Search

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.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.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 EDSLN360 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.

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.

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 x 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.

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.

Introduction: SLN360 is a liver-targeted N-acetyl galactosamine (GalNAc)-conjugated siRNA with a promising profile for addressing Lp(a)-related cardiovascular risk. We previously reported the pharmacodynamic effects of SLN360 in female (F) cynomolgus monkeys (cynos) 1 . Here we describe the findings from key pre-clinical safety studies. Methods: SLN360 was tested in vitro in primary human hepatocytes for LPA knockdown and effects on hypothetical off targets identified through in silico screening. An in vivo biodistribution study was performed in rats over 21 days (4 males [M]/4 F per timepoint; single 10 mg/kg s.c. injection). In a GLP safety study, healthy cynos received 5 once weekly s.c. injections of saline control or SLN360 (3 M / 3 F per group, up to 200 mg/kg) followed by an 8-week recovery period (2 M / 2 F in saline and top dose). A standard battery of safety assessments was performed. Results: In vitro, SLN360 reduced LPA expression in primary human hepatocytes with no effects on any hypothetical liver-expressed human off-target genes at concentrations >300-fold the human LPA IC 50 . SLN360 showed a typical rodent GalNAc distribution pattern, with significant levels in liver and kidney (peak 126 or 246 mg/g tissue at 6h respectively; estimated liver half-life of 56 hours). Levels in other organs (including reproductive organs) were LPA mRNA levels were significantly reduced by 98% at day 30 and 95% after the 8-week recovery period, while serum Lp(a) was undetectable at both timepoints. Findings were restricted to the liver (increased weight and diffuse hepatocyte hypertrophy) and lymph nodes (vacuolated macrophages) at day 30. These were considered non-adverse due to reversibility after recovery. No dose-related changes in clinical chemistry, hematology, circulatory and ECG parameters, respiratory rate, neurobehavior, plasma cytokines, complement activation or CRP were noted. The NOAEL was defined as 200 mg/kg, >60-fold the active dose in cynos. Conclusions: Overall, the off-target profile, biodistribution and NOAEL of SLN360 indicate suitability for entry into clinical studies. 1 Aleku et al., 2019. Circulation. 2019, 140:A9538.

Heart failure (HF) is a leading cause of morbidity and mortality worldwide1. A small proportion of HF cases are attributable to monogenic cardiomyopathies and existing genome-wide association studies (GWAS) have yielded only limited insights, leaving the observed heritability of HF largely unexplained2–4. We report the largest GWAS meta-analysis of HF to-date, comprising 47,309 cases and 930,014 controls. We identify 12 independent variant associations with HF at 11 genomic loci, all of which demonstrate one or more associations with coronary artery disease (CAD), atrial fibrillation, or reduced left ventricular function suggesting shared genetic aetiology. Expression quantitative trait analysis of non-CAD-associated loci implicate genes involved in cardiac development (MYOZ1, SYNPO2L), protein homeostasis (BAG3), and cellular senescence (CDKN1A). Using Mendelian randomisation analysis we provide new evidence supporting previously equivocal causal roles for several HF risk factors identified in observational studies, and demonstrate CAD-independent effects for atrial fibrillation, body mass index, hypertension and triglycerides. These findings extend our knowledge of the genes and pathways underlying HF and may inform the development of new therapeutic approaches.

BackgroundWe characterised the phenotypic consequence of genetic variation at the PCSK9 locus and compared findings with recent trials of pharmacological inhibitors of PCSK9.MethodsPublished and individual participant level data (300,000+ participants) were combined to construct a weighted PCSK9 gene-centric score (GS). Fourteen 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 concentrationResultsThe 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.ConclusionsGenetic variation at the PCSK9 locus recapitulates the effects of therapeutic inhibition of PCSK9 on major blood lipid fractions and MI. Apparent discordance between genetic associations and trial outcome for T2DM might be explained lack by a of statistical precision, or differences in the nature and duration of genetic versus pharmacological perturbation of PCSK9.FundingThis research was funded by the British Heart Foundation (SP/13/6/30554, RG/10/12/28456, FS/18/23/33512), UCL Hospitals NIHR Biomedical Research Centre, by the Rosetrees and Stoneygate Trusts.Condensed abstractEvidence on the long-term efficacy and safety of therapeutic inhibition of PCSK9 is lacking. To explore potential long-term effects of PCSK9 inhibition, we characterised the phenotypic consequence of LDL-cholesterol lowering variants at the PCSK9 locus. A PCSK9 gene score comprising 4 SNPs recapitulated the effects of therapeutic inhibition of PCSK9 on major blood lipid fractions and risk of myocardial infarction, and was associated with an increased risk of type 2 diabetes. No associations with safety outcomes such as cancer, COPD, Alzheimer’s disease or atrial fibrillation were identified. Our findings suggest PCSK9 inhibition may be safe and effective during prolonged use.

