Daniel I. Swerdlow

Mendelian randomization of blood lipids for coronary heart disease.

Aims To investigate the causal role of high-density lipoprotein cholesterol (HDL-C) and triglycerides in coronary heart disease (CHD) using multiple instrumental variables for Mendelian randomization. Methods and results We developed weighted allele scores based on single nucleotide polymorphisms (SNPs) with established associations with HDL-C, triglycerides, and low-density lipoprotein cholesterol (LDL-C). For each trait, we constructed two scores. The first was unrestricted, including all independent SNPs associated with the lipid trait identified from a prior meta-analysis (threshold P < 2 × 10−6); and the second a restricted score, filtered to remove any SNPs also associated with either of the other two lipid traits at P ≤ 0.01. Mendelian randomization meta-analyses were conducted in 17 studies including 62,199 participants and 12,099 CHD events. Both the unrestricted and restricted allele scores for LDL-C (42 and 19 SNPs, respectively) associated with CHD. For HDL-C, the unrestricted allele score (48 SNPs) was associated with CHD (OR: 0.53; 95% CI: 0.40, 0.70), per 1 mmol/L higher HDL-C, but neither the restricted allele score (19 SNPs; OR: 0.91; 95% CI: 0.42, 1.98) nor the unrestricted HDL-C allele score adjusted for triglycerides, LDL-C, or statin use (OR: 0.81; 95% CI: 0.44, 1.46) showed a robust association. For triglycerides, the unrestricted allele score (67 SNPs) and the restricted allele score (27 SNPs) were both associated with CHD (OR: 1.62; 95% CI: 1.24, 2.11 and 1.61; 95% CI: 1.00, 2.59, respectively) per 1-log unit increment. However, the unrestricted triglyceride score adjusted for HDL-C, LDL-C, and statin use gave an OR for CHD of 1.01 (95% CI: 0.59, 1.75). Conclusion The genetic findings support a causal effect of triglycerides on CHD risk, but a causal role for HDL-C, though possible, remains less certain.

Causal effects of body mass index on cardiometabolic traits and events: A Mendelian randomization analysis

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.

Interleukin-6 receptor pathways in abdominal aortic aneurysm

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, I2 = 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, I2 = 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.

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.

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

Summary 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.

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.

The genetics of coronary heart disease

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.

Gene-Centric Analysis Identifies Variants Associated With Interleukin-6 Levels and Shared Pathways With Other Inflammation Markers

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<10–5), 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 (r2>0.9) with a nonsynonymous variant, rs2228145, were also associated with IL-6 and C-reactive protein concentration (P<10–5). 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.

Causal relevance of blood lipid fractions in the development of carotid atherosclerosis: mendelian randomization analysis

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.

Genetic Determinants of Circulating Interleukin-1 Receptor Antagonist Levels and Their Association With Glycemic Traits

The proinflammatory cytokine interleukin (IL)-1β is implicated in the development of insulin resistance and β-cell dysfunction, whereas higher circulating levels of IL-1 receptor antagonist (IL-1RA), an endogenous inhibitor of IL-1β, has been suggested to improve glycemia and β-cell function in patients with type 2 diabetes. 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 seven discovery and four replication cohort studies, two single nucleotide polymorphisms (SNPs) were independently associated with circulating IL-1RA concentration (rs4251961 at the IL1RN locus [n = 13,955, P = 2.76 × 10−21] and rs6759676, closest gene locus IL1F10 [n = 13,994, P = 1.73 × 10−17]). 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 levels and lower HOMA insulin resistance. In conclusion, we show that circulating IL-1RA levels are predicted by two independent SNPs at the IL1RN and IL1F10 loci and that genetically raised IL-1RA may be protective against the development of insulin resistance.