Coronary artery disease (CAD), one of the most frequent causes of mortality, is the most common type of cardiovascular disease. This condition is characterized by the accumulation of plaques in the coronary artery, leading to blockage of blood flow to the heart. The main symptom of CAD is chest pain caused by blockage of the coronary artery and shortness of breath. HOX transcript antisense RNA gene (HOTAIR) is a long non-coding RNA which is well-known as an oncogene involved in various cancers, such as lung, breast, colorectal, and gastric cancer. We selected six single nucleotide polymorphisms, rs4759314 A>G, rs1899663 G>T, rs920778 T>C, rs7958904 G>C, rs12826786 C>T, and rs874945 C>T, for genotype frequency analysis and assessed the frequency of HOTAIR gene polymorphisms in 442 CAD patients and 418 randomly selected control subjects. To analyze the differences between these two populations, we performed a Student’s t-test, adjusted odds ratio (AOR), 95% confidence intervals (CIs), and ANOVA analysis. According to our baseline characteristic analysis, control subjects and CAD patients were significantly different in hypertension and diabetes mellitus. We also found that the rs4759314 A>G, rs1899663 G>T, and rs12826786 C>T genotypes were strongly associated with CAD susceptibility (AA vs. AG+GG: AOR = 0.608, 95% CI = 0.393−0.940, p = 0.025; GG vs. TT: AOR = 2.276, 95% CI = 1.125−4.607, p = 0.022; CC vs. CT+TT: AOR = 1.366, 95% CI = 1.027−1.818, p = 0.032, respectively). Our data also demonstrated that the genotype of HOTAIR polymorphisms, genotype combination, and haplotype analysis affect disease occurrence. Moreover, these polymorphisms are linked to clinical factors that contribute to disease susceptibility. In conclusion, results from our study suggest that HOTAIR polymorphisms may be useful novel biomarkers for diagnosing CAD.

The most common type of cardiovascular disease is coronary artery disease (CAD), in which a plaque builds up inside the coronary arteries that can lead to a complete blockage of blood flow to the heart, resulting in a heart attack. The CAD may be affected by various factors including age, gender, and lipoprotein disposition as well as genetic factors and metabolic syndrome. In this study, we investigated whether three PAI-1 polymorphisms (−844 G > A, −675 4G > 5G, and +43 G > A) and CAD-related clinical parameters are associated with CAD susceptibility. Genotyping of 463 CAD patients and 401 controls was performed using polymerase chain reaction restriction fragment length polymorphism analysis. We report that the 4G5G genotype (crude odds ratio(COR), 1.392; 95% confidence interval (CI), 1.036–1.871; p = 0.028) and dominant model (4G4G vs. 4G5G + 5G5G; COR, 1.401; 95% CI, 1.060–1.850; p = 0.018; adjust odds ratio, 1.371; 95% CI, 1.027–1.831; p = 0.032) of PAI-1 −675 polymorphisms were associated with increased CAD risk. Haplotype and genotype combinations of PAI-1 −675 and +43 polymorphisms show an increased risk of CAD according to alterations of the −675 polymorphism allele or genotype. Moreover, the PAI-1 -675 polymorphisms show a synergistic effect with the metabolic syndrome component of CAD risk. This study suggests that polymorphisms in the PAI-1 genes along with the metabolic syndrome component of CAD can be useful biomarkers for CAD diagnosis and treatment.

Coronary artery disease (CAD) is a prevalent cardiovascular condition characterized by the accumulation of plaque within coronary arteries. While distinct features of CAD have been reported, the association between genetic factors and CAD in terms of biomarkers was insufficient. This study aimed to investigate the connection between genetic factors and CAD, focusing on the thymidylate synthase (TS) gene, a gene involved in DNA synthesis and one-carbon metabolism. TS plays a critical role in maintaining the deoxythymidine monophosphate (dTMP) pool, which is essential for DNA replication and repair. Therefore, our research targeted single nucleotide polymorphisms that could potentially impact TS gene expression and lead to dysfunction. Our findings strongly associate the TS 1100T>C and 1170A>G genotypes with CAD susceptibility. We observed that TS 1100T>C polymorphisms increased disease susceptibility in several groups, while the TS 1170A>G polymorphism displayed a decreasing trend for disease risk when interacting with clinical factors. Furthermore, our results demonstrate the potential contribution of the TS 1100/1170 haplotypes to disease susceptibility, indicating a synergistic interaction with clinical factors in disease occurrence. Based on these findings, we propose that polymorphisms in the TS gene had the possibility of clinically useful biomarkers for the prevention, prognosis, and management of CAD in the Korean population.

