Pharmacotherapy for children with elevated levels of lipoprotein(a): future directions.

INTRODUCTION: Elevated lipoprotein(a) [Lp(a)] is an independent risk factor for atherosclerotic cardiovascular disease (ASCVD). With the advent of the antisense oligonucleotides (ASOs) and small interfering RNAs (siRNAs) targeted at LPA, that are highly effective for lowering Lp(a) levels, this risk factor might be managed in the near future. Given that Lp(a) levels are mostly genetically determined and once elevated, present from early age, we have evaluated future directions for the treatment of children with high Lp(a) levels. AREAS COVERED: In the current review, we discuss different pharmacological treatments in clinical development and provide an in-depth overview of the effects of ASOs and siRNAs targeted at LPA. EXPERT OPINION: Since high Lp(a) is an important risk factor for ASCVD and given the promising effects of both ASOs and siRNAs targeted at apo(a), there is an urgent need for well-designed prospective studies to assess the impact of elevated Lp(a) in childhood. If the Lp(a)-hypothesis is confirmed in adults, and also in children, the rationale might arise for treating children with high Lp(a) levels. However, we feel that this should be limited to children with the highest cardiovascular risk including familial hypercholesterolemia and potentially pediatric stroke.

Single Ascending Dose Study of a Short Interfering RNA Targeting Lipoprotein(a) Production in Individuals With Elevated Plasma Lipoprotein(a) Levels.

Importance: Lipoprotein(a) (Lp[a]) is an important risk factor for atherothrombotic cardiovascular disease and aortic stenosis, for which there are no treatments approved by regulatory authorities. Objectives: To assess adverse events and tolerability of a short interfering RNA (siRNA) designed to reduce hepatic production of apolipoprotein(a) and to assess associated changes in plasma concentrations of Lp(a) at different doses. Design, Setting, and Participants: A single ascending dose study of SLN360, an siRNA targeting apolipoprotein(a) synthesis conducted at 5 clinical research unit sites located in the US, United Kingdom, and Australia. The study enrolled adults with Lp(a) plasma concentrations of 150 nmol/L or greater at screening and no known clinically overt cardiovascular disease. Participants were enrolled between November 18, 2020, and July 21, 2021, with last follow-up on December 29, 2021. Interventions: Participants were randomized to receive placebo (n = 8) or single doses of SLN360 at 30 mg (n = 6), 100 mg (n = 6), 300 mg (n = 6), or 600 mg (n = 6), administered subcutaneously. Main Outcomes and Measures: The primary outcome was evaluation of safety and tolerability. Secondary outcomes included change in plasma concentrations of Lp(a) to a maximum follow-up of 150 days. Results: Among 32 participants who were randomized and received the study intervention (mean age, 50 [SD, 13.5] years; 17 women [53%]), 32 (100%) completed the trial. One participant experienced 2 serious adverse event episodes: admission to the hospital for headache following SARS-CoV-2 vaccination and later for complications of cholecystitis, both of which were judged to be unrelated to study drug. Median baseline Lp(a) concentrations were as follows: placebo, 238 (IQR, 203-308) nmol/L; 30-mg SLN360, 171 (IQR, 142-219) nmol/L; 100-mg SLN360, 217 (IQR, 202-274) nmol/L; 300-mg SLN360, 285 (IQR, 195-338) nmol/L; and 600-mg SLN360, 231 (IQR, 179-276) nmol/L. Maximal median changes in Lp(a) were -20 (IQR, -61 to 3) nmol/L, -89 (IQR, -119 to -61) nmol/L, -185 (IQR, -226 to -163) nmol/L, -268 (IQR, -292 to -189) nmol/L, and -227 (IQR, -270 to -174) nmol/L, with maximal median percentage changes of -10% (IQR, -16% to 1%), -46% (IQR, -64% to -40%), -86% (IQR, -92% to -82%), -96% (IQR, -98% to -89%), and -98% (IQR, -98% to -97%), for the placebo group and the 30-mg, 100-mg, 300-mg, and 600-mg SLN360 groups, respectively. The duration of Lp(a) lowering was dose dependent, persisting for at least 150 days after administration. Conclusions and Relevance: In this phase 1 study of 32 participants with elevated Lp(a) levels and no known cardiovascular disease, the siRNA SLN360 was well tolerated, and a dose-dependent lowering of plasma Lp(a) concentrations was observed. The findings support further study to determine the safety and efficacy of this siRNA. Trial Registration: ClinicalTrials.gov Identifier: NCT04606602; EudraCT Identifier: 2020-002471-35.

