Sergi Sayols-Baixeras

Pathogenesis of coronary artery disease: focus on genetic risk factors and identification of genetic variants

Coronary artery disease (CAD) is the leading cause of death and disability worldwide, and its prevalence is expected to increase in the coming years. CAD events are caused by the interplay of genetic and environmental factors, the effects of which are mainly mediated through cardiovascular risk factors. The techniques used to study the genetic basis of these diseases have evolved from linkage studies to candidate gene studies and genome-wide association studies. Linkage studies have been able to identify genetic variants associated with monogenic diseases, whereas genome-wide association studies have been more successful in determining genetic variants associated with complex diseases. Currently, genome-wide association studies have identified approximately 40 loci that explain 6% of the heritability of CAD. The application of this knowledge to clinical practice is challenging, but can be achieved using various strategies, such as genetic variants to identify new therapeutic targets, personal genetic information to improve disease risk prediction, and pharmacogenomics. The main aim of this narrative review is to provide a general overview of our current understanding of the genetics of coronary artery disease and its potential clinical utility.

Epigenome-wide association study identifies TXNIP gene associated with type 2 diabetes mellitus and sustained hyperglycemia

Type 2 diabetes mellitus (DM) is an established risk factor for a wide range of vascular diseases, including ischemic stroke (IS). Glycated hemoglobin A1c (HbA1c), a marker for average blood glucose levels over the previous 12 weeks, is used as a measure of glycemic control and also as a diagnostic criterion for diabetes (HbA1c levels ≥ 6.5%). Epigenetic mechanisms, such as DNA methylation, may be associated with aging processes and with modulation of the risk of various pathologies, such as DM. Specifically, DNA methylation could be one of the mechanisms mediating the relation between DM and environmental exposures. Our goal was to identify new CpG methylation sites associated with DM. We performed a genome-wide methylation study in whole-blood DNA from an IS patient cohorts. Illumina HumanMethylation450 BeadChip array was used to measure DNA methylation in CpG sites. All statistical analyses were adjusted for sex, age, hyperlipidemia, body mass index (BMI), smoking habit and cell count. Findings were replicated in two independent cohorts, an IS cohort and a population-based cohort, using the same array. In the discovery phase (N = 355), we identified a CpG site, cg19693031 (located in the TXNIP gene) that was associated with DM (P = 1.17 × 10(-12)); this CpG was replicated in two independent cohorts (N = 167 and N = 645). Methylation of TXNIP was inversely and intensely associated with HbA1c levels (P = 7.3 × 10(-16)), specifically related to diabetic patients with poor control of glucose levels. We identified an association between the TXNIP gene and DM through epigenetic mechanisms, related to sustained hyperglycemia levels (HbA1c ≥ 7%).

Identification and validation of seven new loci showing differential DNA methylation related to serum lipid profile: an epigenome-wide approach. The REGICOR study.

Lipid traits (total, low-density and high-density lipoprotein cholesterol, and triglycerides) are risk factors for cardiovascular disease. DNA methylation is not only an inherited but also modifiable epigenetic mark that has been related to cardiovascular risk factors. Our aim was to identify loci showing differential DNA methylation related to serum lipid levels. Blood DNA methylation was assessed using the Illumina Human Methylation 450 BeadChip. A two-stage epigenome-wide association study was performed, with a discovery sample in the REGICOR study (n = 645) and validation in the Framingham Offspring Study (n = 2,542). Fourteen CpG sites located in nine genes (SREBF1, SREBF2, PHOSPHO1, SYNGAP1, ABCG1, CPT1A, MYLIP, TXNIP and SLC7A11) and 2 intergenic regions showed differential methylation in association with lipid traits. Six of these genes and 1 intergenic region were new discoveries showing differential methylation related to total cholesterol (SREBF2), HDL-cholesterol (PHOSPHO1, SYNGAP1 and an intergenic region in chromosome 2) and triglycerides (MYLIP, TXNIP and SLC7A11). These CpGs explained 0.7%, 9.5% and 18.9% of the variability of total cholesterol, HDL cholesterol and triglycerides in the Framingham Offspring Study, respectively. The expression of the genes SREBF2 and SREBF1 was inversely associated with methylation of their corresponding CpGs (P-value = 0.0042 and 0.0045, respectively) in participants of the GOLDN study (n = 98). In turn, SREBF1 expression was directly associated with HDL cholesterol (P-value = 0.0429). Genetic variants in SREBF1, PHOSPHO1, ABCG1 and CPT1A were also associated with lipid profile. Further research is warranted to functionally validate these new loci and assess the causality of new and established associations between these differentially methylated loci and lipid metabolism.

