Prioritising genetic findings for drug target identification and validation.

The decreasing costs of high-throughput genetic sequencing and increasing abundance of sequenced genome data have paved the way for the use of genetic data in identifying and validating potential drug targets. However, the number of identified potential drug targets is often prohibitively large to experimentally evaluate in wet lab experiments, highlighting the need for systematic approaches for target prioritisation. In this review, we discuss principles of genetically guided drug development, specifically addressing loss-of-function analysis, colocalization and Mendelian randomisation (MR), and the contexts in which each may be most suitable. We subsequently present a range of biomedical resources which can be used to annotate and prioritise disease-associated proteins identified by these studies including 1) ontologies to map genes, proteins, and disease, 2) resources for determining the druggability of a potential target, 3) tissue and cell expression of the gene encoding the potential target, and 4) key biological pathways involving the potential target. We illustrate these concepts through a worked example, identifying a prioritised set of plasma proteins associated with non-alcoholic fatty liver disease (NAFLD). We identified five proteins with strong genetic support for involvement with NAFLD: CYB5A, NT5C, NCAN, TGFBI and DAPK2. All of the identified proteins were expressed in both liver and adipose tissues, with TGFBI and DAPK2 being potentially druggable. In conclusion, the current review provides an overview of genetic evidence for drug target identification, and how biomedical databases can be used to provide actionable prioritisation, fully informing downstream experimental validation.

Penetrance and Prognosis of MYH7 Variant-Associated Cardiomyopathies: Results From a Dutch Multicenter Cohort Study.

BACKGROUND: MYH7 variants cause hypertrophic cardiomyopathy (HCM), noncompaction cardiomyopathy (NCCM), and dilated cardiomyopathy (DCM). Screening of relatives of patients with genetic cardiomyopathy is recommended from 10 to 12 years of age onward, irrespective of the affected gene. OBJECTIVES: This study sought to study the penetrance and prognosis of MYH7 variant-associated cardiomyopathies. METHODS: In this multicenter cohort study, penetrance and major cardiomyopathy-related events (MCEs) were assessed in carriers of (likely) pathogenic MYH7 variants by using Kaplan-Meier curves and log-rank tests. Prognostic factors were evaluated using Cox regression with time-dependent coefficients. RESULTS: In total, 581 subjects (30.1% index patients, 48.4% male, median age 37.0 years [IQR: 19.5-50.2 years]) were included. HCM was diagnosed in 226 subjects, NCCM in 70, and DCM in 55. Early penetrance and MCEs (age <12 years) were common among NCCM-associated variant carriers (21.2% and 12.0%, respectively) and DCM-associated variant carriers (15.3% and 10.0%, respectively), compared with HCM-associated variant carriers (2.9% and 2.1%, respectively). Penetrance was significantly increased in carriers of converter region variants (adjusted HR: 1.87; 95% CI: 1.15-3.04; P = 0.012) and at age ≤1 year in NCCM-associated or DCM-associated variant carriers (adjusted HR: 21.17; 95% CI: 4.81-93.20; P < 0.001) and subjects with a family history of early MCEs (adjusted HR: 2.45; 95% CI: 1.09-5.50; P = 0.030). The risk of MCE was increased in subjects with a family history of early MCEs (adjusted HR: 1.82; 95% CI: 1.15-2.87; P = 0.010) and at age ≤5 years in NCCM-associated or DCM-associated variant carriers (adjusted HR: 38.82; 95% CI: 5.16-291.88; P < 0.001). CONCLUSIONS: MYH7 variants can cause cardiomyopathies and MCEs at a young age. Screening at younger ages may be warranted, particularly in carriers of NCCM- or DCM-associated variants and/or with a family history of MCEs at <12 years.

Unraveling the relationships between alpha- and beta-adrenergic modulation and the risk of heart failure.

