Public health applications of cardiovascular genomics

Background Genetic epidemiology is at the interface of translational and basic research and the pace of progress has been unprecedented, with findings representing some of the most robust available in the Scientific literature. However, how we can translate this high- fidelity genomic information into improvements in health of the population? Two dis¬tinct translational opportunities include personalized medicine (pharmacogenetics) and using Mendelian randomization to investigate disease aetiology to inform public health policy and develop new therapies. Objectives In this PhD thesis, I investigated the evidence base underlying the well-publicized use of the pharmacogenetic biomarker CYP2C19 genotype to predict the response to clopi¬dogrel, a widely prescribed antiplatelet drug. Second, I used Mendelian randomization to investigate the role of an endogenous biomarker, secretory phospholipase A2-IIA (sPLA2-IIA), thought to be a pro-atherogenic enzyme and a potential drug target for the prevention of cardiovascular disease (CVD). Third, I used Mendelian randomization to investigate the relationship between alcohol, an exogenous exposure, and cardiovas¬cular traits and disease events. Results CYP2C19 and cardiovascular disease I identified 32 studies of 42,016 patients reporting 3545 CVD events. Only 6 studies were set within randomized trials (“effect-modification” design) and the remaining 26 reported individuals exposed to clopidogrel (“treatment-only” design). In treatment- only studies, possession of one or more *2-*8 CYP2C19 alleles was associated with lower cytochrome P450 C19 (CYP2C19) enzyme activity and a higher risk of CVD events (RR 1.18; 95%CI:1.09, 1.28), however, there was strong evidence of small-study bias (Harbord test P=0.001) and, when restricted to large studies (≥200 events), the association of CYP2C19 *2-*8 carrier status with CVD was null (RR 0.97; 95%CI: 0.86, 1.09). In the effect-modification studies, CYP2C19 genotype did not modify the effect of clopidogrel on CVD end-points. These findings cast doubt on whether information on CYP2C19 genotype would be helpful to guide selection of the dose of clopidogrel or use of an alternative antiplatelet agent. The role of secretory phospholipase A2-IIA (sPLA2-IIA) in CVD I used Mendelian randomization to make causal inference on the role of sPLA2-IIA in CVD. I identified a single nucleotide polymorphism (SNP) in PLA2G2A (rs11573 156) that was specific for and had a very strong impact on circulating levels of the sPLA2-IIA isoform. Using data from 36 studies and over 100,000 participants, instrumental variable analysis found no association between sPLA2-IIA with incident, prevalent or recurrent CVD events. These findings suggest sPLA2-IIA is not a valid therapeutic target for CVD prevention, which was in keeping with a phase III randomized clinical trial that was halted for futility in 2012 (during this thesis). Alcohol and CVD I used a SNP in ADH1B to investigate the relationship between alcohol and coronary heart disease (CHD) in >260,000 participants. The genetic variant (ADH1B rs1229984 A-allele) showed very strong association with reduced alcohol consumption when evalu¬ated as volume of alcohol consumed, binge drinking and abstaining from alcohol. The A-allele of rs1229984 showed associations with SBP, CRP, IL-6, BMI and waist circum¬ference that were all directionally concordant with a reduced risk of CHD. Indeed, when the clinical outcome CHD was investigated, individuals carrying the A-allele (who con¬sumed less alcohol than non-carriers) had a reduced risk of CHD at all levels of alcohol consumption. No evidence of a cardioprotective association of alcohol with CHD was identified. Conclusions My investigation into use of CYP2C19 genotype as a pharmacogenetic biomarker for clopidogrel response did not identify evidence to support its clinical use and limitations were identified that could apply to other pharmacogenetic tests. Use of Mendelian randomization revealed no evidence to support a causal role of sPLA2- IIA in CVD, which paralleled findings from a phase III randomized clinical trial, and provides support for the use of Mendelian randomization studies more widely to in¬form drug development. Finally, using the ADH1B gene to interrogate the relationship of alcohol yielded findings that argue against a cardioprotective effect of alcohol con¬sumption. These findings should encourage rethinking of public health advice about the cardiovascular benefits of moderate levels of alcohol consumption

Type 2 Diabetes, Metabolic traits and Risk of Heart Failure:a Mendelian Randomization study

