Applications of genetic data to identify cardiovascular disease mechanisms and therapeutic opportunities

Recent years have offered a wealth of genetic association data, with a concurrent explosion in the availability of methods for exploring causal effects through randomly allocated genetic variants that serve as proxies for traits of interest. This thesis investigates the state of this field within the remit of cardiovascular disease. Following an introduction into cardiovascular disease and Mendelian randomization (MR), the research focuses on dietary, social and pharmacological exposures as demonstrative examples for highlighting the breadth of techniques that can be harnessed towards understanding underlying mechanisms and therapeutic opportunities. Both two-sample and one-sample MR analyses are performed, using genetic summary data from large-scale consortia and the UK Biobank. Sample sizes for individual analyses typically exceed tens of thousands of participants. A diverse array of MR methods are employed, appropriate to the setting and objective of each analysis. Considering systemic iron status as a diet-related trait, genetic instruments are identified with consequent MR analyses supporting a protective effect on risk of cardiovascular outcomes related to atherosclerosis but a detrimental effect on outcomes related to thrombosis arising from stasis of blood. Phenome-wide association study further highlights effects of systemic iron status outside the remit of cardiovascular disease. In the investigation of social factors, MR mediation analysis techniques are applied to identify the pathways by which education affects cardiovascular disease risk, with multivariable MR further used to disentangle the direct effects of education and intelligence respectively. In the investigation of pharmacological exposures, genetic instruments for antihypertensive drugs are identified and validated by comparing against corresponding estimates from clinical trials. Phenome-wide association study is used to identify possible side-effects and repurposing opportunities, with a potential detrimental effect of calcium channel blockers identified on risk of diverticulosis. The final section provides an overview of the current state of applied MR, as well as future perspectives.Open Acces

Noise-augmented directional clustering of genetic association data identifies distinct mechanisms underlying obesity.

Funder: NIHR Cambridge Biomedical Research CentreClustering genetic variants based on their associations with different traits can provide insight into their underlying biological mechanisms. Existing clustering approaches typically group variants based on the similarity of their association estimates for various traits. We present a new procedure for clustering variants based on their proportional associations with different traits, which is more reflective of the underlying mechanisms to which they relate. The method is based on a mixture model approach for directional clustering and includes a noise cluster that provides robustness to outliers. The procedure performs well across a range of simulation scenarios. In an applied setting, clustering genetic variants associated with body mass index generates groups reflective of distinct biological pathways. Mendelian randomization analyses support that the clusters vary in their effect on coronary heart disease, including one cluster that represents elevated body mass index with a favourable metabolic profile and reduced coronary heart disease risk. Analysis of the biological pathways underlying this cluster identifies inflammation as potentially explaining differences in the effects of increased body mass index on coronary heart disease

Estimating the Population Benefits of Blood Pressure Lowering: A Wide-Angled Mendelian Randomization Study in UK Biobank.

Background The causal relevance of elevated blood pressure for several cardiovascular diseases (CVDs) is uncertain, as is the population impact of blood pressure lowering. This study systematically assesses evidence of causality for various CVDs in a 2-sample Mendelian randomization framework, and estimates the potential reduction in the prevalence of these diseases attributable to long-term population shifts in the distribution of systolic blood pressure (SBP). Methods and Results We investigated associations of genetically predicted SBP as predicted by 256 genetic variants with 21 CVDs in UK Biobank, a population-based cohort of UK residents. The sample consisted of 376 703 participants of European ancestry, aged 40 to 69 years at recruitment. Genetically predicted SBP was positively associated with 14 of the outcomes (P<0.002), including dilated cardiomyopathy, endocarditis, peripheral vascular disease, and rheumatic heart disease. Using genetic variation to estimate the long-term impact of blood pressure lowering on disease in a middle-aged to early late-aged UK-based population, population reductions in SBP were predicted to result in an overall 16.9% (95% CI, 12.2%-21.3%) decrease in morbidity for a 5-mm Hg decrease from a population mean of 137.7 mm Hg, 30.8% (95% CI, 22.8%-38.0%) decrease for a 10-mm Hg decrease, and 56.2% (95% CI, 43.7%-65.9%) decrease for a 22.7-mm Hg decrease in SBP (22.7 mm Hg represents a shift from the current mean SBP to 115 mm Hg). Conclusions Risk of many CVDs is influenced by long-term differences in SBP. The burden of a broad range of CVDs could be substantially reduced by long-term population-wide reductions in the distribution of blood pressure

Noise-augmented directional clustering of genetic association data identifies distinct mechanisms underlying obesity.

