scholarly journals Biobank scale pharmacogenomics informs the genetic underpinnings of simvastatin use

2020 ◽  
Author(s):  
Frank R Wendt ◽  
Dora Koller ◽  
Gita A Pathak ◽  
Daniel Jacoby ◽  
Edward J Miller ◽  
...  
Keyword(s):  
Linear Models ◽  
Association Studies ◽  
Absolute Risk ◽  
African Ancestry ◽  
Medication Use ◽  
Density Lipoprotein ◽  
Interactive Effects ◽  
European Ancestry ◽  
Uk Biobank ◽  
The Uk

AbstractBackground and PurposeStudying drug metabolizing enzymes, encoded by pharmacogenes (PGx), may inform biological mechanisms underlying the diseases for which a medication is prescribed. Until recently, PGx loci could not be studied at biobank scale. Here we analyze PGx haplotype variation to detect associations with medication use in the UK Biobank.MethodsIn 7,649 unrelated African-ancestry (AFR) and 326,214 unrelated European-ancestry (EUR) participants from the UK Biobank, aged 37-73 at time of recruitment, we associated clinically-relevant PGx haplotypes with 265 (EUR) and 17 (AFR) medication use phenotypes using generalized linear models covaried with sex, age, age2, sex×age, sex×age2, and ten principal components of ancestry. Haplotypes across 50 genes were assigned with Stargazer. Our analyses focused on the association of PGx haplotype dose (quantitative predictor), diplotype (categorical predictor), and rare haplotype burden on medication use.ResultsIn EUR, NAT2 metabolizer phenotype (OR=1.05, 95% CI: 1.03-1.08, p=7.03×10−6) and activity score (OR=1.09, 95% CI: 1.05-1.14, p=2.46×10−6) were associated with simvastatin use. The dose of N-acetyltransferase 2 (NAT2)*1 was associated with simvastatin use relative to NAT2*5 (NAT2*1 OR=1.04, 95% CI=1.03-1.07, p=1.37×10−5) and was robust to effects of low-density lipoprotein cholesterol (LDL-C) concentration (NAT2*1 given LDL-C concentration: OR=1.07, 95% CI=1.05-1.09, p=1.14×10−8) and polygenic risk for LDL-C concentration (NAT2*1 given LDL-C PRS: OR=1.09, 95% CI=1.04-1.14, p=2.26×10−4). Interactive effects between NAT2*1, simvastatin use, and LDL-C concentration (OR: 0.957, 95% CI=0.916-0.998, p=0.045) were replicated in eMERGE PGx cohort (OR: 0.987, 95% CI: 0.976-0.998, p=0.029).Conclusions and relevanceWe used biobank-scale data to uncover and replicate a novel association between NAT2 locus variation (and suggestive evidence with several other genes) and better response to simvastatin (and other statins) therapy. The presence of NAT2*1 versus NAT2*5 may therefore be useful for making clinically informative decisions regarding the potential benefit (e.g., absolute risk reduction) in LDL-C concentration prior to statin treatment.Subject termsgenetics, genetic association studies, cardiovascular disease

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.

Shared genetic influences on depression and menopause symptoms

2021 ◽  
pp. 1-11
Author(s):  
Joeri J. Meijsen ◽  
Hanyang Shen ◽  
Mytilee Vemuri ◽  
Natalie L. Rasgon ◽  
Karestan C. Koenen ◽  
...  
Keyword(s):  
Genetic Correlation ◽  
Hot Flashes ◽  
Medication Use ◽  
European Ancestry ◽  
Genetic Influences ◽  
Uk Biobank ◽  
Genetic Analyses ◽  
Correlation Analyses ◽  
The Uk ◽  
Shared Genetic

Abstract Background Women experience major depression and post-traumatic stress disorder (PTSD) approximately twice as often as men. Estrogen is thought to contribute to sex differences in these disorders, and reduced estrogen is also known to be a key driver of menopause symptoms such as hot flashes. Moreover, estrogen is used to treat menopause symptoms. In order to test for potential shared genetic influences between menopause symptoms and psychiatric disorders, we conducted a genome-wide association study (GWAS) of estrogen medication use (as a proxy for menopause symptoms) in the UK Biobank. Methods The analysis included 232 993 women aged 39–71 in the UK Biobank. The outcome variable for genetic analyses was estrogen medication use, excluding women using hormonal contraceptives. Trans-ancestry GWAS meta-analyses were conducted along with genetic correlation analyses on the European ancestry GWAS results. Hormone usage was also tested for association with depression and PTSD. Results GWAS of estrogen medication use (compared to non-use) identified a locus in the TACR3 gene, which was previously linked to hot flashes in menopause [top rs77322567, odds ratio (OR) = 0.78, p = 7.7 × 10−15]. Genetic correlation analyses revealed shared genetic influences on menopause symptoms and depression (rg = 0.231, s.e.= 0.055, p = 2.8 × 10−5). Non-genetic analyses revealed higher psychiatric symptoms scores among women using estrogen medications. Conclusions These results suggest that menopause symptoms have a complex genetic etiology which is partially shared with genetic influences on depression. Moreover, the TACR3 gene identified here has direct clinical relevance; antagonists for the neurokinin 3 receptor (coded for by TACR3) are effective treatments for hot flashes.