Background: The effects of α and ß adrenergic receptor modulation on the risk of developing heart failure (HF) remains uncertain due to a lack of randomized controlled trials. This study aimed to estimate the effects of α and ß adrenergic receptors modulation on the risk of HF and to provide proof of principle for genetic target validation studies in HF. Methods: Genetic variants within the cis regions encoding the adrenergic receptors α1A, α2B, ß1, and ß2 associated with blood pressure in a 757,601-participant genome-wide association study (GWAS) were selected as instruments to perform a drug target Mendelian randomization study. Effects of these variants on HF risk were derived from the HERMES GWAS (542,362 controls; 40,805 HF cases). Results: Lower α1A or ß1 activity was associated with reduced HF risk: odds ratio (OR) 0.83 (95% CI 0.74-0.93, P = 0.001) and 0.95 (95% CI 0.93-0.97, P = 8 × 10-6). Conversely, lower α2B activity was associated with increased HF risk: OR 1.09 (95% CI 1.05-1.12, P = 3 × 10-7). No evidence of an effect of lower ß2 activity on HF risk was found: OR 0.99 (95% CI 0.92-1.07, P = 0.95). Complementary analyses showed that these effects were consistent with those on left ventricular dimensions and acted independently of any potential effect on coronary artery disease. Conclusions: This study provides genetic evidence that α1A or ß1 receptor inhibition will likely decrease HF risk, while lower α2B activity may increase this risk. Genetic variant analysis can assist with drug development for HF prevention.

Triangulating evidence from observational and Mendelian randomization studies of ketone bodies for cognitive performance.

BACKGROUND: Ketone bodies (KBs) are an alternative energy supply for brain functions when glucose is limited. The most abundant ketone metabolite, 3-ß-hydroxybutyrate (BOHBUT), has been suggested to prevent or delay cognitive impairment, but the evidence remains unclear. We triangulated observational and Mendelian randomization (MR) studies to investigate the association and causation between KBs and cognitive function. METHODS: In observational analyses of 5506 participants aged ≥ 45 years from the Whitehall II study, we used multiple linear regression to investigate the associations between categorized KBs and cognitive function scores. Two-sample MR was carried out using summary statistics from an in-house KBs meta-analysis between the University College London-London School of Hygiene and Tropical Medicine-Edinburgh-Bristol (UCLEB) Consortium and Kettunen et al. (N = 45,031), and publicly available summary statistics of cognitive performance and Alzheimer's disease (AD) from the Social Science Genetic Association Consortium (N = 257,841), and the International Genomics of Alzheimer's Project (N = 54,162), respectively. Both strong (P < 5 × 10-8) and suggestive (P < 1 × 10-5) sets of instrumental variables for BOHBUT were applied. Finally, we performed cis-MR on OXCT1, a well-known gene for KB catabolism. RESULTS: BOHBUT was positively associated with general cognitive function (ß = 0.26, P = 9.74 × 10-3). In MR analyses, we observed a protective effect of BOHBUT on cognitive performance (inverse variance weighted: ßIVW = 7.89 × 10-2, PIVW = 1.03 × 10-2; weighted median: ßW-Median = 8.65 × 10-2, PW-Median = 9.60 × 10-3) and a protective effect on AD (ßIVW = - 0.31, odds ratio: OR = 0.74, PIVW = 3.06 × 10-2). Cis-MR showed little evidence of therapeutic modulation of OXCT1 on cognitive impairment. CONCLUSIONS: Triangulation of evidence suggests that BOHBUT has a beneficial effect on cognitive performance. Our findings raise the hypothesis that increased BOHBUT may improve general cognitive functions, delaying cognitive impairment and reducing the risk of AD.

Exploring the Role of Plasma Lipids and Statin Interventions on Multiple Sclerosis Risk and Severity: A Mendelian Randomization Study.