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.

The genetics of rare familial hyperlipidaemias have been studied for many years, but the last decade has seen major advances in our understanding of the genetics of common dyslipidaemias. These developments have largely been propelled by the rapid innovations in genotyping and phenotyping technologies. Genome-wide association, whole exome sequencing, and whole genome sequencing studies have identified a large number of genetic loci involved in lipid metabolism. Large-scale meta-analyses have included over 150,000 individuals, increasing statistical power to identify rarer variants, and common variants with smaller phenotypic effects. Furthermore, advances in phenotyping such as nuclear magnetic resonance-based lipidomics have facilitated finer mapping of circulating lipids and lipoproteins. Capitalizing on the findings from these large-scale studies, genetic analyses using the Mendelian randomization principle have been used successfully to explore the causal contributions to heart disease of a range of circulating lipid fractions. Such investigations have confirmed a causal role for low-density lipoprotein cholesterol, suggest a causal role for triglycerides, but cast doubt on that of high-density lipoprotein cholesterol. Furthermore, genetic studies have been shown to have an important application in the validation of novel therapeutic targets for treatment of dyslipidaemias.

The pro-inflammatory cytokine interleukin (IL)-1β is implicated in the development of insulin resistance and beta-cell dysfunction, whereas higher circulating IL-1 receptor antagonist (IL-1RA - an endogenous inhibitor of IL-1β - has been suggested to improve glycemia and beta-cell function in patients with type 2 diabetes. In order to elucidate the protective role of IL-1RA, this study aimed to identify genetic determinants of circulating IL-1RA concentration and to investigate their associations with immunological and metabolic variables related to cardiometabolic risk. In the analysis of 7 discovery and 4 replication cohort studies, two single nucleotide polymorphisms (SNPs) were independently associated with circulating IL-1RA concentration (rs4251961 at the IL-1RN locus, n=13,955, P=2.76x10(-21); and rs6759676, closest gene locus IL1F10, n=13,994, P=1.73x10(-17)). The proportion of the variance in IL-1RA explained by both SNPs combined was 2.0%. IL-1RA-raising alleles of both SNPs were associated with lower circulating C-reactive protein concentration. The IL-1RA-raising allele of rs6759676 was also associated with lower fasting insulin and lower homeostasis model assessment insulin resistance (HOMA-IR). In conclusion, we show that circulating IL-1RA levels are predicted by two independent SNPs at the IL-1RN and IL-1F10 loci and that genetically raised IL-1RA may be protective against the development of insulin resistance.

Background— Inflammatory cytokine interleukin-6 (IL-6), a possible risk factor for coronary heart disease, has an estimated heritability of >60%, but to date few genetic variants influencing IL-6 levels are known. Methods and Results— We used the ITMAT-Broad-Care (IBC) HumanCVD disease BeadChip in the Whitehall II study (N=4911) and British Women’s Heart and Health Study (N=3445) to identify single-nucleotide polymorphisms associated with circulating IL-6 levels. Twenty-two single-nucleotide polymorphisms from 7 loci ( IL6R/TDRD10 , HLA-DRB1 , BUD13 , SEZ6L , IL1RN , TRIB3 , and ABO ) were associated with IL-6 ( P –5 ), although none were associated with the IL6 gene itself. With the exception of TRIB3 , all loci have been previously reported in genome-wide association studies for autoimmune and cardiovascular diseases. Fourteen single-nucleotide polymorphisms in the IL6R region in high-linkage disequilibrium (r 2 >0.9) with a nonsynonymous variant, rs2228145, were also associated with IL-6 and C-reactive protein concentration ( P –5 ). An IL-6–specific weighted allele score explained 2% of the variance of log IL-6 levels ( P =2.4410 –22 ) in Whitehall II and 1% ( P =1.910 –8 ) in British Women’s Heart and Health Studies. Conclusions— Multiple common genetic variants of modest effect influence IL-6 concentration. Several loci contain single-nucleotide polymorphisms, exhibiting overlapping associations with autoimmune and cardiovascular disorders and other circulating biomarkers. Genetic variants associated with IL-6 provide important tools for probing the causal relevance of IL-6 signaling in a range of cardiometabolic diseases.

