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

The association of telomere length with paternal history of premature myocardial infarction in the European Atherosclerosis Research Study II

Inter-individual variability in telomere length is highly heritable and has been correlated with risk of coronary heart disease (CHD). Our aim was to determine the association of mean leukocyte telomere length with paternal history of premature myocardial infarction (MI). Mean leukocyte telomere length was measured with real-time polymerase chain reactions in 369 male students (18–28 years) with a paternal history of MI before the age of 55, recruited from 14 European universities, serving as cases and 396 age-matched controls with no paternal history of CHD. Overall, cases had borderline significantly shorter mean length (~550 bp), adjusted for age and geographical region, than controls (p = 0.05). A significant difference in telomere length across the geographical regions of Europe was observed (p < 0.0001), with shorter mean length in the Baltic and South and the longest in the Middle. The case–control difference (∼2.24 kb) in mean length was highly significant only in the Baltic region (p < 0.0001). There is suggestive evidence that, in young men, the biological expression of a paternal history of premature MI is at least in part mediated through inherited short telomeres. The association with paternal history of MI is strongly seen only in the Baltic compared to the rest of Europe, but this is not explained by shorter telomere length in this region

Genetic Susceptibility for Coronary Heart Disease and Type 2 Diabetes Complications

Type II diabetes (T2D) 3 represents a major public health challenge, with the WHO having estimated a current prevalence of 346 million worldwide. Cardiovascular disease, including coronary heart disease (CHD), stroke, and peripheral vascular disease, is one of the major complications of T2D, and the development of new strategies to tackle this problem is undoubtedly necessary. Although the association between diabetes and cardiovascular risk is well established, the pathologic basis of CHD in patients with T2D may differ from that in the general population. Whether this relationship has a genetic component is not fully understood. With regard to understanding the genetic basis of complex diseases, genomewide association studies (GWASs) have led to an unprecedented number of well-validated variants associated with complex diseases. There is now considerable interest in understanding both the mechanism by which these variants confer risk and whether the variants identified will be useful for predicting complex disease phenotypes. A recent report by Qi et al. (1 ) addressed 2 questions in this regard: (a) Are single-nucleotide polymorphisms (SNPs) identified by GWASs of CHD associated with the risk of CHD in T2D, and (b) can these variants be combined in a score that will aid prediction of CHD risk in T2D? In investigating these questions, Qi and coworkers genotyped 12 CHD susceptibility loci in 3 nested case-control studies of CHD in T2D: the Nurses&apos; Health Study, the Health Professional Follow-Up Study, and the Joslin Heart Study. As expected, the chromosome 9p21 CHD risk locus showed a strong association with CHD risk, whereas 4 other loci [PHACTR1 4 (phosphatase and ac- None of the other variants tested showed associations with CHD below the significance threshold (P ϭ 0.05), although the authors noted that 2 of the loci examined [MRAS (muscle RAS oncogene homolog) and KCNE2 (potassium voltage-gated channel, Isk-related family, member 2)] had summary effect sizes in the direction opposite to that described in previous reports. Although it may be tempting to speculate on the reasons for this result, the 95% CI for the summary odds ratios crosses the line of null effect, and the study had limited power to detect overall effects. Therefore, these results should be interpreted with caution. The authors then constructed a simple unweighted genetic risk score (GRS) based on the number of risk alleles carried (each individual will carry 0, 1, or 2 risk alleles at each locus) and assessed the performance of the GRS in predicting CHD. In common with other reports of studies that used a similar methodology, the discriminative performance of the GRS was modest (area under the ROC curve, 0.5782). Addition of the GRS to a panel of clinical risk factors did lead to a modest improvement in both the area under the ROC curve and the net reclassification index. Two important features that could have aided in discrimination but were not included in the clinical parameters are the duration of diabetes in patients who developed CHD and the age of diabetes diagnosis

Utility of genetic and non-genetic risk factors in prediction of type 2 diabetes: Whitehall II prospective cohort study

Objectives To assess the performance of a panel of common single nucleotide polymorphisms (genotypes) associated with type 2 diabetes in distinguishing incident cases of future type 2 diabetes (discrimination), and to examine the effect of adding genetic information to previously validated non-genetic (phenotype based) models developed to estimate the absolute risk of type 2 diabetes

Population genomics of cardiometabolic traits: design of the University College London-London School of Hygiene and Tropical Medicine-Edinburgh-Bristol (UCLEB) Consortium.