Pre-clinical assessment of SLN360, a novel siRNA targeting LPA, developed to address elevated lipoprotein (a) in cardiovascular disease.

BACKGROUND AND AIMS: The LPA gene encodes apolipoprotein (a), a key component of Lp(a), a potent risk factor for cardiovascular disease with no specific pharmacotherapy. Here we describe the pharmacological data for SLN360, a GalNAc-conjugated siRNA targeting LPA, designed to address this unmet medical need. METHODS: SLN360 was tested in vitro for LPA knockdown in primary hepatocytes. Healthy cynomolgus monkeys received single or multiple subcutaneous doses of the SLN360 sequence ranging from 0.1 to 9.0 mg/kg to determine the pharmacokinetic and pharmacodynamic effects. Liver mRNA and serum biomarker analyses were performed. RESULTS: In vitro, the SLN360 sequence potently reduces LPA mRNA in primary cynomolgus and human hepatocytes, while no effect was observed on the expression of APOB or PLG. In vivo, SLN360 exposure peaks 2 h after subcutaneous injection with near full elimination by 24 h. Specific LPA mRNA reduction (up to 91% 2 weeks after dosing) was observed with only the 3 mg/kg group showing appreciable return to baseline (40%). No consistent dose- or time-dependent effect on the expression of APOB, PLG or a panel of sensitive markers of liver lipid accumulation was observed. Potent (up to 95%) and long lasting (≥9 weeks) serum Lp(a) reduction was observed, peaking in all active groups at day 21. The minimally effective dose was determined to be 0.3 mg/kg with an ED50 of 0.6 mg/kg. CONCLUSIONS: SLN360 induces a sustained reduction in serum Lp(a) levels in cynomolgus monkeys following subcutaneous dosing. SLN360 has potential to address the unmet need of Lp(a) reduction in cardiovascular diseases.

Treatment and prevention of lipoprotein(a)-mediated cardiovascular disease: the emerging potential of RNA interference therapeutics.

Lipid- and lipoprotein-modifying therapies have expanded substantially in the last 25 years, resulting in reduction in the incidence of major adverse cardiovascular events. However, no specific lipoprotein(a) [Lp(a)]-targeting therapy has yet been shown to reduce cardiovascular disease risk. Many epidemiological and genetic studies have demonstrated that Lp(a) is an important genetically determined causal risk factor for coronary heart disease, aortic valve disease, stroke, heart failure, and peripheral vascular disease. Accordingly, the need for specific Lp(a)-lowering therapy has become a major public health priority. Approximately 20% of the global population (1.4 billion people) have elevated levels of Lp(a) associated with higher cardiovascular risk, though the threshold for determining 'high risk' is debated. Traditional lifestyle approaches to cardiovascular risk reduction are ineffective at lowering Lp(a). To address a lifelong risk factor unmodifiable by non-pharmacological means, Lp(a)-lowering therapy needs to be safe, highly effective, and tolerable for a patient population who will likely require several decades of treatment. N-acetylgalactosamine-conjugated gene silencing therapeutics, such as small interfering RNA (siRNA) and antisense oligonucleotide targeting LPA, are ideally suited for this application, offering a highly tissue- and target transcript-specific approach with the potential for safe and durable Lp(a) lowering with as few as three or four doses per year. In this review, we evaluate the causal role of Lp(a) across the cardiovascular disease spectrum, examine the role of established lipid-modifying therapies in lowering Lp(a), and focus on the anticipated role for siRNA therapeutics in treating and preventing Lp(a)-related disease.

The genomics of heart failure: design and rationale of the HERMES consortium.

