Genomics of premature atherosclerotic vascular disease

Integrated omics analysis of coronary artery calcifications and myocardial infarction: the Framingham Heart Study

Gene function can be described using various measures. We integrated association studies of three types of omics data to provide insights into the pathophysiology of subclinical coronary disease and myocardial infarction (MI). Using multivariable regression models, we associated: (1) single nucleotide polymorphism, (2) DNA methylation, and (3) gene expression with coronary artery calcification (CAC) scores and MI. Among 3106 participants of the Framingham Heart Study, 65 (2.1%) had prevalent MI and 60 (1.9%) had incident MI, median CAC value was 67.8 [IQR 10.8, 274.9], and 1403 (45.2%) had CAC scores > 0 (prevalent CAC). Prevalent CAC was associated with AHRR (linked to smoking) and EXOC3 (affecting platelet function and promoting hemostasis). CAC score was associated with VWA1 (extracellular matrix protein associated with cartilage structure in endomysium). For prevalent MI we identified FYTTD1 (down-regulated in familial hypercholesterolemia) and PINK1 (linked to cardiac tissue homeostasis and ischemia-reperfusion injury). Incident MI was associated with IRX3 (enhancing browning of white adipose tissue) and STXBP3 (controlling trafficking of glucose transporter type 4 to plasma). Using an integrative trans-omics approach, we identified both putatively novel and known candidate genes associated with CAC and MI. Replication of findings is warranted.

Novel lipid biomarkers and ratios as risk predictors for premature coronary artery disease: A retrospective analysis of 2952 patients

This study examined the associations between emerging lipid biomarkers (small dense low-density lipoprotein cholesterol [sdLDL-C), lipoprotein(a) [Lp(a)], and free fatty acids [FFA]), two ratios (sdLDL-C/LDL-C and the triglyceride-glucose [TyG) index), and the Gensini score (GS) in patients with premature coronary artery disease (PCAD) in relation to the extent of coronary stenosis. The authors evaluated a cohort of 2952 individuals undergoing coronary angiography (CAG), encompassing those with PCAD (n = 1749), late-onset coronary artery disease (LCAD; n = 328), and non-coronary artery disease (non-CAD; n = 575). Noteworthy differences were observed in the levels of the novel lipid biomarkers and ratio indexes among the PCAD, LCAD, and non-CAD groups (p < .05). Multiple logistic regression analyses pinpointed Lp(a) (OR = 2.62, 95% CI 1.22-5.63, p = .014) and the TyG index (OR = 2.53, 95% CI 1.08-5.93, p = .033) as independent risk factors for PCAD. Furthermore, these biomarkers and ratio indexes discerned substantial distinctions among PCAD patients with varying GS (p < .05). Consequently, these markers can proficiently anticipate the gravity of coronary artery stenosis (GS > 40) in PCAD patients, as evidenced by the ROC analysis. In conclusion, sdLDL-C, Lp(a), FFA, and the sdLDL-C/LDL-C and TyG indexes have considerable potential as risk and diagnostic markers for coronary artery stenosis in individuals afflicted with PCAD.

Comparison of demographic, psychosocial, and clinical characteristics among younger and older persons with acute coronary syndrome

PURPOSE

The aim of this study was to examine the differences in demographic, psychosocial (depression), and clinical profiles among younger (males ≤ 50 years of age and females ≤ 55 years of age) and older (males > 50 years of age and females > 55 years of age) patients with acute coronary syndrome (ACS).

DATA SOURCES

This study is a preliminary analysis of data collected from 1140 patients with ACS enrolled in an ongoing longitudinal investigation.

CONCLUSIONS

As compared to their older counterparts, younger ACS patients were significantly more likely to be obese (p < .001), to smoke (p < .001), to have a higher BDI-II depression score (p < .001), and to feel depressed in the last year (p < .001). In contrast, younger ACS patients were significantly less likely to be dyslipidemic (p < .001), diabetic (p = 0.025), or hypertensive (p < .001) than their older counterparts.

IMPLICATIONS FOR PRACTICE

Clinicians need to be persistent in promoting the importance of weight loss and smoking cessation. Screening and treating depression in younger persons is a prudent approach. The significance of regular screening and aggressive treatment of other risk factors (i.e., diabetes, hypertension, and dyslipidemia) should not be overlooked.

Cardiovascular genomics: a biomarker identification pipeline

Genomic biomarkers are essential for understanding the underlying molecular basis of human diseases such as cardiovascular disease. In this review, we describe a biomarker identification pipeline for cardiovascular disease, which includes 1) high-throughput genomic data acquisition, 2) preprocessing and normalization of data, 3) exploratory analysis, 4) feature selection, 5) classification, and 6) interpretation and validation of candidate biomarkers. We review each step in the pipeline, presenting current and widely used bioinformatics methods. Furthermore, we analyze several publicly available cardiovascular genomics datasets to illustrate the pipeline. Finally, we summarize the current challenges and opportunities for further research.

New technologies personalize diagnostics and therapeutics

Atherosclerotic cardiovascular disease remains the leading cause of morbidity and mortality in industrialized societies [10]. Efforts to reduce cardiovascular events in "high-risk" individuals or recurrent events in patients with established atherosclerotic cardiovascular disease emphasize broad-based implementation of guideline-directed therapeutic lifestyle changes and pharmacotherapy. Despite successful implementation of these evidence-based strategies, many individuals are not properly identified before their first event or they continue to experience cardiovascular events despite "optimal" levels of biomarkers. The application of genomics, proteomics, and metabolomics provides opportunities to improve our understanding of the complex process of atherosclerosis and enables personalized diagnostic and therapeutic approaches.