BACKGROUND AND OBJECTIVES: There has been considerable interest in statins because of their pleiotropic effects beyond their lipid-lowering properties. Many of these pleiotropic effects are predominantly ascribed to Rho small guanosine triphosphatases (Rho GTPases) proteins. We aimed to genetically investigate the role of lipids and statin interventions on multiple sclerosis (MS) risk and severity. METHOD: We used two-sample Mendelian randomization (MR) to investigate (1) the causal role of genetically mimic both cholesterol-dependent (through low-density lipoprotein cholesterol (LDL-C) and cholesterol biosynthesis pathway) and cholesterol-independent (through Rho GTPases) effects of statins on MS risk and MS severity, (2) the causal link between lipids (high-density lipoprotein cholesterol [HDL-C] and triglycerides [TG]) levels and MS risk and severity, and (3) the reverse causation between lipid fractions and MS risk. We used summary statistics from the Global Lipids Genetics Consortium (GLGC), eQTLGen Consortium, and the International MS Genetics Consortium (IMSGC) for lipids, expression quantitative trait loci, and MS, respectively (GLGC: n = 188,577; eQTLGen: n = 31,684; IMSGC (MS risk): n = 41,505; IMSGC (MS severity): n = 7,069). RESULTS: The results of MR using the inverse-variance weighted method show that genetically predicted RAC2, a member of cholesterol-independent pathway (OR 0.86 [95% CI 0.78-0.95], p-value 3.80E-03), is implicated causally in reducing MS risk. We found no evidence for the causal role of LDL-C and the member of cholesterol biosynthesis pathway on MS risk. The MR results also show that lifelong higher HDL-C (OR 1.14 [95% CI 1.04-1.26], p-value 7.94E-03) increases MS risk but TG was not. Furthermore, we found no evidence for the causal role of lipids and genetically mimicked statins on MS severity. There is no evidence of reverse causation between MS risk and lipids. DISCUSSION: Evidence from this study suggests that RAC2 is a genetic modifier of MS risk. Because RAC2 has been reported to mediate some of the pleiotropic effects of statins, we suggest that statins may reduce MS risk through a cholesterol-independent pathway (that is, RAC2-related mechanism(s)). MR analyses also support a causal effect of HDL-C on MS risk.

Druggable proteins influencing cardiac structure and function: Implications for heart failure therapies and cancer cardiotoxicity.

Dysfunction of either the right or left ventricle can lead to heart failure (HF) and subsequent morbidity and mortality. We performed a genome-wide association study (GWAS) of 16 cardiac magnetic resonance (CMR) imaging measurements of biventricular function and structure. Cis-Mendelian randomization (MR) was used to identify plasma proteins associating with CMR traits as well as with any of the following cardiac outcomes: HF, non-ischemic cardiomyopathy, dilated cardiomyopathy (DCM), atrial fibrillation, or coronary heart disease. In total, 33 plasma proteins were prioritized, including repurposing candidates for DCM and/or HF: IL18R (providing indirect evidence for IL18), I17RA, GPC5, LAMC2, PA2GA, CD33, and SLAF7. In addition, 13 of the 25 druggable proteins (52%; 95% confidence interval, 0.31 to 0.72) could be mapped to compounds with known oncological indications or side effects. These findings provide leads to facilitate drug development for cardiac disease and suggest that cardiotoxicities of several cancer treatments might represent mechanism-based adverse effects.

Individualized Family Screening for Arrhythmogenic Right Ventricular Cardiomyopathy.

BACKGROUND: Clinical guidelines recommend regular screening for arrhythmogenic right ventricular cardiomyopathy (ARVC) to monitor at-risk relatives, resulting in a significant burden on clinical resources. Prioritizing relatives on their probability of developing definite ARVC may provide more efficient patient care. OBJECTIVES: The aim of this study was to determine the predictors and probability of ARVC development over time among at-risk relatives. METHODS: A total of 136 relatives (46% men, median age 25.5 years [IQR: 15.8-44.4 years]) from the Netherlands Arrhythmogenic Cardiomyopathy Registry without definite ARVC by 2010 task force criteria were included. Phenotype was ascertained using electrocardiography, Holter monitoring, and cardiac imaging. Subjects were divided into groups with "possible ARVC" (only genetic or familial predisposition) and "borderline ARVC" (1 minor task force criterion plus genetic or familial predisposition). Cox regression was performed to determine predictors and multistate modeling to assess the probability of ARVC development. Results were replicated in an unrelated Italian cohort (57% men, median age 37.0 years [IQR: 25.4-50.4 years]). RESULTS: At baseline, 93 subjects (68%) had possible ARVC, and 43 (32%) had borderline ARVC. Follow-up was available for 123 relatives (90%). After 8.1 years (IQR: 4.2-11.4 years), 41 (33%) had developed definite ARVC. Independent of baseline phenotype, symptomatic subjects (P = 0.014) and those 20 to 30 years of age (P = 0.002) had a higher hazard of developing definite ARVC. Furthermore, patients with borderline ARVC had a higher probability of developing definite ARVC compared with those with possible ARVC (1-year probability 13% vs 0.6%, 3-year probability 35% vs 5%; P < 0.01). External replication showed comparable results (P > 0.05). CONCLUSIONS: Symptomatic relatives, those 20 to 30 years of age, and those with borderline ARVC have a higher probability of developing definite ARVC. These patients may benefit from more frequent follow-up, while others may be monitored less often.

