a genome-wide variance quantitative trait locus (vQTL) analysis of ~5.6 million variants on 348,501 unrelated individuals of European ancestry for 13 quantitative traits in the UK Biobank and identified 75 significant vQTLs with P < 2.0 × 10−9 for 9 traits, especially for those related to obesity. Direct GEI analysis with five environmental factors showed that the vQTLs were strongly enriched with GEI effects. Our results indicate pervasive GEI effects for obesity-related traits and demonstrate the detection of GEI without environmental data.

scholarly journals The role of linoleic acid in asthma and inflammatory markers: a Mendelian randomization study

2019 ◽  
Vol 110 (3) ◽  
pp. 685-690 ◽  
Author(s):  
Jie V Zhao ◽  
C Mary Schooling
Keyword(s):  
Linoleic Acid ◽  
Blood Cell ◽  
White Blood Cell ◽  
Genetic Variants ◽  
Mendelian Randomization ◽  
European Ancestry ◽  
Uk Biobank ◽  
Reverse Causality ◽  
The Uk

ABSTRACT Background Asthma is a common respiratory disease, possibly caused by autoimmunity. Linoleic acid (LA), the main n–6 (ω-6) PUFA from widely used vegetable oils, is thought to suppress immune responses that might have benefits for asthma. However, this question has not been examined in randomized controlled trials. Objectives To obtain unconfounded estimates, we assessed how genetically predicted LA affected asthma using 2-sample Mendelian randomization. We also examined its role in white blood cell traits (eosinophil, neutrophil, and low monocyte counts) identified as potential causal factors in asthma. Methods We used 18 uncorrelated, genome-wide significant genetic variants to predict LA, which we applied to a large genetic case (n = 19,954)–control (n = 107,715) study of asthma, to the UK Biobank (408,961 people of European ancestry with 26,332 asthma cases), and for white blood cell traits to the UK Biobank. We also repeated the analysis on asthma using 29 replicated, functionally relevant genetic variants. In addition, we examined the role of asthma in LA to assess reverse causality. Results Genetically predicted LA was associated with lower risk of asthma (OR: 0.89 per SD increase in LA; 95% CI: 0.85, 0.93), with no association of asthma with LA. Genetically predicted LA was associated with lower eosinophil count (−0.03; 95% CI: −0.061, −0.004) and lower neutrophil count (−0.04; 95% CI: −0.057, −0.023). These estimates were robust to different selections of genetic variants and sensitivity analyses. Conclusions LA might protect against asthma possibly via white blood cell traits, with relevance to the identification of effective new interventions for asthma.

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