In complex trait genetics, the ability to predict phenotype from genotype is the ultimate measure of our understanding of genetic architecture underlying the heritability of a trait. A complete understanding of the genetic basis of a trait should allow for predictive methods with accuracies approaching the trait's heritability. The highly polygenic nature of quantitative traits and most common phenotypes has motivated the development of statistical strategies focused on combining myriad individually non-significant genetic effects. Now that predictive accuracies are improving, there is a growing interest in the practical utility of such methods for predicting risk of common diseases responsive to early therapeutic intervention. However, existing methods require individual-level genotypes or depend on accurately specifying the genetic architecture underlying each disease to be predicted. Here, we propose a polygenic risk prediction method that does not require explicitly modeling any underlying genetic architecture. We start with summary statistics in the form of SNP effect sizes from a large GWAS cohort. We then remove the correlation structure across summary statistics arising due to linkage disequilibrium and apply a piecewise linear interpolation on conditional mean effects. In both simulated and real datasets, this new non-parametric shrinkage (NPS) method can reliably allow for linkage disequilibrium in summary statistics of 5 million dense genome-wide markers and consistently improves prediction accuracy. We show that NPS improves the identification of groups at high risk for breast cancer, type 2 diabetes, inflammatory bowel disease, and coronary heart disease, all of which have available early intervention or prevention treatments.

BACKGROUND: Nitric oxide signaling plays a key role in the regulation of vascular tone and platelet activation. Here, we seek to understand the impact of a genetic predisposition to enhanced nitric oxide signaling on risk for cardiovascular diseases, thus informing the potential utility of pharmacological stimulation of the nitric oxide pathway as a therapeutic strategy.METHODS: We analyzed the association of common and rare genetic variants in 2 genes that mediate nitric oxide signaling (Nitric Oxide Synthase 3 [NOS3] and Guanylate Cyclase 1, Soluble, Alpha 3 [GUCY1A3]) with a range of human phenotypes. We selected 2 common variants (rs3918226 in NOS3 and rs7692387 in GUCY1A3) known to associate with increased NOS3 and GUCY1A3 expression and reduced mean arterial pressure, combined them into a genetic score, and standardized this exposure to a 5 mm Hg reduction in mean arterial pressure. Using individual-level data from 335 464 participants in the UK Biobank and summary association results from 7 large-scale genome-wide association studies, we examined the effect of this nitric oxide signaling score on cardiometabolic and other diseases. We also examined whether rare loss-of-function mutations in NOS3 and GUCY1A3 were associated with coronary heart disease using gene sequencing data from the Myocardial Infarction Genetics Consortium (n=27 815).RESULTS: A genetic predisposition to enhanced nitric oxide signaling was associated with reduced risks of coronary heart disease (odds ratio, 0.37; 95% confidence interval [CI], 0.31. 0.45; P= 5.5* 10(-26)], peripheral arterial disease (odds ratio 0.42; 95% CI, 0.26-0.68; P= 0.0005), and stroke (odds ratio, 0.53; 95% CI, 0.37-0.76; P= 0.0006). In a mediation analysis, the effect of the genetic score on decreased coronary heart disease risk extended beyond its effect on blood pressure. Conversely, rare variants that inactivate the NOS3 or GUCY1A3 genes were associated with a 23 mm Hg higher systolic blood pressure (95% CI, 12-34; P= 5.6* 10(-5)) and a 3-fold higher risk of coronary heart disease (odds ratio, 3.03; 95% CI, 1.29-7.12; P=0.01).CONCLUSIONS: A genetic predisposition to enhanced nitric oxide signaling is associated with reduced risks of coronary heart disease, peripheral arterial disease, and stroke. Pharmacological stimulation of nitric oxide signaling may prove useful in the prevention or treatment of cardiovascular disease.

Aortic aneurysms are morbid conditions that can lead to rupture or dissection and are categorized as thoracic (TAA) or abdominal aortic aneurysms (AAA) depending on their location. While AAA shares overlapping risk factors with atherosclerotic cardiovascular disease, TAA exhibits strong heritability. Human genetic studies in the past two decades have successfully identified numerous genes involved in both familial and sporadic forms of aortic aneurysm. In this review we will discuss the genetic basis of aortic aneurysm, focusing on the extracellular matrix and how insights from these studies have informed our understanding of human biology and disease pathogenesis. (C) 2018 Elsevier B.V. All rights reserved.

Purpose of review Human genetic studies have been successfully used to identify genes and pathways relevant to human biology. Using genetic instruments composed of loci associated with human lipid traits, recent studies have begun to clarify the causal role of major lipid fractions in risk of cardiometabolic disease.Recent findings The causal relationship between LDL cholesterol and coronary disease has been firmly established. Of the remaining two major fractions, recent studies have found that HDL cholesterol is not likely to be a causal particle in atherogenesis, and have instead shifted the causal focus to triglyceride-rich lipoproteins. Subsequent results are refining this view to suggest that triglycerides themselves might not be causal, but instead may be a surrogate for the causal cholesterol content within this fraction. Other studies have used a similar approach to address the association between lipid fractions and risk of type 2 diabetes. Beyond genetic variation in the target of statin medications, reduced LDL cholesterol associated with multiple genes encoding current or prospective drug targets associated with increased diabetic risk. In addition, genetically lower HDL cholesterol and genetically lower triglycerides both appear to increase risk of type 2 diabetes.Summary Results of these and future human genetic studies are positioned to provide substantive insights into the causal relationship between lipids and human disease, and should highlight mechanisms with important implications for our understanding of human biology and future lipid-altering therapeutic development.