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

Sixty-five common genetic variants and prediction of type 2 diabetes.

We developed a 65 type 2 diabetes (T2D) variant-weighted gene score to examine the impact on T2D risk assessment in a U.K.-based consortium of prospective studies, with subjects initially free from T2D (N = 13,294; 37.3% women; mean age 58.5 [38-99] years). We compared the performance of the gene score with the phenotypically derived Framingham Offspring Study T2D risk model and then the two in combination. Over the median 10 years of follow-up, 804 participants developed T2D. The odds ratio for T2D (top vs. bottom quintiles of gene score) was 2.70 (95% CI 2.12-3.43). With a 10% false-positive rate, the genetic score alone detected 19.9% incident cases, the Framingham risk model 30.7%, and together 37.3%. The respective area under the receiver operator characteristic curves were 0.60 (95% CI 0.58-0.62), 0.75 (95% CI 0.73 to 0.77), and 0.76 (95% CI 0.75 to 0.78). The combined risk score net reclassification improvement (NRI) was 8.1% (5.0 to 11.2; P = 3.31 × 10(-7)). While BMI stratification into tertiles influenced the NRI (BMI ≤24.5 kg/m(2), 27.6% [95% CI 17.7-37.5], P = 4.82 × 10(-8); 24.5-27.5 kg/m(2), 11.6% [95% CI 5.8-17.4], P = 9.88 × 10(-5); >27.5 kg/m(2), 2.6% [95% CI -1.4 to 6.6], P = 0.20), age categories did not. The addition of the gene score to a phenotypic risk model leads to a potentially clinically important improvement in discrimination of incident T2D

Integrated associations of genotypes with multiple blood biomarkers linked to coronary heart disease risk

Individuals at risk of coronary heart disease (CHD) show multiple correlations across blood biomarkers. Single nucleotide polymorphisms (SNPs) indexing biomarker differences could help distinguish causal from confounded associations because of their random allocation prior to disease. We examined the association of 948 SNPs in 122 candidate genes with 12 CHD-associated phenotypes in 2775 middle aged men (a genic scan). Of these, 140 SNPs indexed differences in HDL- and LDL-cholesterol, triglycerides, C-reactive protein, fibrinogen, factor VII, apolipoproteins AI and B, lipoprotein-associated phospholipase A2, homocysteine or folate, some with large effect sizes and highly significant P-values (e.g. 2.15 standard deviations at P = 9.2 × 10−140 for F7 rs6046 and FVII levels). Top ranking SNPs were then tested for association with additional biomarkers correlated with the index phenotype (phenome scan). Several SNPs (e.g. in APOE, CETP, LPL, APOB and LDLR) influenced multiple phenotypes, while others (e.g. in F7, CRP and FBB) showed restricted association to the index marker. SNPs influencing six blood proteins were used to evaluate the nature of the associations between correlated blood proteins utilizing Mendelian randomization. Multiple SNPs were associated with CHD-related quantitative traits, with some associations restricted to a single marker and others exerting a wider genetic ‘footprint’. SNPs indexing biomarkers provide new tools for investigating biological relationships and causal links with disease. Broader and deeper integrated analyses, linking genomic with transcriptomic, proteomic and metabolomic analysis, as well as clinical events could, in principle, better delineate CHD causing pathways amenable to treatment

ANGPTL4 variants E40K and T266M are associated with lower fasting triglyceride levels in Non-Hispanic White Americans from the Look AHEAD Clinical Trial