Association between DNA methylation and coronary heart disease or other atherosclerotic events: A systematic review

BACKGROUND AND AIMS The aim of this study was to perform a systematic review of the association between DNA methylation and coronary heart disease (CHD) or related atherosclerotic traits. METHODS A systematic review was designed. The condition of interest was DNA methylation, and the outcome was CHD or other atherosclerosis-related traits. Three DNA methylation approaches were considered: global methylation, candidate-gene, and epigenome-wide association studies (EWAS). A functional analysis was undertaken using the Ingenuity Pathway Analysis software. RESULTS In total, 51 articles were included in the analysis: 12 global methylation, 34 candidate-gene and 11 EWAS, with six studies using more than one approach. The results of the global methylation studies were inconsistent. The candidate-gene results were consistent for some genes, suggesting that hypermethylation in ESRα, ABCG1 and FOXP3 and hypomethylation in IL-6 were associated with CHD. The EWAS identified 84 genes showing differential methylation associated with CHD in more than one study. The probability of these findings was <1.37·10-5. One third of these genes have been related to obesity in genome-wide association studies. The functional analysis identified several diseases and functions related to these set of genes: inflammatory, metabolic and cardiovascular disease. CONCLUSIONS Global DNA methylation seems to be not associated with CHD. The evidence from candidate-gene studies was limited. The EWAS identified a set of 84 genes highlighting the relevance of obesity, inflammation, lipid and carbohydrate metabolism in CHD. This set of genes could be prioritized in future studies assessing the role of DNA methylation in CHD.

Identification of a new locus and validation of previously reported loci showing differential methylation associated with smoking. The REGICOR study

Smoking increases the risk of many diseases and could act through changes in DNA methylation patterns. The aims of this study were to determine the association between smoking and DNA methylation throughout the genome at cytosine-phosphate-guanine (CpG) site level and genomic regions. A discovery cross-sectional epigenome-wide association study nested in the follow-up of the REGICOR cohort was designed and included 645 individuals. Blood DNA methylation was assessed using the Illumina HumanMethylation450 BeadChip. Smoking status was self-reported using a standardized questionnaire. We identified 66 differentially methylated CpG sites associated with smoking, located in 38 genes. In most of these CpG sites, we observed a trend among those quitting smoking to recover methylation levels typical of never smokers. A CpG site located in a novel smoking-associated gene (cg06394460 in LNX2) was hypomethylated in current smokers. Moreover, we validated two previously reported CpG sites (cg05886626 in THBS1, and cg24838345 in MTSS1) for their potential relation to atherosclerosis and cancer diseases, using several different approaches: CpG site methylation, gene expression, and plasma protein level determinations. Smoking was also associated with higher THBS1 gene expression but with lower levels of thrombospondin-1 in plasma. Finally, we identified differential methylation regions in 13 genes and in four non-coding RNAs. In summary, this study replicated previous findings and identified and validated a new CpG site located in LNX2 associated with smoking.

Prevalence and prognosis of high-risk myocardial infarction patient candidates to extended antiplatelet therapy.

INTRODUCTION AND OBJECTIVES Secondary prevention in myocardial infarction patients is paramount to prevent recurrences. Dual antiplatelet therapy has been shown to reduce the risk of subsequent events up to 1 year and beyond in the PEGASUS-TIMI 54 trial. This study aimed to estimate the annual number of myocardial infarction patients with PEGASUS characteristics in Spain and to analyze short- and long-term outcomes in these patients. METHODS The number of myocardial infarction patients was estimated assuming a Poisson distribution. Myocardial infarction incidence and mortality rates obtained from population registries (IBERICA and REGICOR) were properly adjusted. The proportion of myocardial infarction patients with PEGASUS characteristics was estimated with a REGICOR cohort of consecutive patients from 2003-2009 (n=1391). This cohort follow-up was used to compare the occurrence of reinfarction and death at 1 year and at the end of the follow-up (4.7 years) in patients with and without PEGASUS characteristics by Cox regression. RESULTS The estimated annual number of stable myocardial infarction patients aged ≥ 50 years and without bleeding events was 41 311. Of these, 22 493 had at least 1 PEGASUS characteristic (diabetes, previous myocardial infarction, or chronic kidney disease). At 4.7 years of follow-up, having any PEGASUS characteristic or age ≥ 65 years was associated with a higher risk of cardiovascular and all-cause death in adjusted analyses (hazard ratio=3.44 and 2.21, 95% confidence interval, 1.22-9.74 and 1.11-4.42, respectively). CONCLUSIONS In Spain, more than 50% of the stable myocardial infarction patients aged ≥ 50 years are estimated to have at least 1 PEGASUS characteristic, which substantially increases the long-term risk of cardiovascular and all-cause death.