Coronary artery disease (CAD) is a prevalent cardiovascular condition characterized by the accumulation of plaque within coronary arteries. This plaque accumulation obstructs blood flow to the heart, resulting in a heart attack. While distinct features of CAD have been identified, its causes remain largely unclear, with the exception of environmental and nutritional factors. This study aimed to investigate the connection between genetic factors and CAD, focusing on the thymidylate synthase (TS) gene, a gene involved in one-carbon metabolism. Therefore, our research targeted single nucleotide polymorphisms that could potentially impact TS gene expression and lead to dysfunction. Our findings strongly associate the TS 1100T>C and 1170A>G genotypes with CAD susceptibility. We observed that TS 1100T>C polymorphisms increased disease susceptibility in several groups, while the TS 1170A>G polymorphism displayed a decreasing trend for disease risk when interacting with clinical factors. Furthermore, our results demonstrate the potential contribution of the TS 1100/1170 haplotypes to disease susceptibility, indicating a synergistic interaction with clinical factors in disease occurrence. Based on these findings, we propose that polymorphisms in the 3'-UTR miRNA binding site of the TS gene could serve as clinically useful biomarkers for the prevention, prognosis, and management of CAD.

Coronary artery disease (CAD), a leading cause of death worldwide, has a complex etiology comprising both traditional risk factors (type 2 diabetes, dyslipidemia, arterial hypertension, and cigarette smoking) and genetic factors. Vascular endothelial growth factor (VEGF) notably contributes to angiogenesis and endothelial homeostasis. However, little is known about the relationship between CAD and VEGF polymorphisms in Koreans. The aim of this study is to investigate the associations of 2 VEGF promoter region polymorphisms (−1154G>A [rs1570360], −1498T>C [rs833061]) and 4 VEGF 3′-UTR polymorphisms (+936C>T [rs3025039], +1451C>T [rs3025040], +1612G>A [rs10434], and +1725G>A [rs3025053]) with CAD susceptibility in Koreans. We studied 885 subjects: 463 CAD patients and 422 controls. Genotyping was conducted with polymerase chain reaction-restriction fragment length polymorphism analysis and TaqMan allelic discrimination assays, and the genotype frequencies were calculated. We then performed haplotype and genotype combination analyses and measured the associations between VEGF polymorphisms and clinical variables in both the CAD patients and control subjects. We detected statistically significant associations between CAD and certain VEGF allele combinations. In the haplotypes of 5 single-nucleotide polymorphisms, the VEGF allele combination −1154A/+936T was associated with a decreased prevalence of CAD (A-T-T-G-G of VEGF −1154G>A/−1498T>C/+936C>T/+1612G>A/+1725G>A, AOR = 0.077, p = 0.021). In contrast, the VEGF allele combinations −1498T/+1725A and −1498T/+1612A/+1725A were associated with an increased prevalence of CAD (G-T-C-C-A of VEGF −1154G>A/−1498T>C/+936C>T/+1451C>T/+1725G>A, AOR = 1.602, p = 0.047; T-C-C-A-A of VEGF −1498T>C/+936C>T/+1451C>T/+1612G>A/+1725G>A, AOR = 1.582, p = 0.045). Gene–environment combinatorial analysis showed that the combination of the VEGF +1725AA genotype and several clinical factors (e.g., body mass index, hemoglobin A1c, and low-density lipoprotein cholesterol) increased the risk of CAD. Therefore, we suggest that VEGF polymorphisms and clinical factors may impact CAD prevalence.