AIMS: The HERMES (HEart failure Molecular Epidemiology for Therapeutic targetS) consortium aims to identify the genomic and molecular basis of heart failure. METHODS AND RESULTS: The consortium currently includes 51 studies from 11 countries, including 68 157 heart failure cases and 949 888 controls, with data on heart failure events and prognosis. All studies collected biological samples and performed genome-wide genotyping of common genetic variants. The enrolment of subjects into participating studies ranged from 1948 to the present day, and the median follow-up following heart failure diagnosis ranged from 2 to 116 months. Forty-nine of 51 individual studies enrolled participants of both sexes; in these studies, participants with heart failure were predominantly male (34-90%). The mean age at diagnosis or ascertainment across all studies ranged from 54 to 84 years. Based on the aggregate sample, we estimated 80% power to genetic variant associations with risk of heart failure with an odds ratio of ≥1.10 for common variants (allele frequency ≥ 0.05) and ≥1.20 for low-frequency variants (allele frequency 0.01-0.05) at P < 5 × 10-8 under an additive genetic model. CONCLUSIONS: HERMES is a global collaboration aiming to (i) identify the genetic determinants of heart failure; (ii) generate insights into the causal pathways leading to heart failure and enable genetic approaches to target prioritization; and (iii) develop genomic tools for disease stratification and risk prediction.

Mendelian randomization for studying the effects of perturbing drug targets.

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.

Phenome-wide association analysis of LDL-cholesterol lowering genetic variants in PCSK9.

BACKGROUND: We characterised the phenotypic consequence of genetic variation at the PCSK9 locus and compared findings with recent trials of pharmacological inhibitors of PCSK9. METHODS: Published and individual participant level data (300,000+ participants) were combined to construct a weighted PCSK9 gene-centric score (GS). Seventeen randomized placebo controlled PCSK9 inhibitor trials were included, providing data on 79,578 participants. Results were scaled to a one mmol/L lower LDL-C concentration. RESULTS: The PCSK9 GS (comprising 4 SNPs) associations with plasma lipid and apolipoprotein levels were consistent in direction with treatment effects. The GS odds ratio (OR) for myocardial infarction (MI) was 0.53 (95% CI 0.42; 0.68), compared to a PCSK9 inhibitor effect of 0.90 (95% CI 0.86; 0.93). For ischemic stroke ORs were 0.84 (95% CI 0.57; 1.22) for the GS, compared to 0.85 (95% CI 0.78; 0.93) in the drug trials. ORs with type 2 diabetes mellitus (T2DM) were 1.29 (95% CI 1.11; 1.50) for the GS, as compared to 1.00 (95% CI 0.96; 1.04) for incident T2DM in PCSK9 inhibitor trials. No genetic associations were observed for cancer, heart failure, atrial fibrillation, chronic obstructive pulmonary disease, or Alzheimer's disease - outcomes for which large-scale trial data were unavailable. CONCLUSIONS: Genetic variation at the PCSK9 locus recapitulates the effects of therapeutic inhibition of PCSK9 on major blood lipid fractions and MI. While indicating an increased risk of T2DM, no other possible safety concerns were shown; although precision was moderate.

Genetic Association of Lipids and Lipid Drug Targets With Abdominal Aortic Aneurysm: A Meta-analysis.

Importance: Risk factors for abdominal aortic aneurysm (AAA) are largely unknown, which has hampered the development of nonsurgical treatments to alter the natural history of disease. Objective: To investigate the association between lipid-associated single-nucleotide polymorphisms (SNPs) and AAA risk. Design, Setting, and Participants: Genetic risk scores, composed of lipid trait-associated SNPs, were constructed and tested for their association with AAA using conventional (inverse-variance weighted) mendelian randomization (MR) and data from international AAA genome-wide association studies. Sensitivity analyses to account for potential genetic pleiotropy included MR-Egger and weighted median MR, and multivariable MR method was used to test the independent association of lipids with AAA risk. The association between AAA and SNPs in loci that can act as proxies for drug targets was also assessed. Data collection took place between January 9, 2015, and January 4, 2016. Data analysis was conducted between January 4, 2015, and December 31, 2016. Exposures: Genetic elevation of low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides (TG). Main Outcomes and Measures: The association between genetic risk scores of lipid-associated SNPs and AAA risk, as well as the association between SNPs in lipid drug targets (HMGCR, CETP, and PCSK9) and AAA risk. Results: Up to 4914 cases and 48 002 controls were included in our analysis. A 1-SD genetic elevation of LDL-C was associated with increased AAA risk (odds ratio [OR], 1.66; 95% CI, 1.41-1.96; P = 1.1 × 10-9). For HDL-C, a 1-SD increase was associated with reduced AAA risk (OR, 0.67; 95% CI, 0.55-0.82; P = 8.3 × 10-5), whereas a 1-SD increase in triglycerides was associated with increased AAA risk (OR, 1.69; 95% CI, 1.38-2.07; P = 5.2 × 10-7). In multivariable MR analysis and both MR-Egger and weighted median MR methods, the association of each lipid fraction with AAA risk remained largely unchanged. The LDL-C-reducing allele of rs12916 in HMGCR was associated with AAA risk (OR, 0.93; 95% CI, 0.89-0.98; P = .009). The HDL-C-raising allele of rs3764261 in CETP was associated with lower AAA risk (OR, 0.89; 95% CI, 0.85-0.94; P = 3.7 × 10-7). Finally, the LDL-C-lowering allele of rs11206510 in PCSK9 was weakly associated with a lower AAA risk (OR, 0.94; 95% CI, 0.88-1.00; P = .04), but a second independent LDL-C-lowering variant in PCSK9 (rs2479409) was not associated with AAA risk (OR, 0.97; 95% CI, 0.92-1.02; P = .28). Conclusions and Relevance: The MR analyses in this study lend support to the hypothesis that lipids play an important role in the etiology of AAA. Analyses of individual genetic variants used as proxies for drug targets support LDL-C lowering as a potential effective treatment strategy for preventing and managing AAA.