Untargeted Metabolomics Identifies Potential Hypertrophic Cardiomyopathy Biomarkers in Carriers of MYBPC3 Founder Variants.

Hypertrophic cardiomyopathy (HCM) is the most prevalent monogenic heart disease, commonly caused by pathogenic MYBPC3 variants, and a significant cause of sudden cardiac death. Severity is highly variable, with incomplete penetrance among genotype-positive family members. Previous studies demonstrated metabolic changes in HCM. We aimed to identify metabolite profiles associated with disease severity in carriers of MYBPC3 founder variants using direct-infusion high-resolution mass spectrometry in plasma of 30 carriers with a severe phenotype (maximum wall thickness ≥20 mm, septal reduction therapy, congestive heart failure, left ventricular ejection fraction <50%, or malignant ventricular arrhythmia) and 30 age- and sex-matched carriers with no or a mild phenotype. Of the top 25 mass spectrometry peaks selected by sparse partial least squares discriminant analysis, XGBoost gradient boosted trees, and Lasso logistic regression (42 total), 36 associated with severe HCM at a p < 0.05, 20 at p < 0.01, and 3 at p < 0.001. These peaks could be clustered to several metabolic pathways, including acylcarnitine, histidine, lysine, purine and steroid hormone metabolism, and proteolysis. In conclusion, this exploratory case-control study identified metabolites associated with severe phenotypes in MYBPC3 founder variant carriers. Future studies should assess whether these biomarkers contribute to HCM pathogenesis and evaluate their contribution to risk stratification.

Biomedical consequences of elevated cholesterol-containing lipoproteins and apolipoproteins on cardiovascular and non-cardiovascular outcomes.

BACKGROUND: Higher concentrations of cholesterol-containing low-density lipoprotein (LDL-C) increase the risk of cardiovascular disease (CVD). The association of LDL-C with non-CVD traits remains unclear, as are the possible independent contributions of other cholesterol-containing lipoproteins and apolipoproteins. METHODS: Nuclear magnetic resonance spectroscopy was used to measure the cholesterol content of high density (HDL-C), very low-density (VLDL-C), intermediate-density (IDL-C), as well as low-density lipoprotein fractions, the apolipoproteins Apo-A1 and Apo-B, as well as total triglycerides (TG), remnant-cholesterol (Rem-Chol) and total cholesterol (TC). The causal effects of these exposures were assessed against 33 outcomes using univariable and multivariable Mendelian randomization (MR). RESULTS: The majority of cholesterol containing lipoproteins and apolipoproteins affect coronary heart disease (CHD), carotid intima-media thickness, carotid plaque, C-reactive protein (CRP) and blood pressure. Multivariable MR indicated that many of these effects act independently of HDL-C, LDL-C and TG, the most frequently measured lipid fractions. Higher concentrations of TG, VLDL-C, Rem-Chol and Apo-B increased heart failure (HF) risk; often independently of LDL-C, HDL-C or TG. Finally, a subset of these exposures associated with non-CVD traits such as Alzheimer's disease (AD: HDL-C, LDL-C, IDL-C, Apo-B), type 2 diabetes (T2DM: VLDL-C, IDL-C, LDL-C), and inflammatory bowel disease (IBD: LDL-C, IDL-C). CONCLUSIONS: The cholesterol content of a wide range of lipoprotein and apolipoproteins associate with measures of atherosclerosis, blood pressure, CRP, and CHD, with a subset affecting HF, T2DM, AD and IBD risk. Many of the observed effects appear to act independently of LDL-C, HDL-C, and TG, supporting the targeting of lipid fractions beyond LDL-C for disease prevention.