scholarly journals Analyses of Biomarker Traits in Diverse UK Biobank Participants Identify Associations Missed by European-centric Analysis Strategies

2020 ◽  
Author(s):  
Quan Sun ◽  
Misa Graff ◽  
Bryce Rowland ◽  
Jia Wen ◽  
Le Huang ◽  
...  
Keyword(s):  
South Asian ◽  
Human Genetics ◽  
Association Studies ◽  
African Ancestry ◽  
European Ancestry ◽  
Gamma Glutamyl Transferase ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Genes Encoding ◽  
Glutamyl Transferase

AbstractDespite the dramatic underrepresentation of non-European populations in human genetics studies, researchers continue to exclude participants of non-European ancestry, even when these data are available. This practice perpetuates existing research disparities and can lead to important and large effect size associations being missed. Here, we conducted genome-wide association studies (GWAS) of 31 serum and urine biomarker quantitative traits in African (n=9354), East Asian (n=2559) and South Asian (n=9823) UK Biobank participants ancestry. We adjusted for all known GWAS catalog variants for each trait, as well as novel signals identified in European ancestry UK Biobank participants alone. We identify 12 novel signals in African ancestry and 3 novel signals in South Asian participants (p<1.61 × 10−10). Many of these signals are highly plausible and rare in Europeans (1% or lower minor allele frequency), including cis pQTLs for the genes encoding serum biomarkers like gamma-glutamyl transferase and apolipoprotein A, PIEZ01 and G6PD variants with impacts on HbA1c through likely erythocytic mechanisms, and a coding variant in GPLD1, a gene which cleaves GPI-anchors, associated with normally GPI-anchored protein alkaline phosphatase in serum. This work illustrates the importance of using the genetic data we already have in diverse populations, with many novel discoveries possible in even modest sample sizes.

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 Cardiometabolic risk factors for COVID-19 susceptibility and severity: A Mendelian randomization analysis

PLoS Medicine ◽  
2021 ◽  
Vol 18 (3) ◽  
pp. e1003553
Author(s):  
Aaron Leong ◽  
Joanne B. Cole ◽  
Laura N. Brenner ◽  
James B. Meigs ◽  
Jose C. Florez ◽  
...  
Keyword(s):  
Odds Ratio ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Statistical Significance ◽  
Epidemiological Studies ◽  
Population Based ◽  
European Ancestry ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
The Uk

Background Epidemiological studies report associations of diverse cardiometabolic conditions including obesity with COVID-19 illness, but causality has not been established. We sought to evaluate the associations of 17 cardiometabolic traits with COVID-19 susceptibility and severity using 2-sample Mendelian randomization (MR) analyses. Methods and findings We selected genetic variants associated with each exposure, including body mass index (BMI), at p < 5 × 10−8 from genome-wide association studies (GWASs). We then calculated inverse-variance-weighted averages of variant-specific estimates using summary statistics for susceptibility and severity from the COVID-19 Host Genetics Initiative GWAS meta-analyses of population-based cohorts and hospital registries comprising individuals with self-reported or genetically inferred European ancestry. Susceptibility was defined as testing positive for COVID-19 and severity was defined as hospitalization with COVID-19 versus population controls (anyone not a case in contributing cohorts). We repeated the analysis for BMI with effect estimates from the UK Biobank and performed pairwise multivariable MR to estimate the direct effects and indirect effects of BMI through obesity-related cardiometabolic diseases. Using p < 0.05/34 tests = 0.0015 to declare statistical significance, we found a nonsignificant association of genetically higher BMI with testing positive for COVID-19 (14,134 COVID-19 cases/1,284,876 controls, p = 0.002; UK Biobank: odds ratio 1.06 [95% CI 1.02, 1.10] per kg/m2; p = 0.004]) and a statistically significant association with higher risk of COVID-19 hospitalization (6,406 hospitalized COVID-19 cases/902,088 controls, p = 4.3 × 10−5; UK Biobank: odds ratio 1.14 [95% CI 1.07, 1.21] per kg/m2, p = 2.1 × 10−5). The implied direct effect of BMI was abolished upon conditioning on the effect on type 2 diabetes, coronary artery disease, stroke, and chronic kidney disease. No other cardiometabolic exposures tested were associated with a higher risk of poorer COVID-19 outcomes. Small study samples and weak genetic instruments could have limited the detection of modest associations, and pleiotropy may have biased effect estimates away from the null. Conclusions In this study, we found genetic evidence to support higher BMI as a causal risk factor for COVID-19 susceptibility and severity. These results raise the possibility that obesity could amplify COVID-19 disease burden independently or through its cardiometabolic consequences and suggest that targeting obesity may be a strategy to reduce the risk of severe COVID-19 outcomes.