PCSK9 genetic variants and risk of type 2 diabetes: a mendelian randomisation study.

BACKGROUND: Statin treatment and variants in the gene encoding HMG-CoA reductase are associated with reductions in both the concentration of LDL cholesterol and the risk of coronary heart disease, but also with modest hyperglycaemia, increased bodyweight, and modestly increased risk of type 2 diabetes, which in no way offsets their substantial benefits. We sought to investigate the associations of LDL cholesterol-lowering PCSK9 variants with type 2 diabetes and related biomarkers to gauge the likely effects of PCSK9 inhibitors on diabetes risk. METHODS: In this mendelian randomisation study, we used data from cohort studies, randomised controlled trials, case control studies, and genetic consortia to estimate associations of PCSK9 genetic variants with LDL cholesterol, fasting blood glucose, HbA1c, fasting insulin, bodyweight, waist-to-hip ratio, BMI, and risk of type 2 diabetes, using a standardised analysis plan, meta-analyses, and weighted gene-centric scores. FINDINGS: Data were available for more than 550 000 individuals and 51 623 cases of type 2 diabetes. Combined analyses of four independent PCSK9 variants (rs11583680, rs11591147, rs2479409, and rs11206510) scaled to 1 mmol/L lower LDL cholesterol showed associations with increased fasting glucose (0·09 mmol/L, 95% CI 0·02 to 0·15), bodyweight (1·03 kg, 0·24 to 1·82), waist-to-hip ratio (0·006, 0·003 to 0·010), and an odds ratio for type diabetes of 1·29 (1·11 to 1·50). Based on the collected data, we did not identify associations with HbA1c (0·03%, -0·01 to 0·08), fasting insulin (0·00%, -0·06 to 0·07), and BMI (0·11 kg/m2, -0·09 to 0·30). INTERPRETATION: PCSK9 variants associated with lower LDL cholesterol were also associated with circulating higher fasting glucose concentration, bodyweight, and waist-to-hip ratio, and an increased risk of type 2 diabetes. In trials of PCSK9 inhibitor drugs, investigators should carefully assess these safety outcomes and quantify the risks and benefits of PCSK9 inhibitor treatment, as was previously done for statins. FUNDING: British Heart Foundation, and University College London Hospitals NHS Foundation Trust (UCLH) National Institute for Health Research (NIHR) Biomedical Research Centre.

Association of Lipid Fractions With Risks for Coronary Artery Disease and Diabetes.