OBJECTIVE: The aim of this study was to use Mendelian randomization (MR) techniques to estimate the causal relationships between genetic liability to type 2 diabetes (T2D), glycemic traits, and risk of heart failure (HF). RESEARCH DESIGN AND METHODS: Summary-level data were obtained from genome-wide association studies of T2D, insulin resistance (IR), glycated hemoglobin, fasting insulin and glucose, and HF. MR was conducted using the inverse-variance weighted method. Sensitivity analyses included the MR-Egger method, weighted median and mode methods, and multivariable MR conditioning on potential mediators. RESULTS: Genetic liability to T2D was causally related to higher risk of HF (odds ratio [OR] 1.13 per 1-log unit higher risk of T2D; 95% CI 1.11-1.14; P < 0.001); however, sensitivity analysis revealed evidence of directional pleiotropy. The relationship between T2D and HF was attenuated when adjusted for coronary disease, BMI, LDL cholesterol, and blood pressure in multivariable MR. Genetically instrumented higher IR was associated with higher risk of HF (OR 1.19 per 1-log unit higher risk of IR; 95% CI 1.00-1.41; P = 0.041). There were no notable associations identified between fasting insulin, glucose, or glycated hemoglobin and risk of HF. Genetic liability to HF was causally linked to higher risk of T2D (OR 1.49; 95% CI 1.01-2.19; P = 0.042), although again with evidence of pleiotropy. CONCLUSIONS: These findings suggest a possible causal role of T2D and IR in HF etiology, although the presence of both bidirectional effects and directional pleiotropy highlights potential sources of bias that must be considered

Type 2 Diabetes, Metabolic Traits, and Risk of Heart Failure: A Mendelian Randomization Study

OBJECTIVE: The aim of this study was to use Mendelian randomization (MR) techniques to estimate the causal relationships between genetic liability to type 2 diabetes (T2D), glycemic traits, and risk of heart failure (HF). RESEARCH DESIGN AND METHODS: Summary-level data were obtained from genome-wide association studies of T2D, insulin resistance (IR), glycated hemoglobin, fasting insulin and glucose, and HF. MR was conducted using the inverse-variance weighted method. Sensitivity analyses included the MR-Egger method, weighted median and mode methods, and multivariable MR conditioning on potential mediators. RESULTS: Genetic liability to T2D was causally related to higher risk of HF (odds ratio [OR] 1.13 per 1-log unit higher risk of T2D; 95% CI 1.11-1.14; P < 0.001); however, sensitivity analysis revealed evidence of directional pleiotropy. The relationship between T2D and HF was attenuated when adjusted for coronary disease, BMI, LDL cholesterol, and blood pressure in multivariable MR. Genetically instrumented higher IR was associated with higher risk of HF (OR 1.19 per 1-log unit higher risk of IR; 95% CI 1.00-1.41; P = 0.041). There were no notable associations identified between fasting insulin, glucose, or glycated hemoglobin and risk of HF. Genetic liability to HF was causally linked to higher risk of T2D (OR 1.49; 95% CI 1.01-2.19; P = 0.042), although again with evidence of pleiotropy. CONCLUSIONS: These findings suggest a possible causal role of T2D and IR in HF etiology, although the presence of both bidirectional effects and directional pleiotropy highlights potential sources of bias that must be considered

Longitudinal trajectories of blood lipid levels in an ageing population sample of Russian Western-Siberian urban population

This study investigated 12-year blood lipid trajectories and whether these trajectories are modified by smoking and lipid lowering treatment in older Russians. To do so, we analysed data on 9,218 Russian West-Siberian Caucasians aged 45-69 years at baseline participating in the international HAPIEE cohort study. Mixed-effect multilevel models were used to estimate individual level lipid trajectories across the baseline and two follow-up examinations (16,445 separate measurements over 12 years). In all age groups, we observed a reduction in serum total cholesterol (TC), LDL-C and non-HDL-C over time even after adjusting for sex, statin treatment, hypertension, diabetes, social factors and mortality (P 60 years at baseline). In smokers, TC, LDL-C, non-HDL-C and TG decreased less markedly than in non-smokers, while HDL-C decreased more rapidly while the LDL-C/HDL-C ratio increased. In subjects treated with lipid-lowering drugs, TC, LDL-C and non-HDL-C decreased more markedly and HDL-C less markedly than in untreated subjects while TG and LDL-C/HDL-C remained stable or increased in treatment naïve subjects. We conclude, that in this ageing population we observed marked changes in blood lipids over a 12 year follow up, with decreasing trajectories of TC, LDL-C and non-HDL-C and mixed trajectories of TG. The findings suggest that monitoring of age-related trajectories in blood lipids may improve prediction of CVD risk beyond single measurements

Metabolic profiling of angiopoietin-like protein 3 and 4 inhibition: a drug-target Mendelian randomization analysis