Background— Carotid intima–media thickness (CIMT), a subclinical measure of atherosclerosis, is associated with risk of coronary heart disease events. Statins reduce progression of CIMT and coronary heart disease risk in proportion to the reduction in low-density lipoprotein cholesterol. However, interventions targeting triglycerides (TGs) or high-density lipoprotein cholesterol (HDL-C) have produced inconsistent effects on CIMT and coronary heart disease risk, making it uncertain whether such agents are ineffective for coronary heart disease prevention or whether CIMT is an inadequate marker of HDL-C or TG-mediated effects. We aimed to determine the causal association among the 3 major blood lipid fractions and common CIMT using mendelian randomization analysis. Methods and Results— Genetic scores specific for low-density lipoprotein cholesterol, HDL-C, and TGs were derived based on single nucleotide polymorphisms from a gene-centric array in ≈5000 individuals (Cardiochip scores) and from a genome-wide association meta-analysis in >100 000 individuals (Global Lipids Genetic Consortium scores). These were used as instruments in a mendelian randomization analysis in 2 prospective cohort studies. A genetically predicted 1 mmol/L higher low-density lipoprotein cholesterol concentration was associated with a higher common CIMT by 0.03 mm (95% confidence interval, 0.01–0.04) and 0.04 mm (95% confidence interval, 0.02–0.06) based on the Cardiochip and Global Lipids Genetic Consortium scores, respectively. HDL-C and TGs were not causally associated with CIMT. Conclusions— Our findings confirm a causal relationship between low-density lipoprotein cholesterol and CIMT but not with HDL-C and TGs. At present, the suitability of CIMT as a surrogate marker in trials of cardiovascular therapies targeting HDL-C and TGs is questionable and requires further study.

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.

Genome-wide association studies (GWASs) have identified many SNPs underlying variations in plasma-lipid levels. We explore whether additional loci associated with plasma-lipid phenotypes, such as high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), and triglycerides (TGs), can be identified by a dense gene-centric approach. Our meta-analysis of 32 studies in 66,240 individuals of European ancestry was based on the custom ∼50,000 SNP genotyping array (the ITMAT-Broad-CARe array) covering ∼2,000 candidate genes. SNP-lipid associations were replicated either in a cohort comprising an additional 24,736 samples or within the Global Lipid Genetic Consortium. We identified four, six, ten, and four unreported SNPs in established lipid genes for HDL-C, LDL-C, TC, and TGs, respectively. We also identified several lipid-related SNPs in previously unreported genes: DGAT2, HCAR2, GPIHBP1, PPARG, and FTO for HDL-C; SOCS3, APOH, SPTY2D1, BRCA2, and VLDLR for LDL-C; SOCS3, UGT1A1, BRCA2, UBE3B, FCGR2A, CHUK, and INSIG2 for TC; and SERPINF2, C4B, GCK, GATA4, INSR, and LPAL2 for TGs. The proportion of explained phenotypic variance in the subset of studies providing individual-level data was 9.9% for HDL-C, 9.5% for LDL-C, 10.3% for TC, and 8.0% for TGs. This large meta-analysis of lipid phenotypes with the use of a dense gene-centric approach identified multiple SNPs not previously described in established lipid genes and several previously unknown loci. The explained phenotypic variance from this approach was comparable to that from a meta-analysis of GWAS data, suggesting that a focused genotyping approach can further increase the understanding of heritability of plasma lipids. © 2012 The American Society of Human Genetics.

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.