IMPORTANCE: Low-density lipoprotein cholesterol (LDL-C) is causally related to coronary artery disease (CAD), but the relevance of high-density lipoprotein cholesterol (HDL-C) and triglycerides (TGs) is uncertain. Lowering of LDL-C levels by statin therapy modestly increases the risk of type 2 diabetes, but it is unknown whether this effect is specific to statins. OBJECTIVE: To investigate the associations of 3 routinely measured lipid fractions with CAD and diabetes through mendelian randomization (MR) using conventional MR and making use of newer approaches, such as multivariate MR and MR-Egger, that address the pleiotropy of genetic instruments where relevant. DESIGN, SETTING, AND PARTICIPANTS: Published data from genome-wide association studies were used to construct genetic instruments and then applied to investigate associations between lipid fractions and the risk of CAD and diabetes using MR approaches that took into account pleiotropy of genetic instruments. The study was conducted from March 12 to December 31, 2015. MAIN OUTCOMES AND MEASURES: Coronary artery disease and diabetes. RESULTS: Genetic instruments composed of 130 single-nucleotide polymorphisms (SNPs) were used for LDL-C (explaining 7.9% of its variance), 140 SNPs for HDL-C (6.6% of variance), and 140 SNPs for TGs (5.9% of variance). A 1-SD genetically instrumented elevation in LDL-C levels (equivalent to 38 mg/dL) and TG levels (equivalent to 89 mg/dL) was associated with higher CAD risk; odds ratios (ORs) were 1.68 (95% CI, 1.51-1.87) for LDL-C and 1.28 (95% CI, 1.13-1.45) for TGs. The corresponding OR for HDL-C (equivalent to a 16-mg/dL increase) was 0.95 (95% CI, 0.85-1.06). All 3 lipid traits were associated with a lower risk of type 2 diabetes. The ORs were 0.79 (95% CI, 0.71-0.88) for LDL-C and 0.83 (95% CI, 0.76-0.90) for HDL-C per 1-SD elevation. For TG, the MR estimates for diabetes were inconsistent, with MR-Egger giving an OR of 0.83 (95%CI, 0.72-0.95) per 1-SD elevation. CONCLUSIONS AND RELEVANCE: Routinely measured lipid fractions exhibit contrasting associations with the risk of CAD and diabetes. Increased LDL-C, HDL-C, and possibly TG levels are associated with a lower risk of diabetes. This information will be relevant to the design of clinical trials of lipid-modifying agents, which should carefully monitor participants for dysglycemia and the incidence of diabetes.

Selecting instruments for Mendelian randomization in the wake of genome-wide association studies.

Mendelian randomization (MR) studies typically assess the pathogenic relevance of environmental exposures or disease biomarkers, using genetic variants that instrument these exposures. The approach is gaining popularity-our systematic review reveals a greater than 10-fold increase in MR studies published between 2004 and 2015. When the MR paradigm was first proposed, few biomarker- or exposure-related genetic variants were known, most having been identified by candidate gene studies. However, genome-wide association studies (GWAS) are now providing a rich source of potential instruments for MR analysis. Many early reviews covering the concept, applications and analytical aspects of the MR technique preceded the surge in GWAS, and thus the question of how best to select instruments for MR studies from the now extensive pool of available variants has received insufficient attention. Here we focus on the most common category of MR studies-those concerning disease biomarkers. We consider how the selection of instruments for MR analysis from GWAS requires consideration of: the assumptions underlying the MR approach; the biology of the biomarker; the genome-wide distribution, frequency and effect size of biomarker-associated variants (the genetic architecture); and the specificity of the genetic associations. Based on this, we develop guidance that may help investigators to plan and readers interpret MR studies.

Genetic insights into statin-associated diabetes risk.

PURPOSE OF REVIEW: Meta-analyses of major statin trials have suggested that statin therapy modestly increases the risk of developing diabetes. However, the quality of the data on which these findings are based is not without weaknesses and it has also been unclear whether this effect, if true, is an on-target or off-target effect of statins. RECENT FINDINGS: In a major Mendelian randomization study of variants in the HMGCR gene, which encodes the protein through which statins exert their effect, two polymorphisms associated with lower LDL-cholesterol were also associated with higher weight, higher waist circumference, higher glucose and higher diabetes risk. These findings correspond with findings from the statin trials. In addition, new observational studies using a genetic risk score for LDL-cholesterol suggest that other pathways linked to LDL-cholesterol metabolism may also affect diabetes risk. SUMMARY: Genetic studies indicate that the observed effect of statins on diabetes risk in trials is highly likely to be a true on-target effect. Although other recent studies have suggested that genetically determined lower LDL-cholesterol may be linked to diabetes risk, further data from both genetic studies and clinical trials of other LDL-cholesterol lowering agents are needed to confirm or refute this.

Harnessing publicly available genetic data to prioritize lipid modifying therapeutic targets for prevention of coronary heart disease based on dysglycemic risk.

