Genome-wide association experiments have uncovered a slew of cardiometabolic trait-associated variants. This information can be useful in the implementation of new diagnostic and treatment strategies.
Moataz Dowaidar
Abstract
A slew of cardiometabolic trait-associated variants have been discovered thanks to genome-wide association studies. The majority of imputed SNPs are located in the noncoding region, suggesting that noncoding genes are significant. In this sense, lncRNAs are gaining attention due to their biological functions, and rising data suggests that lncRNAs could be able to assist researchers in better understanding the pathogenesis of cardiometabolic disorders. The existing state of knowledge about lncRNAs in cardiometabolic disorders is still in its early stages, and further research will help us better understand how the noncoding sector regulates us. This knowledge would be important in the development of modern diagnosis and treatment methods.Cardiometabolic diseases are the primary cause of death in both developed and developing countries. Cardiometabolic disorders include excessive blood glucose levels, elevated triglycerides and apolipoprotein B-containing lipoproteins, and low high-density lipoproteins, as well as high blood pressure, obesity, and prothrombotic and proinflammatory states. Cardiometabolic diseases are a major economic burden, particularly in low-and middle-income countries, due to the increased risk of coronary heart disease, stroke, peripheral artery disease, renal insufficiency, prothrombotic and inflammatory disorders. Furthermore, cardiometabolic disorders are common, and they are increasing in lockstep with global obesity rates. In addition to conventional and environmental risk factors for cardiometabolic diseases including diabetes, dyslipidemia, hypertension, and obesity, human genome heterogeneity plays a role in disease progression. Many disease-associated single-nucleotide polymorphisms have been identified using genome-wide association studies (GWAS) to improve understanding of cardiometabolic disease pathogenesis (SNPs). The majority of them are present in noncoding elements, with just a few in coding, enabling structural changes in proteins to be used as a basis for reasoning. As a result, the molecular behavior of SNPs must be interpreted accordingly.