<p>Abstract</p> <p>Background</p> <p>Elevated triglyceride levels are a risk factor for cardiovascular disease. Angiopoietin-like protein 4 (Angptl4) is a metabolic factor that raises plasma triglyceride levels by inhibiting lipoprotein lipase (LPL). In non-diabetic individuals, the <it>ANGPTL4 </it>coding variant E40K has been associated with lower plasma triglyceride levels while the T266M variant has been associated with more modest effects on triglyceride metabolism. The objective of this study was to determine whether ANGPTL4 E40K and T266M are associated with triglyceride levels in the setting of obesity and T2D, and whether modification of triglyceride levels by these genetic variants is altered by a lifestyle intervention designed to treat T2D.</p> <p>Methods</p> <p>The association of <it>ANGPTL4 </it>E40K and T266M with fasting triglyceride levels was investigated in 2,601 participants from the Look AHEAD Clinical Trial, all of whom had T2D and were at least overweight. Further, we tested for an interaction between genotype and treatment effects on triglyceride levels.</p> <p>Results</p> <p>Among non-Hispanic White Look AHEAD participants, <it>ANGPTL4 </it>K40 carriers had mean triglyceride levels of 1.61 ± 0.62 mmol/L, 0.33 mmol/L lower than E40 homozygotes (p = 0.001). Individuals homozygous for the minor M266 allele (MAF 30%) had triglyceride levels of 1.75 ± 0.58 mmol/L, 0.24 mmol/L lower than T266 homozygotes (p = 0.002). The association of the M266 with triglycerides remained significant even after removing K40 carriers from the analysis (p = 0.002). There was no interaction between the weight loss intervention and genotype on triglyceride levels.</p> <p>Conclusions</p> <p>This is the first study to demonstrate that the <it>ANGPTL4 </it>E40K and T266M variants are associated with lower triglyceride levels in the setting of T2D. In addition, our findings demonstrate that <it>ANGPTL4 </it>genotype status does not alter triglyceride response to a lifestyle intervention in the Look AHEAD study.</p

Association of genetic variation with systolic and diastolic blood pressure among African Americans: the Candidate Gene Association Resource study

The prevalence of hypertension in African Americans (AAs) is higher than in other US groups; yet, few have performed genome-wide association studies (GWASs) in AA. Among people of European descent, GWASs have identified genetic variants at 13 loci that are associated with blood pressure. It is unknown if these variants confer susceptibility in people of African ancestry. Here, we examined genome-wide and candidate gene associations with systolic blood pressure (SBP) and diastolic blood pressure (DBP) using the Candidate Gene Association Resource (CARe) consortium consisting of 8591 AAs. Genotypes included genome-wide single-nucleotide polymorphism (SNP) data utilizing the Affymetrix 6.0 array with imputation to 2.5 million HapMap SNPs and candidate gene SNP data utilizing a 50K cardiovascular gene-centric array (ITMAT-Broad-CARe [IBC] array). For Affymetrix data, the strongest signal for DBP was rs10474346 (P= 3.6 × 10−8) located near GPR98 and ARRDC3. For SBP, the strongest signal was rs2258119 in C21orf91 (P= 4.7 × 10−8). The top IBC association for SBP was rs2012318 (P= 6.4 × 10−6) near SLC25A42 and for DBP was rs2523586 (P= 1.3 × 10−6) near HLA-B. None of the top variants replicated in additional AA (n = 11 882) or European-American (n = 69 899) cohorts. We replicated previously reported European-American blood pressure SNPs in our AA samples (SH2B3, P= 0.009; TBX3-TBX5, P= 0.03; and CSK-ULK3, P= 0.0004). These genetic loci represent the best evidence of genetic influences on SBP and DBP in AAs to date. More broadly, this work supports that notion that blood pressure among AAs is a trait with genetic underpinnings but also with significant complexit

Improving Interpretation of Cardiac Phenotypes and Enhancing Discovery With Expanded Knowledge in the Gene Ontology.

BACKGROUND: A systems biology approach to cardiac physiology requires a comprehensive representation of how coordinated processes operate in the heart, as well as the ability to interpret relevant transcriptomic and proteomic experiments. The Gene Ontology (GO) Consortium provides structured, controlled vocabularies of biological terms that can be used to summarize and analyze functional knowledge for gene products. METHODS AND RESULTS: In this study, we created a computational resource to facilitate genetic studies of cardiac physiology by integrating literature curation with attention to an improved and expanded ontological representation of heart processes in the Gene Ontology. As a result, the Gene Ontology now contains terms that comprehensively describe the roles of proteins in cardiac muscle cell action potential, electrical coupling, and the transmission of the electrical impulse from the sinoatrial node to the ventricles. Evaluating the effectiveness of this approach to inform data analysis demonstrated that Gene Ontology annotations, analyzed within an expanded ontological context of heart processes, can help to identify candidate genes associated with arrhythmic disease risk loci. CONCLUSIONS: We determined that a combination of curation and ontology development for heart-specific genes and processes supports the identification and downstream analysis of genes responsible for the spread of the cardiac action potential through the heart. Annotating these genes and processes in a structured format facilitates data analysis and supports effective retrieval of gene-centric information about cardiac defects. Circ Genom Precis Med 2018 Feb; 11(2):e001813