It is known that increases in the amount of certain fats and proteins in the blood can lead to heart attacks. These increases are also found in people with other diseases. Here, we looked at inherited differences in some fats and proteins in blood to explore whether these could be associated with various diseases. We found that some fats and proteins in blood were associated with heart disease (including heart failure), blood pressure, blockages in blood vessels, and to a lesser extent with diabetes, Alzheimer's disease, and inflammatory bowel disease. These findings suggest that changes to lipids and proteins in the blood might lead to various diseases, including some that are not normally associated with changes in the blood. Monitoring these changes could improve diagnosis and treatment of these diseases.

Joint Genetic Inhibition of PCSK9 and CETP and the Association With Coronary Artery Disease: A Factorial Mendelian Randomization Study.

Importance: Cholesteryl ester transfer protein inhibition (CETP) has been shown to increase levels of high-density lipoprotein cholesterol (HDL-C) and reduce levels of low-density lipoprotein cholesterol (LDL-C). Current LDL-C target attainment is low, and novel phase 3 trials are underway to investigate whether CETP inhibitors result in reduction of cardiovascular disease risk in high-risk patients who may be treated with PCSK9-inhibiting agents. Objective: To explore the associations of combined reduction of CETP and PCSK9 concentrations with risk of coronary artery disease (CAD) and other clinical and safety outcomes. Design, Setting, and Participants: Two-sample 2 × 2 factorial Mendelian randomization study in a general population sample that includes data for UK Biobank participants of European ancestry. Exposures: Separate genetic scores were constructed for CETP and PCSK9 plasma protein concentrations, which were combined to determine the associations of combined genetically reduced CETP and PCSK9 concentrations with disease. Main Outcomes and Measures: Blood lipid and lipoprotein concentrations, blood pressure, CAD, age-related macular degeneration, type 2 diabetes, any stroke and ischemic stroke, Alzheimer disease, vascular dementia, heart failure, atrial fibrillation, chronic kidney disease, asthma, and multiple sclerosis. Results: Data for 425 354 UKB participants were included; the median (IQR) age was 59 years (51-64), and 229 399 (53.9%) were female. The associations of lower CETP and lower PCSK9 concentrations with CAD are similar when scaled per 10-mg/dL reduction in LDL-C concentrations (CETP: odds ratio [OR], 0.74; 95% CI, 0.67 to 0.81; PCSK9: OR, 0.75; 95% CI, 0.71 to 0.79). Combined exposure to lower CETP and PCSK9 concentrations was associated with an additive magnitude with lipids and all outcomes, and we did not observe any nonadditive interactions, most notably for LDL-C (CETP: effect size, -1.11 mg/dL; 95% CI, -1.40 to -0.82; PCSK9: effect size, -2.13 mg/dL; 95% CI, -2.43 to -1.84; combined: effect size, -3.47 mg/dL; 95% CI, -3.76 to -3.18; P = .34 for interaction) and CAD (CETP: OR, 0.96; 95% CI, 0.94 to 1.00; PCSK9: OR, 0.94; 95% CI, 0.91 to 0.97; combined: OR, 0.90; 95% CI, 0.87 to 0.93; P = .83 for interaction). In addition, when corrected for multiple testing, lower CETP concentrations were associated with increased age-related macular degeneration (OR, 1.11; 95% CI, 1.04 to 1.19). Conclusions and Relevance: Our results suggest that joint inhibition of CETP and PCSK9 has additive effects on lipid traits and disease risk, including a lower risk of CAD. Further research may explore whether a combination of CETP- and PCSK9-related therapeutics can benefit high-risk patients who are unable to reach treatment targets with existing options.

Unravelling the Difference Between Men and Women in Post-CABG Survival.

