The association of functional polymorphisms in genes expressed in endothelial cells and smooth muscle cells with the myocardial infarction

Hypoxia-inducible factor-1: Regulatory mechanisms and drug therapy in myocardial infarction

Myocardial infarction (MI), an acute cardiovascular disease characterized by coronary artery blockage, inadequate blood supply, and subsequent ischemic necrosis of the myocardium, is one of the leading causes of death. The cellular, physiological, and pathological responses following MI are complex, involving multiple intertwined pathological mechanisms. Hypoxia-inducible factor-1 (HIF-1), a crucial regulator of hypoxia, plays a significant role in of the development of MI by modulating the behavior of various cells such as cardiomyocytes, endothelial cells, macrophages, and fibroblasts under hypoxic conditions. HIF-1 regulates various post-MI adaptive reactions to acute ischemia and hypoxia through various mechanisms. These mechanisms include angiogenesis, energy metabolism, oxidative stress, inflammatory response, and ventricular remodeling. With its crucial role in MI, HIF-1 is expected to significantly influence the treatment of MI. However, the drugs available for the treatment of MI targeting HIF-1 are currently limited, and most contain natural compounds. The development of precision-targeted drugs modulating HIF-1 has therapeutic potential for advancing MI treatment research and development. This study aimed to summarize the regulatory role of HIF-1 in the pathological responses of various cells following MI, the diverse mechanisms of action of HIF-1 in MI, and the potential drugs targeting HIF-1 for treating MI, thus providing the theoretical foundations for potential clinical therapeutic targets.

A synthesis of pathways linking diet, metabolic risk and cardiovascular disease: a framework to guide further research and approaches to evidence-based practice

Cardiovascular disease (CVD) is the most common non-communicable disease occurring globally. Although previous literature has provided useful insights into the important role that diet plays in CVD prevention and treatment, understanding the causal role of diets is a difficult task considering inherent and introduced weaknesses of observational (e.g. not properly addressing confounders and mediators) and experimental research designs (e.g. not appropriate or well designed). In this narrative review, we organised current evidence linking diet, as well as conventional and emerging physiological risk factors, with CVD risk, incidence and mortality in a series of diagrams. The diagrams presented can aid causal inference studies as they provide a visual representation of the types of studies underlying the associations between potential risk markers/factors for CVD. This may facilitate the selection of variables to be considered and the creation of analytical models. Evidence depicted in the diagrams was systematically collected from studies included in the British Nutrition Task Force report on diet and CVD and database searches, including Medline and Embase. Although several markers and disorders linked to conventional and emerging risk factors for CVD were identified, the causal link between many remains unknown. There is a need to address the multifactorial nature of CVD and the complex interplay between conventional and emerging risk factors with natural and built environments, while bringing the life course into the spotlight.

Association of an ADRB3 Variant with Coronary Artery Disease Within the Chinese Han Population: Construction of a Predictive Nomogram Model

Objective: Coronary artery disease (CAD) is a the most common type of heart disease, and is associated with the highest mortality rate. The role of the β₃-adrenergic receptor gene (ADRB3) in energy homeostasis and lipolysis suggests that it may be associated with obesity, insulin resistance, diabetes, and hypertension. Herein, we sought to examine the relationship between CAD and variants of the ADRB3 gene in individuals with Han and Uygur ethnicities in China. Methods: All 1022 participants were genotyped for two ADRB3 single nucleotide polymorphisms (SNPs; rs1892818 and rs9693898) using real-time polymerase chain reaction (TaqMan). Uygur (259 CAD patients, 161 control group) and Han (308 CAD patients, 294 control group) were included in two case-control studies. We subsequently developed a predictive model using ADRB3 genetic variation and clinical variables to predict risk of CAD. Results: The rs1892818 CT genotype (8.5% vs 3.9%, p = 0.019) and T allele (4.3% vs 1.9%, p = 0.021) were more frequently detected in the control subjects compared to CAD patients of the Han population but not in the Uygur population. The rs9693898 was not associated with CAD in either ethnic population. Logistic regression analysis further demonstrated that carriers of the rs1892818 CT genotype had a lower risk of CAD than did those with the CC genotype (CT vs CC, p = 0.044, odds ratio [OR] = 0.441, 95% confidence interval [CI]: 0.199-0.976). Using this data, we constructed a predictive nomogram model for CAD with an area under the curve (95% CI) of 0.722 (0.682, 0.761). Conclusions: Our results suggest that rs1892818 is associated with CAD in the Han population and that the CT genotype of rs1892818 may serve as a protective factor for CAD in Han individuals. The proposed nomograms can be used for the prediction of CAD in this population.