AIMS : Angiopoietin-like protein 3 (ANGPTL3) and 4 (ANGPTL4) inhibit lipoprotein lipase (LPL) and represent emerging drug targets to lower circulating triglycerides and reduce cardiovascular risk. To investigate the molecular effects of genetic mimicry of ANGPTL3 and ANGPTL4 inhibition and compare them to the effects of genetic mimicry of LPL enhancement. METHODS AND RESULTS : Associations of genetic variants in ANGPTL3 (rs11207977-T), ANGPTL4 (rs116843064-A), and LPL (rs115849089-A) with an extensive serum lipid and metabolite profile (208 measures) were characterized in six cohorts of up to 61 240 participants. Genetic associations with anthropometric measures, glucose-insulin metabolism, blood pressure, markers of kidney function, and cardiometabolic endpoints via genome-wide summary data were also explored. ANGPTL4 rs116843064-A and LPL rs115849089-A displayed a strikingly similar pattern of associations across the lipoprotein and lipid measures. However, the corresponding associations with ANGPTL3 rs11207977-T differed, including those for low-density lipoprotein and high-density lipoprotein particle concentrations and compositions. All three genotypes associated with lower concentrations of an inflammatory biomarker glycoprotein acetyls and genetic mimicry of ANGPTL3 inhibition and LPL enhancement were also associated with lower C-reactive protein. Genetic mimicry of ANGPTL4 inhibition and LPL enhancement were associated with a lower waist-to-hip ratio, improved insulin-glucose metabolism, and lower risk of coronary heart disease and type 2 diabetes, whilst genetic mimicry of ANGPTL3 was associated with improved kidney function. CONCLUSIONS : Genetic mimicry of ANGPTL4 inhibition and LPL enhancement have very similar systemic metabolic effects, whereas genetic mimicry of ANGPTL3 inhibition showed differing metabolic effects, suggesting potential involvement of pathways independent of LPL. Genetic mimicry of ANGPTL4 inhibition and LPL enhancement were associated with a lower risk of coronary heart disease and type 2 diabetes. These findings reinforce evidence that enhancing LPL activity (either directly or via upstream effects) through pharmacological approaches is likely to yield benefits to human health

Stroke genetics: prospects for personalized medicine.

Epidemiologic evidence supports a genetic predisposition to stroke. Recent advances, primarily using the genome-wide association study approach, are transforming what we know about the genetics of multifactorial stroke, and are identifying novel stroke genes. The current findings are consistent with different stroke subtypes having different genetic architecture. These discoveries may identify novel pathways involved in stroke pathogenesis, and suggest new treatment approaches. However, the already identified genetic variants explain only a small proportion of overall stroke risk, and therefore are not currently useful in predicting risk for the individual patient. Such risk prediction may become a reality as identification of a greater number of stroke risk variants that explain the majority of genetic risk proceeds, and perhaps when information on rare variants, identified by whole-genome sequencing, is also incorporated into risk algorithms. Pharmacogenomics may offer the potential for earlier implementation of 'personalized genetic' medicine. Genetic variants affecting clopidogrel and warfarin metabolism may identify non-responders and reduce side-effects, but these approaches have not yet been widely adopted in clinical practice

Sex Differences in the Risk of Coronary Heart Disease Associated With Type 2 Diabetes: A Mendelian Randomization Analysis

OBJECTIVE: Observational studies have demonstrated that type 2 diabetes is a stronger risk factor for coronary heart disease (CHD) in women compared with men. However, it is not clear whether this reflects a sex differential in the causal effect of diabetes on CHD risk or results from sex-specific residual confounding. RESEARCH DESIGN AND METHODS: Using 270 single nucleotide polymorphisms (SNPs) for type 2 diabetes identified in a type 2 diabetes genome-wide association study, we performed a sex-stratified Mendelian randomization (MR) study of type 2 diabetes and CHD using individual participant data in UK Biobank (251,420 women and 212,049 men). Weighted median, MR-Egger, MR-pleiotropy residual sum and outlier, and radial MR from summary-level analyses were used for pleiotropy assessment. RESULTS: MR analyses showed that genetic risk of type 2 diabetes increased the odds of CHD for women (odds ratio 1.13 [95% CI 1.08–1.18] per 1-log unit increase in odds of type 2 diabetes) and men (1.21 [1.17–1.26] per 1-log unit increase in odds of type 2 diabetes). Sensitivity analyses showed some evidence of directional pleiotropy; however, results were similar after correction for outlier SNPs. CONCLUSIONS: This MR analysis supports a causal effect of genetic liability to type 2 diabetes on risk of CHD that is not stronger for women than men. Assuming a lack of bias, these findings suggest that the prevention and management of type 2 diabetes for CHD risk reduction is of equal priority in both sexes

Mendelian randomization for studying the effects of perturbing drug targets [version 1; peer review: awaiting peer review]

Drugs whose targets have genetic evidence to support efficacy and safety are more likely to be approved after clinical development. In this paper, we provide an overview of how natural sequence variation in the genes that encode drug targets can be used in Mendelian randomization analyses to offer insight into mechanism-based efficacy and adverse effects. Large databases of summary level genetic association data are increasingly available and can be leveraged to identify and validate variants that serve as proxies for drug target perturbation. As with all empirical research, Mendelian randomization has limitations including genetic confounding, its consideration of lifelong effects, and issues related to heterogeneity across different tissues and populations. When appropriately applied, Mendelian randomization provides a useful empirical framework for using population level data to improve the success rates of the drug development pipeline