The rs2516839 Polymorphism of the USF1 Gene May Modulate Serum Triglyceride Levels in Response to Cigarette Smoking

Polymorphic Variants of AGT, ABCA1, and CYBA Genes Influence the Survival of Patients with Coronary Artery Disease: A Prospective Cohort Study

Genetic factors can influence the risk of coronary artery disease (CAD) and the survival of patients. Our previous research led to the identification of genetic variants predisposing to CAD in the Polish population. Since many of them affect the clinical phenotype of the disease, the aim of this study was searching for genetic factors potentially influencing survival in patients with CAD. The study included 276 patients hospitalized due to coronary artery disease. The database of medical history and genotypic results of 29 polymorphisms were used. The endpoint was defined as death from cardiovascular causes. Survival was defined as the period from angiographic confirmation of CAD to death from cardiovascular causes. Three of all the analyzed genes were associated with survival. In the case of the AGT (rs699) and ABCA1 (rs2230806) genes polymorphisms, the risk of death was higher in GG homozygotes compared to the A allele carriers in the 10-year period. In the case of the CYBA (rs72811418) gene polymorphism, the effect on mortality was shown in both 5- and 10-year periods. The TA heterozygotes were predisposed to a higher risk of death than the TT homozygotes. Concluding, the AGT, ABCA1, and CYBA genes polymorphisms influence the risk of death in patients with CAD.

An updated analysis on the association of GSTM1 polymorphism and smoking exposure with the increased risk of coronary heart disease

Objective

To undertake a meta-analysis to investigate if there is an association between the glutathione S-transferase mu 1 (GSTM1) gene polymorphism, coronary artery disease (CAD) susceptibility and smoking.

Methods

Electronic databases, including PubMed®, Web of Science and Embase®, were searched for relevant case–control studies. Data were extracted and the odds ratio (OR) was calculated and appropriate statistical methods were used for the meta-analysis.

Results

The analysis included eight studies with a total of 1880 cases with CAD and 1758 control subjects. The results of this meta-analysis demonstrated that there is no association between the GSTM1 null and CAD (OR 1.24, 95% confidence interval [CI] 1.00, 1.55). An increased risk of CAD was observed in the smoking population with the GSTM1 null genotype (OR 1.48, 95% CI 1.02, 2.15). Subgroup analyses of geographical region, genotyping method and publication language category demonstrated potential relationships among gene polymorphism, smoking and CAD.

Conclusions

Based on the current literature, the GSTM1 null genotype was associated to CAD in the smoking population. The interaction between smoking and GSTM1 polymorphism may contribute to the susceptibility of CAD.

Association of common gene-smoking interactions with elevated plasma apolipoprotein B concentration

Background

Increased apolipoprotein (apo) B level (hyperapoB) is a strong predictor of cardiovascular disease (CVD), even in patients who achieve recommended LDL-Cholesterol (LDL-C) goals. ApoB level, an important correlate of metabolic syndrome (MetS), is influenced by several gene-environment interactions. Some of them are rare and can explain a large proportion of apoB variance, whereas others more common have variable effects. The aim of this study was to evaluate the association of interaction between smoking and common hyperapoB gene variants (PPARα-L162V, lipoprotein lipase loss-of function mutation, apo e4 allele or apo E2/2 genotype) with plasma apoB concentrations, according to the expression of MetS.

Methods

This study was performed among 1798 subjects. Smoking was defined as non/mild smokers vs. moderate-to-heavy smokers. ApoB levels were determined using nephelometry. Logistic regression models were used to document interactions between smoking habits and the presence of hyperapoB gene variants on the relative odds to exhibit increased plasma apoB concentrations.

Results

Around 29% of individuals with a low-risk lipid profile without MetS component had hyperapoB. Smoking and the presence of hyperapoB gene variants tended to be associated with higher plasma apoB levels even in presence of low-LDL-C. There was a significant interaction (P = 0.04) between the presence of ≥1 gene variants and smoking on the risk to exhibit hyperapoB among subjects with low risk profile in primary prevention.

Conclusions

Combination of life habits assessment and some common genes variants may detect a significant proportion of patients with increased apoB levels, and therefore a higher risk of CVD, who could have been initially perceived as low-risk.

Gene-environment interactions due to quantile-specific heritability of triglyceride and VLDL concentrations

"Quantile-dependent expressivity" is a dependence of genetic effects on whether the phenotype (e.g., triglycerides) is high or low relative to its distribution in the population. Quantile-specific offspring-parent regression slopes (β_OP) were estimated by quantile regression for 6227 offspring-parent pairs. Quantile-specific heritability (h²), estimated by 2β_OP/(1 + r_spouse), decreased 0.0047 ± 0.0007 (P = 2.9 × 10^-14) for each one-percent decrement in fasting triglyceride concentrations, i.e., h² ± SE were: 0.428 ± 0.059, 0.230 ± 0.030, 0.111 ± 0.015, 0.050 ± 0.016, and 0.033 ± 0.010 at the 90th, 75th, 50th, 25th, and 10th percentiles of the triglyceride distribution, respectively. Consistent with quantile-dependent expressivity, 11 drug studies report smaller genotype differences at lower (post-treatment) than higher (pre-treatment) triglyceride concentrations. This meant genotype-specific triglyceride changes could not move in parallel when triglycerides were decreased pharmacologically, so that subtracting pre-treatment from post-treatment triglyceride levels necessarily created a greater triglyceride decrease for the genotype with a higher pre-treatment value (purported precision-medicine genetic markers). In addition, sixty-five purported gene-environment interactions were found to be potentially attributable to triglyceride's quantile-dependent expressivity, including gene-adiposity (APOA5, APOB, APOE, GCKR, IRS-1, LPL, MTHFR, PCSK9, PNPLA3, PPARγ2), gene-exercise (APOA1, APOA2, LPL), gene-diet (APOA5, APOE, INSIG2, LPL, MYB, NXPH1, PER2, TNFA), gene-alcohol (ALDH2, APOA5, APOC3, CETP, LPL), gene-smoking (APOC3, CYBA, LPL, USF1), gene-pregnancy (LPL), and gene-insulin resistance interactions (APOE, LPL).

Bioinformatics Analysis of the Effects of Tobacco Smoke on Gene Expression

This study was designed to explore the effects of tobacco smoke on gene expression through bioinformatics analyses. Gene expression profile GSE17913 was downloaded from the Gene Expression Omnibus database. The differentially expressed genes (DEGs) in buccal mucosa tissues between 39 active smokers and 40 never smokers were identified. Gene Ontology Specifically, the DEG distribution in the pathway of Metabolism of xenobiotics by cytochrome P450 was shown in Fig 2[corrected] were performed, followed by protein-protein interaction (PPI) network, transcriptional regulatory network as well as miRNA-target regulatory network construction. In total, 88 up-regulated DEGs and 106 down-regulated DEGs were identified. Among these DEGs, cytochrome P450, family 1, subfamily A, polypeptide 1 (CYP1A1) and CYP1B1 were enriched in the Metabolism of xenobiotics by cytochrome P450 pathway. In the PPI network, tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein, zeta (YWHAZ), and CYP1A1 were hub genes. In the transcriptional regulatory network, transcription factors of MYC associated factor X (MAX) and upstream transcription factor 1 (USF1) regulated many overlapped DEGs. In addition, protein tyrosine phosphatase, receptor type, D (PTPRD) was regulated by multiple miRNAs in the miRNA-DEG regulatory network. CYP1A1, CYP1B1, YWHAZ and PTPRD, and TF of MAX and USF1 may have the potential to be used as biomarkers and therapeutic targets in tobacco smoke-related pathological changes.