Objectives: Women have a worse prognosis after coronary artery bypass grafting (CABG) surgery compared to men. We sought to quantify to what extent this difference in post-CABG survival could be attributed to sex itself, or whether this was mediated by difference between men and women at the time of intervention. Additionally, we explored to what extent these effects were homogenous across patient subgroups. Methods: Time to all-cause mortality was available for 102,263 CABG patients, including 20,988 (21%) women, sourced through an individual participant data meta-analysis of five cohort studies. Difference between men and women in survival duration was assessed using Kaplan-Meier estimates, and Cox's proportional hazards model. Results: During a median follow-up of 5 years, 13,598 (13%) patients died, with women more likely to die than men: female HR 1.20 (95%CI 1.16; 1.25). We found that differences in patient characteristics at the time of CABG procedure mediated this sex effect, and accounting for these resulted in a neutral female HR 0.98 (95%CI 0.94; 1.02). Next we performed a priori defined subgroup analyses of the five most prominent mediators: age, creatinine, peripheral vascular disease, type 2 diabetes, and heart failure. We found that women without peripheral vascular disease (PVD) or women aged 70+, survived longer than men (interaction p-values 0.04 and 6 × 10-5, respectively), with an effect reversal in younger women. Conclusion: Sex differences in post-CABG survival were readily explained by difference in patient characteristics and comorbidities. Pre-planned analyses revealed patient subgroups (aged 70+, or without PVD) of women that survived longer than men, and a subgroup of younger women with comparatively poorer survival.

Therapeutic Targets for Heart Failure Identified Using Proteomics and Mendelian Randomization.

BACKGROUND: Heart failure (HF) is a highly prevalent disorder for which disease mechanisms are incompletely understood. The discovery of disease-associated proteins with causal genetic evidence provides an opportunity to identify new therapeutic targets. METHODS: We investigated the observational and causal associations of 90 cardiovascular proteins, which were measured using affinity-based proteomic assays. First, we estimated the associations of 90 cardiovascular proteins with incident heart failure by means of a fixed-effect meta-analysis of 4 population-based studies, composed of a total of 3019 participants with 732 HF events. The causal effects of HF-associated proteins were then investigated by Mendelian randomization, using cis-protein quantitative loci genetic instruments identified from genomewide association studies in more than 30 000 individuals. To improve the precision of causal estimates, we implemented an Mendelian randomization model that accounted for linkage disequilibrium between instruments and tested the robustness of causal estimates through a multiverse sensitivity analysis that included up to 120 combinations of instrument selection parameters and Mendelian randomization models per protein. The druggability of candidate proteins was surveyed, and mechanism of action and potential on-target side effects were explored with cross-trait Mendelian randomization analysis. RESULTS: Forty-four of ninety proteins were positively associated with risk of incident HF (P<6.0×10-4). Among these, 8 proteins had evidence of a causal association with HF that was robust to multiverse sensitivity analysis: higher CSF-1 (macrophage colony-stimulating factor 1), Gal-3 (galectin-3) and KIM-1 (kidney injury molecule 1) were positively associated with risk of HF, whereas higher ADM (adrenomedullin), CHI3L1 (chitinase-3-like protein 1), CTSL1 (cathepsin L1), FGF-23 (fibroblast growth factor 23), and MMP-12 (matrix metalloproteinase-12) were protective. Therapeutics targeting ADM and Gal-3 are currently under evaluation in clinical trials, and all the remaining proteins were considered druggable, except KIM-1. CONCLUSIONS: We identified 44 circulating proteins that were associated with incident HF, of which 8 showed evidence of a causal relationship and 7 were druggable, including adrenomedullin, which represents a particularly promising drug target. Our approach demonstrates a tractable roadmap for the triangulation of population genomic and proteomic data for the prioritization of therapeutic targets for complex human diseases.

Cardiovascular risk prediction in type 2 diabetes: a comparison of 22 risk scores in primary care settings.