Genetic association studies have a long history of delivering insightful results for cardiovascular disease (CVD) research. Beginning with early candidate gene studies, to genome-wide association studies, and now on to newer whole-genome sequencing studies, research in human genetics has enriched our understanding of the pathobiology of CVD. As these studies continue to expand, the issue of statistical power plays an important role in study design as well as the interpretation of results. We provide an overview of the component parts that determine statistical power and preview the future of CVD genetic association studies through this lens.

Identifying appropriate molecular targets is a critical step in drug development. Despite many advantages, the traditional tools of observational epidemiology and cellular or animal models of disease can be misleading in identifying causal pathways likely to lead to successful therapeutics. Here, we review some favorable aspects of human genetics studies that have the potential to accelerate drug target discovery. These include using genetic studies to identify pathways relevant to human disease, leveraging human genetics to discern causal relationships between biomarkers and disease, and studying genetic variation in humans to predict the potential efficacy and safety of inhibitory compounds aimed at molecular targets. We present some examples taken from studies of plasma lipids and coronary artery disease to highlight how human genetics can accelerate therapeutics development.

BACKGROUND: Relative risk reduction with statin therapy has been consistent across nearly all subgroups studied to date. However, in analyses of 2 randomized controlled primary prevention trials (ASCOT [Anglo-Scandinavian Cardiac Outcomes Trial-Lipid-Lowering Arm] and JUPITER [Justification for the Use of Statins in Prevention: An Intervention Trial Evaluating Rosuvastatin]), statin therapy led to a greater relative risk reduction among a subgroup at high genetic risk. Here, we aimed to confirm this observation in a third primary prevention randomized controlled trial. In addition, we assessed whether those at high genetic risk had a greater burden of subclinical coronary atherosclerosis.METHODS: We studied participants from a randomized controlled trial of primary prevention with statin therapy (WOSCOPS [West of Scotland Coronary Prevention Study]; n= 4910) and 2 observational cohort studies (CARDIA [Coronary Artery Risk Development in Young Adults] and BioImage; n= 1154 and 4392, respectively). For each participant, we calculated a polygenic risk score derived from up to 57 common DNA sequence variants previously associated with coronary heart disease. We compared the relative efficacy of statin therapy in those at high genetic risk (top quintile of polygenic risk score) versus all others (WOSCOPS), as well as the association between the polygenic risk score and coronary artery calcification (CARDIA) and carotid artery plaque burden (BioImage).RESULTS: Among WOSCOPS trial participants at high genetic risk, statin therapy was associated with a relative risk reduction of 44% (95% confidence interval [CI], 22-60; P< 0.001), whereas in all others, the relative risk reduction was 24% (95% CI, 8-37; P= 0.004) despite similar low-density lipoprotein cholesterol lowering. In a study-level meta-analysis across the WOSCOPS, ASCOT, and JUPITER primary prevention, relative risk reduction in those at high genetic risk was 46% versus 26% in all others (P for heterogeneity= 0.05). Across all 3 studies, the absolute risk reduction with statin therapy was 3.6% (95% CI, 2.0-5.1) among those in the high genetic risk group and 1.3% (95% CI, 0.6-1.9) in all others. Each 1-SD increase in the polygenic risk score was associated with 1.32-fold (95% CI, 1.04-1.68) greater likelihood of having coronary artery calcification and 9.7% higher (95% CI, 2.2-17.8) burden of carotid plaque.CONCLUSIONS: Those at high genetic risk have a greater burden of subclinical atherosclerosis and derive greater relative and absolute benefit from statin therapy to prevent a first coronary heart disease event.

BACKGROUND Genomic analyses have suggested that the LPA gene and its associated plasma biomarker, lipoprotein(a) (Lp[a]), represent a causal risk factor for coronary heart disease (CHD). As such, lowering Lp(a) levels has emerged as a therapeutic strategy. Beyond target identification, human genetics may contribute to the development of new therapies by defining the full spectrum of beneficial and adverse consequences and by developing a dose-response curve of target perturbation. OBJECTIVES The goal of this study was to establish the full phenotypic impact of LPA gene variation and to estimate a dose-response curve between genetically altered plasma Lp(a) and risk for CHD. METHODS We leveraged genetic variants at the LPA gene from 3 data sources: individual-level data from 112,338 participants in the U.K. Biobank; summary association results from large-scale genome-wide association studies; and LPA gene sequencing results from case subjects with CHD and control subjects free of CHD. RESULTS One SD genetically lowered Lp(a) level was associated with a 29% lower risk of CHD (odds ratio [OR]: 0.71; 95% confidence interval [CI]: 0.69 to 0.73), a 31% lower risk of peripheral vascular disease (OR: 0.69; 95% CI: 0.59 to 0.80), a 13% lower risk of stroke (OR: 0.87; 95% CI: 0.79 to 0.96), a 17% lower risk of heart failure (OR: 0.83; 95% CI: 0.73 to 0.94), and a 37% lower risk of aortic stenosis (OR: 0.63; 95% CI: 0.47 to 0.83). We observed no association with 31 other disorders, including type 2 diabetes and cancer. Variants that led to gain of LPA gene function increased the risk for CHD, whereas those that led to loss of gene function reduced the CHD risk. CONCLUSIONS Beyond CHD, genetically lowered Lp(a) levels are associated with a lower risk of peripheral vascular disease, stroke, heart failure, and aortic stenosis. As such, pharmacological lowering of plasma Lp(a) may influence a range of atherosclerosis-related diseases. (C) 2016 by the American College of Cardiology Foundation.