SummaryBackgroundA high circulating concentration of interleukin 6 is associated with increased risk of coronary heart disease. Blockade of the interleukin-6 receptor (IL6R) with a monoclonal antibody (tocilizumab) licensed for treatment of rheumatoid arthritis reduces systemic and articular inflammation. However, whether IL6R blockade also reduces risk of coronary heart disease is unknown.MethodsApplying the mendelian randomisation principle, we used single nucleotide polymorphisms (SNPs) in the gene IL6R to evaluate the likely efficacy and safety of IL6R inhibition for primary prevention of coronary heart disease. We compared genetic findings with the effects of tocilizumab reported in randomised trials in patients with rheumatoid arthritis.FindingsIn 40 studies including up to 133 449 individuals, an IL6R SNP (rs7529229) marking a non-synonymous IL6R variant (rs8192284; p.Asp358Ala) was associated with increased circulating log interleukin-6 concentration (increase per allele 9·45%, 95% CI 8·34–10·57) as well as reduced C-reactive protein (decrease per allele 8·35%, 95% CI 7·31–9·38) and fibrinogen concentrations (decrease per allele 0·85%, 95% CI 0·60–1·10). This pattern of effects was consistent with IL6R blockade from infusions of tocilizumab (4–8 mg/kg every 4 weeks) in patients with rheumatoid arthritis studied in randomised trials. In 25 458 coronary heart disease cases and 100 740 controls, the IL6R rs7529229 SNP was associated with a decreased odds of coronary heart disease events (per allele odds ratio 0·95, 95% CI 0·93–0·97, p=1·53×10−5).InterpretationOn the basis of genetic evidence in human beings, IL6R signalling seems to have a causal role in development of coronary heart disease. IL6R blockade could provide a novel therapeutic approach to prevention of coronary heart disease that warrants testing in suitably powered randomised trials. Genetic studies in populations could be used more widely to help to validate and prioritise novel drug targets or to repurpose existing agents and targets for new therapeutic uses.FundingUK Medical Research Council; British Heart Foundation; Rosetrees Trust; US National Heart, Lung, and Blood Institute; Du Pont Pharma; Chest, Heart and Stroke Scotland; Wellcome Trust; Coronary Thrombosis Trust; Northwick Park Institute for Medical Research; UCLH/UCL Comprehensive Medical Research Centre; US National Institute on Aging; Academy of Finland; Netherlands Organisation for Health Research and Development; SANCO; Dutch Ministry of Public Health, Welfare and Sports; World Cancer Research Fund; Agentschap NL; European Commission; Swedish Heart-Lung Foundation; Swedish Research Council; Strategic Cardiovascular Programme of the Karolinska Institutet; Stockholm County Council; US National Institute of Neurological Disorders and Stroke; MedStar Health Research Institute; GlaxoSmithKline; Dutch Kidney Foundation; US National Institutes of Health; Netherlands Interuniversity Cardiology Institute of the Netherlands; Diabetes UK; European Union Seventh Framework Programme; National Institute for Healthy Ageing; Cancer Research UK; MacArthur Foundation.

Much of the progress in cardiovascular genetics in 2016 has been driven by next-generation sequencing studies, and the clinical utility of knowing an individual's genotype for predicting their risk of cardiovascular disease is gaining credibility, both for monogenic and polygenic disorders. Additionally, phenotype data are increasingly abundant, although databases linking genotype with clinically relevant phenotypes require optimization.

The study of complex disease genetics is at a critical turning point. Development of high-throughput technology has enabled a change in the investigational approach from traditional candidate gene studies to hypothesis-free genome-wide association studies (GWAS). These experiments have generated an abundance of data, novel analytic methods, some answers but also many questions. The aim of this year's Autumn meeting of the British Atherosclerosis Society was to update members on research in complex disease genetics. This common platform has brought together a number of scientific disciplines including genetics, epidemiology, bioinformatics, statistics and medicine, all of which were reflected in the diverse backgrounds of speakers and delegates at this meeting.Two principal themes emerged from this meeting and are summarised here. Firstly the success of GWAS in discovery of novel disease loci with emerging novel analytical methodologies to interpret this abundance of data (and how to overcome their limitations) and secondly, the translational application of the information gathered so far from GWAS, and what we can expect in the future...

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.

Cardiovascular disease is a leading cause of mortality across Europe and the USA. Epidemiological studies and randomized clinical trials provide strong evidence that coronary disease is largely preventable and can be attributed principally to nine modifiable risk factors. However, a large proportion of coronary events occur in individuals who have intermediate levels of these risk factors, motivating the search for novel markers to improve screening and risk stratification. Work presented at the 78th European Atherosclerosis Society Congress outlined challenges faced in primary prevention as well as novel findings for risk factors. This article focuses on some of these factors, as well as risk prediction and detection, and concludes with the current state of antiatherogenic treatment strategies.