AIMS/HYPOTHESIS: We aimed to compare the performance of risk prediction scores for CVD (i.e., coronary heart disease and stroke), and a broader definition of CVD including atrial fibrillation and heart failure (CVD+), in individuals with type 2 diabetes. METHODS: Scores were identified through a literature review and were included irrespective of the type of predicted cardiovascular outcome or the inclusion of individuals with type 2 diabetes. Performance was assessed in a contemporary, representative sample of 168,871 UK-based individuals with type 2 diabetes (age ≥18 years without pre-existing CVD+). Missing observations were addressed using multiple imputation. RESULTS: We evaluated 22 scores: 13 derived in the general population and nine in individuals with type 2 diabetes. The Systemic Coronary Risk Evaluation (SCORE) CVD rule derived in the general population performed best for both CVD (C statistic 0.67 [95% CI 0.67, 0.67]) and CVD+ (C statistic 0.69 [95% CI 0.69, 0.70]). The C statistic of the remaining scores ranged from 0.62 to 0.67 for CVD, and from 0.64 to 0.69 for CVD+. Calibration slopes (1 indicates perfect calibration) ranged from 0.38 (95% CI 0.37, 0.39) to 0.74 (95% CI 0.72, 0.76) for CVD, and from 0.41 (95% CI 0.40, 0.42) to 0.88 (95% CI 0.86, 0.90) for CVD+. A simple recalibration process considerably improved the performance of the scores, with calibration slopes now ranging between 0.96 and 1.04 for CVD. Scores with more predictors did not outperform scores with fewer predictors: for CVD+, QRISK3 (19 variables) had a C statistic of 0.68 (95% CI 0.68, 0.69), compared with SCORE CVD (six variables) which had a C statistic of 0.69 (95% CI 0.69, 0.70). Scores specific to individuals with diabetes did not discriminate better than scores derived in the general population: the UK Prospective Diabetes Study (UKPDS) scores performed significantly worse than SCORE CVD (p value <0.001). CONCLUSIONS/INTERPRETATION: CVD risk prediction scores could not accurately identify individuals with type 2 diabetes who experienced a CVD event in the 10 years of follow-up. All 22 evaluated models had a comparable and modest discriminative ability.

Assessment of practical applicability and clinical relevance of a commonly used LDL-C polygenic score in patients with severe hypercholesterolemia.

BACKGROUND AND AIMS: Low-density lipoprotein cholesterol (LDL-C) levels vary in patients with familial hypercholesterolemia (FH) and can be explained by a single deleterious genetic variant or by the aggregate effect of multiple, common small-effect variants that can be captured in a polygenic score (PS). We set out to investigate the contribution of a previously published PS to the inter-individual LDL-C variation and coronary artery disease (CAD) risk in patients with a clinical FH phenotype. METHODS: First, in a cohort of 628 patients referred for genetic FH testing, we evaluated the distribution of a PS for LDL-C comprising 12 genetic variants. Next, we determined its association with coronary artery disease (CAD) risk using UK Biobank data. RESULTS: The mean PS was higher in 533 FH-variant-negative patients (FH/M-) compared with 95 FH-variant carriers (1.02 vs 0.94, p < 0.001). 39% of all patients had a PS equal to the top 20% from a population-based reference cohort and these patients were less likely to carry an FH variant (OR 0.22, 95% CI 0.10-0.48) compared with patients in the lowest 20%. In UK Biobank data, the PS explained 7.4% of variance in LDL-C levels and was associated with incident CAD. Addition of PS to a prediction model using age and sex and LDL-C did not increase the c-statistic for predicting CAD risk. CONCLUSIONS: This 12-variant PS was higher in FH/M- patients and associated with incident CAD in UK Biobank data. However, the PS did not improve predictive accuracy when added to the readily available characteristics age, sex and LDL-C, suggesting limited discriminative value for CAD.

Human Genomics and Drug Development.

Insights into the genetic basis of human disease are helping to address some of the key challenges in new drug development including the very high rates of failure. Here we review the recent history of an emerging, genomics-assisted approach to pharmaceutical research and development, and its relationship to Mendelian randomization (MR), a well-established analytical approach to causal inference. We demonstrate how human genomic data linked to pharmaceutically relevant phenotypes can be used for (1) drug target identification (mapping relevant drug targets to diseases), (2) drug target validation (inferring the likely effects of drug target perturbation), (3) evaluation of the effectiveness and specificity of compound-target engagement (inferring the extent to which the effects of a compound are exclusive to the target and distinguishing between on-target and off-target compound effects), and (4) the selection of end points in clinical trials (the diseases or conditions to be evaluated as trial outcomes). We show how genomics can help identify indication expansion opportunities for licensed drugs and repurposing of compounds developed to clinical phase that proved safe but ineffective for the original intended indication. We outline statistical and biological considerations in using MR for drug target validation (drug target MR) and discuss the obstacles and challenges for scaled applications of these genomics-based approaches.

