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

Human paraoxonase gene cluster polymorphisms as predictors of coronary heart disease risk in the prospective Northwick Park Heart Study II

AbstractThe anti-atherogenic effect of HDL has been suggested to be partly due to the action of HDL-associated paraoxonase (PON). Three distinct enzymes have been identified, encoded by PON1, PON2 and PON3, clustered on chromosome 7q21–q22. Two cSNPs in PON1 (L55M and Q192R) and one in PON2 (S311C) have been implicated as independent risk factors for coronary heart disease (CHD) in some, but not all, studies. A PON3 SNP (A99A) was identified and the effect of these four PON SNPs on HDL levels and CHD risk was examined in the prospective Northwick Park Heart Study II (NPHSII). Genotype frequencies did not differ between cases and controls but the CHD risk associated with smoking was significantly modified by PON1 L55M genotype. Compared to LL non-smokers, LL smokers had a hazard ratio (HR) of 1.30 (95% CI 0.81–2.06) while M-allele carriers had a HR of 1.76 (1.17–2.67). When genotypes were analysed in combination, men with the genotype PON1 55 LM/MM+PON2 311 CC, had HR of 3.54 (1.81–6.93) compared to PON1 LL+PON2 SS/SC men (interaction P=0.004). These effects were independent of classical risk factors. These data demonstrate the importance of stratifying by environmental factors and the use of multiple SNPs for genetic analysis

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

The representation of heart development in the gene ontology

AbstractAn understanding of heart development is critical in any systems biology approach to cardiovascular disease. The interpretation of data generated from high-throughput technologies (such as microarray and proteomics) is also essential to this approach. However, characterizing the role of genes in the processes underlying heart development and cardiovascular disease involves the non-trivial task of data analysis and integration of previous knowledge. The Gene Ontology (GO) Consortium provides structured controlled biological vocabularies that are used to summarize previous functional knowledge for gene products across all species. One aspect of GO describes biological processes, such as development and signaling.In order to support high-throughput cardiovascular research, we have initiated an effort to fully describe heart development in GO; expanding the number of GO terms describing heart development from 12 to over 280. This new ontology describes heart morphogenesis, the differentiation of specific cardiac cell types, and the involvement of signaling pathways in heart development. This work also aligns GO with the current views of the heart development research community and its representation in the literature. This extension of GO allows gene product annotators to comprehensively capture the genetic program leading to the developmental progression of the heart. This will enable users to integrate heart development data across species, resulting in the comprehensive retrieval of information about this subject.The revised GO structure, combined with gene product annotations, should improve the interpretation of data from high-throughput methods in a variety of cardiovascular research areas, including heart development, congenital cardiac disease, and cardiac stem cell research. Additionally, we invite the heart development community to contribute to the expansion of this important dataset for the benefit of future research in this area

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

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

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

The impact of focused Gene Ontology curation of specific mammalian systems.

The Gene Ontology (GO) resource provides dynamic controlled vocabularies to provide an information-rich resource to aid in the consistent description of the functional attributes and subcellular locations of gene products from all taxonomic groups (www.geneontology.org). System-focused projects, such as the Renal and Cardiovascular GO Annotation Initiatives, aim to provide detailed GO data for proteins implicated in specific organ development and function. Such projects support the rapid evaluation of new experimental data and aid in the generation of novel biological insights to help alleviate human disease. This paper describes the improvement of GO data for renal and cardiovascular research communities and demonstrates that the cardiovascular-focused GO annotations, created over the past three years, have led to an evident improvement of microarray interpretation. The reanalysis of cardiovascular microarray datasets confirms the need to continue to improve the annotation of the human proteome. AVAILABILITY: GO ANNOTATION DATA IS FREELY AVAILABLE FROM: ftp://ftp.geneontology.org/pub/go/gene-associations