Emerging data from randomized trials have shown that a growing number of lipid-lowering drugs appear to influence glycemic control in addition to their hypolipidemic effects. Statins have been shown conclusively in large meta-analyses of randomized trials to increase, albeit modestly, the risk of new-onset type 2 diabetes (T2D) in an apparently dose-dependent manner (1–3). In the Investigation of Lipid Level Management to Understand Its Impact in Atherosclerotic Events (ILLUMINATE) trial, treatment with torcetrapib, a CETP inhibitor that raised HDL cholesterol (HDL-C) concentrations, improved glycemic control (4), but in the Treatment of HDL to Reduce the Incidence of Vascular Events (HPS2-THRIVE) study, niacin treatment, which also raised HDL-C, raised blood glucose and T2D risk (5). In a recent intriguing observational study, notwithstanding the inevitable limitations of its design, patients with familial hypercholesterolemia (FH) appeared less likely to develop T2D (6). Evidence is therefore emerging for a relationship between circulating lipid concentrations and/or their therapeutic/genetic modulators and alterations in glycemia. The mechanisms underlying such relationships remain uncertain and are the subject of much research, not least because they may reveal new drug targets for diabetes or help in the mitigation of dysglycemia risks with specific therapies. In this issue of Diabetes , Fall et al. (7 …

Objectives:\ud This study sought to investigate the role of secretory phospholipase A2 (sPLA2)-IIA in cardiovascular disease.\ud \ud Background:\ud Higher circulating levels of sPLA2-IIA mass or sPLA2 enzyme activity have been associated with increased risk of cardiovascular events. However, it is not clear if this association is causal. A recent phase III clinical trial of an sPLA2 inhibitor (varespladib) was stopped prematurely for lack of efficacy.\ud \ud Methods:\ud We conducted a Mendelian randomization meta-analysis of 19 general population studies (8,021 incident, 7,513 prevalent major vascular events [MVE] in 74,683 individuals) and 10 acute coronary syndrome (ACS) cohorts (2,520 recurrent MVE in 18,355 individuals) using rs11573156, a variant in PLA2G2A encoding the sPLA2-IIA isoenzyme, as an instrumental variable.\ud \ud Results:\ud PLA2G2A rs11573156 C allele associated with lower circulating sPLA2-IIA mass (38% to 44%) and sPLA2 enzyme activity (3% to 23%) per C allele. The odds ratio (OR) for MVE per rs11573156 C allele was 1.02 (95% confidence interval [CI]: 0.98 to 1.06) in general populations and 0.96 (95% CI: 0.90 to 1.03) in ACS cohorts. In the general population studies, the OR derived from the genetic instrumental variable analysis for MVE for a 1-log unit lower sPLA2-IIA mass was 1.04 (95% CI: 0.96 to 1.13), and differed from the non-genetic observational estimate (OR: 0.69; 95% CI: 0.61 to 0.79). In the ACS cohorts, both the genetic instrumental variable and observational ORs showed a null association with MVE. Instrumental variable analysis failed to show associations between sPLA2 enzyme activity and MVE.\ud \ud Conclusions:\ud Reducing sPLA2-IIA mass is unlikely to be a useful therapeutic goal for preventing cardiovascular events.

Substantial advances have been made in identifying common genetic variants influencing cardiometabolic traits and disease outcomes through genome wide association studies. Nevertheless, gaps in knowledge remain and new questions have arisen regarding the population relevance, mechanisms, and applications for healthcare. Using a new high-resolution custom single nucleotide polymorphism (SNP) array (Metabochip) incorporating dense coverage of genomic regions linked to cardiometabolic disease, the University College-London School-Edinburgh-Bristol (UCLEB) consortium of highly-phenotyped population-based prospective studies, aims to: (1) fine map functionally relevant SNPs; (2) precisely estimate individual absolute and population attributable risks based on individual SNPs and their combination; (3) investigate mechanisms leading to altered risk factor profiles and CVD events; and (4) use Mendelian randomisation to undertake studies of the causal role in CVD of a range of cardiovascular biomarkers to inform public health policy and help develop new preventative therapies.

The size and concentration of exhaled particles may influence respiratory infection transmission risk. We assessed variation in exhaled particle production between individuals, factors associated with high production and stability over time.We measured exhaled particle production during tidal breathing in a sample of 79 healthy volunteers, using optical particle counter technology. Repeat measurements (several months after baseline) were obtained for 37 of the 79 participants. Multilevel linear regression models of log transformed particle production measures were used to assess risk factors for high production. Stability between measurements over time was assessed using Lin’s correlation coefficients.Ninety-nine percent of expired particles were Sub-micron particles conducive to airborne rather than droplet transmission form the great majority of exhaled particles in tidal breathing. There is a high level of variability between subjects but measurements are not stable over time. Production increases with age and may be influenced by airway inflammation caused by environmental irritants. Further research is needed to determine whether the observed variations in exhaled particle production affect transmission of respiratory infection.