Funder: NIHR Cambridge Biomedical Research CentreClustering genetic variants based on their associations with different traits can provide insight into their underlying biological mechanisms. Existing clustering approaches typically group variants based on the similarity of their association estimates for various traits. We present a new procedure for clustering variants based on their proportional associations with different traits, which is more reflective of the underlying mechanisms to which they relate. The method is based on a mixture model approach for directional clustering and includes a noise cluster that provides robustness to outliers. The procedure performs well across a range of simulation scenarios. In an applied setting, clustering genetic variants associated with body mass index generates groups reflective of distinct biological pathways. Mendelian randomization analyses support that the clusters vary in their effect on coronary heart disease, including one cluster that represents elevated body mass index with a favourable metabolic profile and reduced coronary heart disease risk. Analysis of the biological pathways underlying this cluster identifies inflammation as potentially explaining differences in the effects of increased body mass index on coronary heart disease

Evaluating the relationship between alcohol consumption, tobacco use, and cardiovascular disease: A multivariable Mendelian randomization study

BackgroundAlcohol consumption and smoking, 2 major risk factors for cardiovascular disease (CVD), often occur together. The objective of this study is to use a wide range of CVD risk factors and outcomes to evaluate potential total and direct causal roles of alcohol and tobacco use on CVD risk factors and events.Methods and findingsUsing large publicly available genome-wide association studies (GWASs) (results from more than 1.2 million combined study participants) of predominantly European ancestry, we conducted 2-sample single-variable Mendelian randomization (SVMR) and multivariable Mendelian randomization (MVMR) to simultaneously assess the independent impact of alcohol consumption and smoking on a wide range of CVD risk factors and outcomes. Multiple sensitivity analyses, including complementary Mendelian randomization (MR) methods, and secondary alcohol consumption and smoking datasets were used. SVMR showed genetic predisposition for alcohol consumption to be associated with CVD risk factors, including high-density lipoprotein cholesterol (HDL-C) (beta 0.40, 95% confidence interval (CI), 0.04-0.47, P value = 1.72 × 10-28), triglycerides (TRG) (beta -0.23, 95% CI, -0.30, -0.15, P value = 4.69 × 10-10), automated systolic blood pressure (BP) measurement (beta 0.11, 95% CI, 0.03-0.18, P value = 4.72 × 10-3), and automated diastolic BP measurement (beta 0.09, 95% CI, 0.03-0.16, P value = 5.24 × 10-3). Conversely, genetically predicted smoking was associated with increased TRG (beta 0.097, 95% CI, 0.014-0.027, P value = 6.59 × 10-12). Alcohol consumption was also associated with increased myocardial infarction (MI) and coronary heart disease (CHD) risks (MI odds ratio (OR) = 1.24, 95% CI, 1.03-1.50, P value = 0.02; CHD OR = 1.21, 95% CI, 1.01-1.45, P value = 0.04); however, its impact was attenuated in MVMR adjusting for smoking. Conversely, alcohol maintained an association with coronary atherosclerosis (OR 1.02, 95% CI, 1.01-1.03, P value = 5.56 × 10-4). In comparison, after adjusting for alcohol consumption, smoking retained its association with several CVD outcomes including MI (OR = 1.84, 95% CI, 1.43, 2.37, P value = 2.0 × 10-6), CHD (OR = 1.64, 95% CI, 1.28-2.09, P value = 8.07 × 10-5), heart failure (HF) (OR = 1.61, 95% CI, 1.32-1.95, P value = 1.9 × 10-6), and large artery atherosclerosis (OR = 2.4, 95% CI, 1.41-4.07, P value = 0.003). Notably, using the FinnGen cohort data, we were able to replicate the association between smoking and several CVD outcomes including MI (OR = 1.77, 95% CI, 1.10-2.84, P value = 0.02), HF (OR = 1.67, 95% CI, 1.14-2.46, P value = 0.008), and peripheral artery disease (PAD) (OR = 2.35, 95% CI, 1.38-4.01, P value = 0.002). The main limitations of this study include possible bias from unmeasured confounders, inability of summary-level MR to investigate a potentially nonlinear relationship between alcohol consumption and CVD risk, and the generalizability of the UK Biobank (UKB) to other populations.ConclusionsEvaluating the widest range of CVD risk factors and outcomes of any alcohol consumption or smoking MR study to date, we failed to find a cardioprotective impact of genetically predicted alcohol consumption on CVD outcomes. However, alcohol was associated with and increased HDL-C, decreased TRG, and increased BP, which may indicate pathways through impact CVD risk, warranting further study. We found smoking to be a risk factor for many CVDs even after adjusting for alcohol. While future studies incorporating alcohol consumption patterns are necessary, our data suggest causal inference between alcohol, smoking, and CVD risk, further supporting that lifestyle modifications might be able to reduce overall CVD risk