Therapeutic interventions that lower LDL-cholesterol effectively reduce the risk of coronary artery disease (CAD). However, statins, the most widely prescribed LDL-cholesterol lowering drugs, increase diabetes risk. We used genome-wide association study (GWAS) data in the public domain to investigate the relationship of LDL-C and diabetes and identify loci encoding potential drug targets for LDL-cholesterol modification without causing dysglycemia. We obtained summary-level GWAS data for LDL-C from GLGC, glycemic traits from MAGIC, diabetes from DIAGRAM and CAD from CARDIoGRAMplusC4D consortia. Mendelian randomization analyses identified a one standard deviation (SD) increase in LDL-C caused an increased risk of CAD (odds ratio [OR] 1.63 (95 % confidence interval [CI] 1.55, 1.71), which was not influenced by removing SNPs associated with diabetes. LDL-C/CAD-associated SNPs showed consistent effect directions (binomial P = 6.85 × 10(-5)). Conversely, a 1-SD increase in LDL-C was causally protective of diabetes (OR 0.86; 95 % CI 0.81, 0.91), however LDL-cholesterol/diabetes-associated SNPs did not show consistent effect directions (binomial P = 0.15). HMGCR, our positive control, associated with LDL-C, CAD and a glycemic composite (derived from GWAS meta-analysis of four glycemic traits and diabetes). In contrast, PCSK9, APOB, LPA, CETP, PLG, NPC1L1 and ALDH2 were identified as "druggable" loci that alter LDL-C and risk of CAD without displaying associations with dysglycemia. In conclusion, LDL-C increases the risk of CAD and the relationship is independent of any association of LDL-C with diabetes. Loci that encode targets of emerging LDL-C lowering drugs do not associate with dysglycemia, and this provides provisional evidence that new LDL-C lowering drugs (such as PCSK9 inhibitors) may not influence risk of diabetes.

Plasma urate concentration and risk of coronary heart disease: a Mendelian randomisation analysis.

BACKGROUND: Increased circulating plasma urate concentration is associated with an increased risk of coronary heart disease, but the extent of any causative effect of urate on risk of coronary heart disease is still unclear. In this study, we aimed to clarify any causal role of urate on coronary heart disease risk using Mendelian randomisation analysis. METHODS: We first did a fixed-effects meta-analysis of the observational association of plasma urate and risk of coronary heart disease. We then used a conventional Mendelian randomisation approach to investigate the causal relevance using a genetic instrument based on 31 urate-associated single nucleotide polymorphisms (SNPs). To account for potential pleiotropic associations of certain SNPs with risk factors other than urate, we additionally did both a multivariable Mendelian randomisation analysis, in which the genetic associations of SNPs with systolic and diastolic blood pressure, HDL cholesterol, and triglycerides were included as covariates, and an Egger Mendelian randomisation (MR-Egger) analysis to estimate a causal effect accounting for unmeasured pleiotropy. FINDINGS: In the meta-analysis of 17 prospective observational studies (166 486 individuals; 9784 coronary heart disease events) a 1 SD higher urate concentration was associated with an odds ratio (OR) for coronary heart disease of 1·07 (95% CI 1·04-1·10). The corresponding OR estimates from the conventional, multivariable adjusted, and Egger Mendelian randomisation analysis (58 studies; 198 598 individuals; 65 877 events) were 1·18 (95% CI 1·08-1·29), 1·10 (1·00-1·22), and 1·05 (0·92-1·20), respectively, per 1 SD increment in plasma urate. INTERPRETATION: Conventional and multivariate Mendelian randomisation analysis implicates a causal role for urate in the development of coronary heart disease, but these estimates might be inflated by hidden pleiotropy. Egger Mendelian randomisation analysis, which accounts for pleiotropy but has less statistical power, suggests there might be no causal effect. These results might help investigators to determine the priority of trials of urate lowering for the prevention of coronary heart disease compared with other potential interventions. FUNDING: UK National Institute for Health Research, British Heart Foundation, and UK Medical Research Council.

Mendelian Randomization and Type 2 Diabetes.

