International Journal of Molecular Medical Science, 2024, Vol.14, No.1, 69-79 http://medscipublisher.com/index.php/ijmms 70 practitioners, promote the further development of genomics in the field of cardiovascular disease prevention, and make contributions to reducing the incidence rate and mortality of cardiovascular disease and improving human health. 1 The Relationship Between Genomics and Cardiovascular Disease 1.1 Overview of the genetic basis of cardiovascular diseases Cardiovascular disease is a complex disease that often involves the interaction of multiple genetic and environmental factors in its occurrence and development. Genetic factors play an important role in the occurrence of cardiovascular diseases, which has been widely studied and clinically proven. With the rapid development of genomics technology, the understanding of the genetic basis of cardiovascular diseases is also constantly deepening. Genetic basis refers to genes and their variations associated with specific diseases or traits. In cardiovascular diseases, many genes and their variations have been found to be closely related to susceptibility, age of onset, disease progression, and prognosis. For example, Hopewell et al. (2017) found that certain gene variants, such as PCSK9, increase the risk of coronary heart disease, stroke or hypertension, because they affect atherosclerosis and coronary heart disease by regulating cholesterol metabolism. PCSK9 affects cholesterol metabolism, leading to an increase in LDL cholesterol levels and may exacerbate the development of coronary heart disease by promoting thrombosis and inflammatory response. Yin et al. (2013) found that different allele variations in the Apolipoprotein E gene, particularly ε The 4-allele gene is associated with an increased risk of cardiovascular disease, as ε The 4 alleles have adverse effects on cholesterol metabolism and lipid transport. In existence ε In the case of 4-allele genes, energy supply may decrease and support for neurons may weaken, which may exacerbate the development of cardiovascular disease. Ference et al. (2016) found that HMGCR has similar, independent and cumulative effects on reducing cardiovascular events and diabetes risk per unit of low density lipoprotein cholesterol level. 3-hydroxy-3-methylglutaryl CoA reductase (HMG-CoA reductase) is a key enzyme in cholesterol synthesis, and therefore, mutations in the HMGCR gene affect its activity or are associated with cholesterol levels and cardiovascular disease risk. Genomic technologies, particularly genome-wide association studies (GWAS) and single gene genetic disease studies, provide powerful tools for revealing the genetic basis of cardiovascular diseases. GWAS can identify multiple gene regions associated with cardiovascular disease risk by detecting single nucleotide polymorphisms (SNPs) and other variations in the genome on a large scale. Defesche (2017) discussed that single gene genetic disease research focuses on cardiovascular diseases caused by single gene mutations, such as familial hypercholesterolemia and Marfan's syndrome. It is worth noting that although genomics has revealed many genetic variations related to cardiovascular disease, the genetic mechanisms of cardiovascular disease are still far from fully understood. This is mainly because cardiovascular disease is a polygenic genetic disease, which involves the synergistic effects of multiple genes and complex interactions with environmental factors (Figure 1). Therefore, future research needs to explore the interaction between genes and the environment on a broader scale in order to gain a deeper understanding of the genetic basis of cardiovascular disease. 1.2 How genomics reveals the genetic mechanisms of cardiovascular diseases Genomics can deeply reveal the genetic mechanisms of cardiovascular diseases through various methods such as GWAS, sequence analysis, comprehensive genetic and epigenetic data, single gene genetic disease research, gene expression analysis, and genome-environment interaction research. GWAS is a powerful tool for identifying genetic variations associated with specific diseases or traits. By extensively detecting variations such as single nucleotide polymorphisms (SNPs) in the genome, GWAS can identify multiple gene regions associated with cardiovascular disease risk, disease progression, and prognosis. McPherson et al. (2006) reported an association between the 9p21.3 region and the risk of coronary artery disease, which is an early example of using the GWAS method.
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