METHODS: We conducted a systematic review and meta-analysis of studies reporting circulating IL-6 in AAA, and new investigations of the association between a common non-synonymous functional variant (Asp358Ala) in the IL-6R gene (IL6R) and AAA, followed the analysis of the variant both in vitro and in vivo. Inflammation may play a role in the development of abdominal aortic aneurysms (AAA). Interleukin-6 (IL-6) signalling through its receptor (IL-6R) is one pathway that could be exploited pharmacologically. We investigated this using a Mendelian randomization approach. RESULTS: Up to October 2011, we identified seven studies (869 cases, 851 controls). Meta-analysis demonstrated that AAA cases had higher levels of IL-6 than controls [standardized mean difference (SMD) = 0.46 SD, 95% CI = 0.25-0.66, I(2) = 70%, P = 1.1 × 10-5 random effects]. Meta-analysis of five studies (4524 cases/15 710 controls) demonstrated that rs7529229 (which tags the non-synonymous variant Asp358Ala, rs2228145) was associated with a lower risk of AAA, per Ala358 allele odds ratio 0.84, 95% CI: 0.80-0.89, I(2) = 0%, P = 2.7 × 10-11). In vitro analyses in lymphoblastoid cell lines demonstrated a reduction in the expression of downstream targets (STAT3, MYC and ICAM1) in response to IL-6 stimulation in Ala358 carriers. CONCLUSIONS: A Mendelian randomization approach provides robust evidence that signalling via the IL-6R is likely to be a causal pathway in AAA. Drugs that inhibit IL-6R may play a role in AAA management.

Background: Coronary heart disease (CHD) is a leading cause of death worldwide, yet many areas of its pathogenesis remain unknown or poorly understood, leaving potential for novel preventive and therapeutic interventions. Recent major advances in genomic science and technology have opened new avenues of investigation in the pathogenesis of CHD, some of which are leading to clinical translation. Sources of data: The published literature in CHD genetics has burgeoned in the last 5 years with the reporting of genome-wide association studies (GWASs) and many other findings. Areas of agreement: Identification of many genetic variants with small effects on CHD risk has been a common finding. These have included several predicted loci, such as those involved in conventional CHD risk factors (e.g. plasma lipids) and many novel loci, where their mechanism of action is unclear. The need for large, collaborative approaches to research has also become clear and is now an accepted modus operandi. Areas of controversy: The clinical utility of novel GWAS findings remains uncertain. In particular, the relative contribution of common variants of modest effect and rare variants of larger effects to risk of CHD or response to drugs is unclear. Growing points: As a greater number of larger GWASs are conducted in CHD and its related phenotypes, much effort is being made to find translational applications for their findings. Therapeutics, prediction and pathology are major areas of research endeavour.

Image-guided biopsy is a safe and well-established technique that is familiar to most interventional radiologists (IRs). Improvements in image-guidance, biopsy tools and biopsy techniques now routinely allow for safe biopsy of renal and adrenal lesions which traditionally were considered difficult to reach or technically challenging. Image-guided biopsy is used to establish the definitive tissue diagnosis in adrenal mass lesions that can not be fully characterized with imaging or laboratory tests alone. It is also used to establish definitive diagnosis in some cases of renal parenchymal disease and has an expanding role in diagnosis and characterization of renal masses prior to treatment. Although basic principles and techniques for image-guided needle biopsy are similar regardless of organ, this paper will highlight some technical considerations, indications and complications which are unique to the adrenal gland and kidney because of their anatomic location and physiologic features.

A report on the British Atherosclerosis Society autumn meeting 'Genetics of Complex Diseases', Cambridge, UK, 17-18 September 2009.

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. Electronic supplementary material The online version of this article (doi:10.1007/s00439-016-1647-9) contains supplementary material, which is available to authorized users.