Type 2 diabetes (T2DM) is a common, complex disease that poses a substantial burden on individual and population health, but we have relatively limited understanding of its underlying pathophysiology. Observational studies have highlighted large numbers of risk factors for T2DM, some of which are modifiable through behavioural or pharmacological intervention. Determining which of these risk factors plays a causal role in the development of T2DM has been a challenge, but Mendelian randomisation (MR) studies are harnessing genetic data in population studies to offer new insights. Using evolving analytical methods, MR studies continue to address questions of causality related to T2DM, including exploring the roles of adiposity, blood lipids and inflammation. The causal roles of a number of important modifiable risk factors have been confirmed by MR studies, while the relevance of others has been called into question. As more MR studies are conducted, methods are developed and refined in order to make the most efficient and reliable use of available genetic and phenotypic data. In this review, the design and findings of some important MR studies related to T2DM are explored and their relevance for translation to clinical practice considered.

Genetic risk factors and Mendelian randomization in cardiovascular disease.

Cardiovascular disease encompasses several diverse pathological states that place a heavy burden on individual and population health. The aetiological basis of many cardiovascular disorders is not fully understood. Growing knowledge of the genetic architecture underlying coronary heart disease, stroke, cardiac arrhythmias and peripheral vascular disease has confirmed some suspected causal pathways in these conditions but also uncovered many previously unknown mechanisms. Here, we consider the contribution of genetics to the understanding of cardiovascular disease risk. We evaluate the utility and relevance of findings from genome-wide association studies and explore the role that Mendelian randomisation has to play in exploiting these. Mendelian randomisation permits robust causal inference in an area of research where this has been hampered by bias and confounding in observational studies. In doing so, it provides evidence for causal processes in cardiovascular disease that could represent novel targets for much-needed new drugs for disease prevention and treatment.

HMG-coenzyme A reductase inhibition, type 2 diabetes, and bodyweight: evidence from genetic analysis and randomised trials.

BACKGROUND: Statins increase the risk of new-onset type 2 diabetes mellitus. We aimed to assess whether this increase in risk is a consequence of inhibition of 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR), the intended drug target. METHODS: We used single nucleotide polymorphisms in the HMGCR gene, rs17238484 (for the main analysis) and rs12916 (for a subsidiary analysis) as proxies for HMGCR inhibition by statins. We examined associations of these variants with plasma lipid, glucose, and insulin concentrations; bodyweight; waist circumference; and prevalent and incident type 2 diabetes. Study-specific effect estimates per copy of each LDL-lowering allele were pooled by meta-analysis. These findings were compared with a meta-analysis of new-onset type 2 diabetes and bodyweight change data from randomised trials of statin drugs. The effects of statins in each randomised trial were assessed using meta-analysis. FINDINGS: Data were available for up to 223 463 individuals from 43 genetic studies. Each additional rs17238484-G allele was associated with a mean 0·06 mmol/L (95% CI 0·05-0·07) lower LDL cholesterol and higher body weight (0·30 kg, 0·18-0·43), waist circumference (0·32 cm, 0·16-0·47), plasma insulin concentration (1·62%, 0·53-2·72), and plasma glucose concentration (0·23%, 0·02-0·44). The rs12916 SNP had similar effects on LDL cholesterol, bodyweight, and waist circumference. The rs17238484-G allele seemed to be associated with higher risk of type 2 diabetes (odds ratio [OR] per allele 1·02, 95% CI 1·00-1·05); the rs12916-T allele association was consistent (1·06, 1·03-1·09). In 129 170 individuals in randomised trials, statins lowered LDL cholesterol by 0·92 mmol/L (95% CI 0·18-1·67) at 1-year of follow-up, increased bodyweight by 0·24 kg (95% CI 0·10-0·38 in all trials; 0·33 kg, 95% CI 0·24-0·42 in placebo or standard care controlled trials and -0·15 kg, 95% CI -0·39 to 0·08 in intensive-dose vs moderate-dose trials) at a mean of 4·2 years (range 1·9-6·7) of follow-up, and increased the odds of new-onset type 2 diabetes (OR 1·12, 95% CI 1·06-1·18 in all trials; 1·11, 95% CI 1·03-1·20 in placebo or standard care controlled trials and 1·12, 95% CI 1·04-1·22 in intensive-dose vs moderate dose trials). INTERPRETATION: The increased risk of type 2 diabetes noted with statins is at least partially explained by HMGCR inhibition. FUNDING: The funding sources are cited at the end of the paper.