Ischemic stroke patients are biologically older than their chronological age

Ischemic stroke is associated with aging. It is possible to predict chronological age by measuring age-related changes in DNA methylation from multiple CpG sites across the genome, known as biological age. The difference between biological age and actual chronological age would indicate an individuals level of aging. Our aim was to determine the biological age of ischemic stroke patients and compare their aging with controls of the same chronological age. A total of 123 individuals, 41 controls and 82 patients with ischemic stroke were paired by chronological age, ranging from 39 to 82 years. Illumina HumanMethylation450 BeadChip array was used to measure DNA methylation in CpG sites in both groups, and biological age was estimated using methylation values of specific CpGs. Ischemic stroke patients were biologically an average 2.5 years older than healthy controls (p-value=0.010). Stratified by age tertiles, younger stroke patients (≤57 years old) were biologically older than controls (OR=1.19; 95%CI 1.00-1.41, p-value=0.046). The older groups showed no biological age differences between cases and controls, but were close to reaching the significance level. Ischemic stroke patients are biologically older than controls. Biological age should be considered as a potential new biomarker of stroke risk.

DNA methylation and exposure to ambient air pollution in two prospective cohorts

Long-term exposure to air pollution has been associated with several adverse health effects including cardiovascular, respiratory diseases and cancers. However, underlying molecular alterations remain to be further investigated. The aim of this study is to investigate the effects of long-term exposure to air pollutants on (a) average DNA methylation at functional regions and, (b) individual differentially methylated CpG sites. An assumption is that omic measurements, including the methylome, are more sensitive to low doses than hard health outcomes. This study included blood-derived DNA methylation (Illumina-HM450 methylation) for 454 Italian and 159 Dutch participants from the European Prospective Investigation into Cancer and Nutrition (EPIC). Long-term air pollution exposure levels, including NO2, NOx, PM2.5, PMcoarse, PM10, PM2.5 absorbance (soot) were estimated using models developed within the ESCAPE project, and back-extrapolated to the time of sampling when possible. We meta-analysed the associations between the air pollutants and global DNA methylation, methylation in functional regions and epigenome-wide methylation. CpG sites found differentially methylated with air pollution were further investigated for functional interpretation in an independent population (EnviroGenoMarkers project), where (N = 613) participants had both methylation and gene expression data available. Exposure to NO2 was associated with a significant global somatic hypomethylation (p-value = 0.014). Hypomethylation of CpG islands shores and shelves and gene bodies was significantly associated with higher exposures to NO2 and NOx. Meta-analysing the epigenome-wide findings of the 2 cohorts did not show genome-wide significant associations at single CpG site level. However, several significant CpG were found if the analyses were separated by countries. By regressing gene expression levels against methylation levels of the exposure-related CpG sites, we identified several significant CpG-transcript pairs and highlighted 5 enriched pathways for NO2 and 9 for NOx mainly related to the immune system and its regulation. Our findings support results on global hypomethylation associated with air pollution, and suggest that the shores and shelves of CpG islands and gene bodies are mostly affected by higher exposure to NO2 and NOx. Functional differences in the immune system were suggested by transcriptome analyses.

Epigenetics of Lipid Phenotypes

Dyslipidemia is a well-established risk factor for cardiovascular disease, the main cause of death worldwide. Blood lipid profiles are patterned by both genetic and environmental factors. In recent years, epigenetics has emerged as a paradigm that unifies these influences. In this review, we have summarized the latest evidence implicating epigenetic mechanisms—DNA methylation, histone modification, and regulation by RNAs—in lipid homeostasis. Key findings have emerged in a number of novel epigenetic loci located in biologically plausible genes (eg, CPT1A, ABCG1, SREBF1, and others), as well as microRNA-33a/b. Evidence from animal and cell culture models suggests a complex interplay between different classes of epigenetic processes in the lipid-related genomic regions. Although epigenetic findings hold the potential to explain the interindividual variability in lipid profiles as well as the underlying mechanisms, they have yet to be translated into effective therapies for dyslipidemia.

The Genetics of Ischemic Heart Disease: From Current Knowledge to Clinical Implications

Ischemic heart disease continues to cause high morbidity and mortality. Its prevalence is expected to increase due to population aging, and its prevention is a major goal of health policies. The risk of developing ischemic heart disease is related to a complex interplay between genetic, environmental, and lifestyle factors. In the last decade, considerable progress has been made in knowledge of the genetic architecture of this disease. This narrative review provides an overview of current knowledge of the genetics of ischemic heart disease and of its translation to clinical practice: identification of new therapeutic targets, assessment of the causal relationship between biomarkers and disease, improved risk prediction, and identification of responders and nonresponders to specific drugs (pharmacogenomics).