In this issue of the journal, Erqou and colleagues (DOI 10.1007/s00125-014-3374-x ) report, in a systematic review and meta-analysis of randomised trials, a very modest (1.3 mmol/mol or 0.12%) albeit significant increase in HbA1c in patients with diabetes treated with statins, compared with control. Here, we discuss the clinical relevance of the findings. Given the overwhelming benefit of statins on cardiovascular outcomes in diabetes, current guidelines recommending statins for primary prevention in type 2 diabetes should not change, and any effect on microvascular risk is likely to be minimal. Of course, all patients recommended for statin treatment, whether they have diabetes or not, should now be warned of a slight potential for dysglycaemia on starting statins, but at the same time they should be told that very modest lifestyle improvement will help offset this dysglycaemia risk. Finally, we remind colleagues that nearly all drugs have side effects and we should not be surprised by this statin–dysglycaemia effect, which can be easily managed.

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.

Aims The aim of this study was to quantify the collective effect of common lipid-associated single nucleotide polymorphisms (SNPs) on blood lipid levels, cardiovascular risk, use of lipid-lowering medication, and risk of coronary heart disease (CHD) events. Methods and results Analysis was performed in two prospective cohorts: Whitehall II (WHII; N = 5059) and the British Women’s Heart and Health Study (BWHHS; N = 3414). For each participant, scores were calculated based on the cumulative effect of multiple genetic variants influencing total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides (TG). Compared with the bottom quintile, individuals in the top quintile of the LDL-C genetic score distribution had higher LDL-C {mean difference of 0.85 [95% confidence interval, (CI) = 0.76–0.94] and 0.63 [95% CI = 0.50–0.76] mmol/l in WHII and BWHHS, respectively}. They also tended to have greater odds of having ‘high-risk’ status (Framingham 10-year cardiovascular disease risk >20%) [WHII: odds ratio (OR) = 1.36 (0.93–1.98), BWHHS: OR = 1.49 (1.14–1.94)]; receiving lipid-lowering treatment [WHII: OR = 2.38 (1.57–3.59), BWHHS: OR = 2.24 (1.52–3.29)]; and CHD events [WHII: OR = 1.43 (1.02–2.00), BWHHS: OR = 1.31 (0.99–1.72)]. Similar associations were observed for the TC score in both studies. The TG score was associated with high-risk status and medication use in both studies. Neither HDL nor TG scores were associated with the risk of coronary events. The genetic scores did not improve discrimination over the Framingham risk score. Conclusion At the population level, common SNPs associated with LDL-C and TC contribute to blood lipid variation, cardiovascular risk, use of lipid-lowering medications and coronary events. However, their effects are too small to discriminate future lipid-lowering medication requirements or coronary events.

Elevated body mass index (BMI) associates with cardiometabolic traits on observational analysis, yet the underlying causal relationships remain unclear. We conducted Mendelian randomization analyses by using a genetic score (GS) comprising 14 BMI-associated SNPs from a recent discovery analysis to investigate the causal role of BMI in cardiometabolic traits and events. We used eight population-based cohorts, including 34,538 European-descent individuals (4,407 type 2 diabetes (T2D), 6,073 coronary heart disease (CHD), and 3,813 stroke cases). A 1 kg/m(2) genetically elevated BMI increased fasting glucose (0.18 mmol/l; 95% confidence interval (CI) = 0.12-0.24), fasting insulin (8.5%; 95% CI = 5.9-11.1), interleukin-6 (7.0%; 95% CI = 4.0-10.1), and systolic blood pressure (0.70 mmHg; 95% CI = 0.24-1.16) and reduced high-density lipoprotein cholesterol (-0.02 mmol/l; 95% CI = -0.03 to -0.01) and low-density lipoprotein cholesterol (LDL-C; -0.04 mmol/l; 95% CI = -0.07 to -0.01). Observational and causal estimates were directionally concordant, except for LDL-C. A 1 kg/m(2) genetically elevated BMI increased the odds of T2D (odds ratio [OR] = 1.27; 95% CI = 1.18-1.36) but did not alter risk of CHD (OR 1.01; 95% CI = 0.94-1.08) or stroke (OR = 1.03; 95% CI = 0.95-1.12). A meta-analysis incorporating published studies reporting 27,465 CHD events in 219,423 individuals yielded a pooled OR of 1.04 (95% CI = 0.97-1.12) per 1 kg/m(2) increase in BMI. In conclusion, we identified causal effects of BMI on several cardiometabolic traits; however, whether BMI causally impacts CHD risk requires further evidence.