Validation of lipid-related therapeutic targets for coronary heart disease prevention using human genetics.

Drug target Mendelian randomization (MR) studies use DNA sequence variants in or near a gene encoding a drug target, that alter the target's expression or function, as a tool to anticipate the effect of drug action on the same target. Here we apply MR to prioritize drug targets for their causal relevance for coronary heart disease (CHD). The targets are further prioritized using independent replication, co-localization, protein expression profiles and data from the British National Formulary and clinicaltrials.gov. Out of the 341 drug targets identified through their association with blood lipids (HDL-C, LDL-C and triglycerides), we robustly prioritize 30 targets that might elicit beneficial effects in the prevention or treatment of CHD, including NPC1L1 and PCSK9, the targets of drugs used in CHD prevention. We discuss how this approach can be generalized to other targets, disease biomarkers and endpoints to help prioritize and validate targets during the drug development process.

Cholesteryl ester transfer protein (CETP) as a drug target for cardiovascular disease.

Development of cholesteryl ester transfer protein (CETP) inhibitors for coronary heart disease (CHD) has yet to deliver licensed medicines. To distinguish compound from drug target failure, we compared evidence from clinical trials and drug target Mendelian randomization of CETP protein concentration, comparing this to Mendelian randomization of proprotein convertase subtilisin/kexin type 9 (PCSK9). We show that previous failures of CETP inhibitors are likely compound related, as illustrated by significant degrees of between-compound heterogeneity in effects on lipids, blood pressure, and clinical outcomes observed in trials. On-target CETP inhibition, assessed through Mendelian randomization, is expected to reduce the risk of CHD, heart failure, diabetes, and chronic kidney disease, while increasing the risk of age-related macular degeneration. In contrast, lower PCSK9 concentration is anticipated to decrease the risk of CHD, heart failure, atrial fibrillation, chronic kidney disease, multiple sclerosis, and stroke, while potentially increasing the risk of Alzheimer's disease and asthma. Due to distinct effects on lipoprotein metabolite profiles, joint inhibition of CETP and PCSK9 may provide added benefit. In conclusion, we provide genetic evidence that CETP is an effective target for CHD prevention but with a potential on-target adverse effect on age-related macular degeneration.

No Clinically Relevant Effect of Heart Rate Increase and Heart Rate Recovery During Exercise on Cardiovascular Disease: A Mendelian Randomization Analysis.

BACKGROUND: Reduced heart rate (HR) increase (HRI), recovery (HRR), and higher resting HR are associated with cardiovascular (CV) disease, but causal inferences have not been deduced. We investigated causal effects of HRI, HRR, and resting HR on CV risk, all-cause mortality (ACM), atrial fibrillation (AF), coronary artery disease (CAD), and ischemic stroke (IS) using Mendelian Randomization. METHODS: 11 variants for HRI, 11 for HRR, and two sets of 46 and 414 variants for resting HR were obtained from four genome-wide association studies (GWASs) on UK Biobank. We performed a lookup on GWASs for CV risk and ACM in UK Biobank (N = 375,367, 5.4% cases and N = 393,165, 4.4% cases, respectively). For CAD, AF, and IS, we used publicly available summary statistics. We used a random-effects inverse-variance weighted (IVW) method and sensitivity analyses to estimate causality. RESULTS: IVW showed a nominally significant effect of HRI on CV events (odds ratio [OR] = 1.0012, P = 4.11 × 10-2) and on CAD and AF. Regarding HRR, IVW was not significant for any outcome. The IVW method indicated statistically significant associations of resting HR with AF (OR = 0.9825, P = 9.8 × 10-6), supported by all sensitivity analyses, and a nominally significant association with IS (OR = 0.9926, P = 9.82 × 10-3). CONCLUSION: Our findings suggest no strong evidence of an association between HRI and HRR and any outcome and confirm prior work reporting a highly significant effect of resting HR on AF. Future research is required to explore HRI and HRR associations further using more powerful predictors, when available.