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 Theoretical and empirical quantification of the accuracy of polygenic scores in ancestry divergent populations

2020 ◽  
Author(s):  
Ying Wang ◽  
Jing Guo ◽  
Guiyan Ni ◽  
Jian Yang ◽  
Peter M. Visscher ◽  
...  
Keyword(s):  
Complex Traits ◽  
Association Studies ◽  
African Ancestry ◽  
Real Data ◽  
European Ancestry ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Polygenic Scores ◽  
Causal Variants ◽  
The Uk

AbstractPolygenic scores (PGS) have been widely used to predict complex traits and risk of diseases using variants identified from genome-wide association studies (GWASs). To date, most GWASs have been conducted in populations of European ancestry, which limits the use of GWAS-derived PGS in non-European populations. Here, we develop a new theory to predict the relative accuracy (RA, relative to the accuracy in populations of the same ancestry as the discovery population) of PGS across ancestries. We used simulations and real data from the UK Biobank to evaluate our results. We found across various simulation scenarios that the RA of PGS based on trait-associated SNPs can be predicted accurately from modelling linkage disequilibrium (LD), minor allele frequencies (MAF), cross-population correlations of SNP effect sizes and heritability. Altogether, we find that LD and MAF differences between ancestries explain alone up to ~70% of the loss of RA using European-based PGS in African ancestry for traits like body mass index and height. Our results suggest that causal variants underlying common genetic variation identified in European ancestry GWASs are mostly shared across continents.

scholarly journals Comparison of Two Genome-Wide Association Studies for Heart Rate Response to Exercise from the UK Biobank

2021 ◽  
Author(s):  
Abhinav Thakral ◽  
Andrew D Paterson
Keyword(s):  
Heart Rate ◽  
Association Studies ◽  
Genome Wide Association ◽  
European Ancestry ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Post Exercise ◽  
Genome Wide ◽  
The Difference ◽  
The Uk

The short-term changes in heart rate (HR) during and after exercise are important physiologic traits mediated via the autonomic nervous system. Variations in these traits are associated with mortality from cardiovascular causes. We conducted a systematic review of genome-wide association studies for these traits (with >10,000 participants) with the aim of comparing Polygenic Risk Scores (PRS) from different studies. Additionally, we applied the STrengthening of Reporting of Genetic Association Studies (STREGA) statement for assessing the completeness of reporting of evidence. Our systematic search yielded two studies (Verweij et al. and Ramirez et al.) that met our inclusion criteria. Both were conducted on the UK Biobank. Both defined their exercise traits as the difference between resting HR and the maximum HR during exercise. Their recovery traits were defined differently. Verweij et al. defined 5 recovery traits as the differences between the peak HR during exercise and the HRs at 10-50 sec post exercise cessation. Ramirez et al. defined their recovery trait as the difference between peak HR during exercise and the minimum HR during the minute post exercise cessation. While Ramirez et al. divided their sample into discovery and replication subsets, Verweij et al. analyzed the whole sample together. In terms of results, there were several common SNPs identified between studies and traits. There was evidence for the phenomenon of winners curse operating for a SNP from the Ramirez studys HR recovery analysis. Many of the SNPs were mutually exclusive between the studies. However, there was a good agreement of PRS from the studies. The differences in the results could be attributed to the different exclusion criteria, analytic approaches, and definitions of traits used. Both studies had an under-representation of individuals of non-European ancestry compared to those of European ancestry. Further studies with proportionate representation of individuals of all ancestries would help address this gap.

Contrasting Broad- and Clinically- defined Polygenic Indicators of Depression and Depression-related Phenotypes in Adults and Children

2020 ◽  
Author(s):  
John E. McGeary ◽  
Chelsie Benca-Bachman ◽  
Victoria Risner ◽  
Christopher G Beevers ◽  
Brandon Gibb ◽  
...  
Keyword(s):  
Suicidal Ideation ◽  
Cognitive Reappraisal ◽  
Twin Studies ◽  
European Ancestry ◽  
Summary Statistics ◽  
Depression Severity ◽  
Uk Biobank ◽  
Polygenic Scores ◽  
Adults And Children ◽  
The Uk

Twin studies indicate that 30-40% of the disease liability for depression can be attributed to genetic differences. Here, we assess the explanatory ability of polygenic scores (PGS) based on broad- (PGSBD) and clinical- (PGSMDD) depression summary statistics from the UK Biobank using independent cohorts of adults (N=210; 100% European Ancestry) and children (N=728; 70% European Ancestry) who have been extensively phenotyped for depression and related neurocognitive phenotypes. PGS associations with depression severity and diagnosis were generally modest, and larger in adults than children. Polygenic prediction of depression-related phenotypes was mixed and varied by PGS. Higher PGSBD, in adults, was associated with a higher likelihood of having suicidal ideation, increased brooding and anhedonia, and lower levels of cognitive reappraisal; PGSMDD was positively associated with brooding and negatively related to cognitive reappraisal. Overall, PGS based on both broad and clinical depression phenotypes have modest utility in adult and child samples of depression.

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.

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