Abstract P3007: Relationship between ET-1 Gene Polymorphism rs5370 and Cardiovascular Disease among Hispanics Using All of Us data

Background: The Hispanic population in the continental US has grown by 23% over the last decade. Cardiovascular disease (CVD) remains the leading cause of death in this group, affecting 42.7% of Hispanic women and 52.3% of Hispanic men. Endothelin-1 (ET-1), a potent vasoconstrictor, is proposed as a novel biomarker for cardiovascular risk prediction. The ET-1 genetic polymorphism rs5370 involves a substitution of Guanine by Thymine at codon 198. This polymorphism appears to play a role in developing CVD risk factors. However, it has not been studied in the Hispanic population. Hypothesis: ET-1 gene polymorphism in Hispanics will be associated with CVD and can be used as a CVD risk factor to assess Hispanic persons clinically. Methods: This study included 73,491 Hispanic participants from the All of Us data. ET-1 genotypes were assessed for CVD risk factors (hypertension, obesity, and T2DM) and CVD (disorders of the cardiovascular system, HF, myocardial infarction, cerebrovascular accident, and cerebral infarction) in the Hispanic population. Fischer's exact test and multinomial logistic regression were applied to predict the association between ET-1 gene polymorphism rs5370 and CVD. Preliminary Results: The ET-1 gene polymorphism rs5370, which has a frequency of 19.77% in the Hispanic population, was found to be associated with a risk for hypertension (OR=1.214, p<.0001), obesity (OR=1.194, p<.0001), and T2DM (OR=1.152, p<.0001). Additionally, it was associated with a risk for disorders of the cardiovascular system (OR= 1.290, p<.0001), myocardial infarction (OR=1.117, p<.05), cerebrovascular accident (OR=1.231, p<.001), and cerebral infarction (OR=1.227, p<.0001). However, the polymorphism was not found to be associated with HF. Conclusions: The association of ET1 gene polymorphism rs5370 with CVD in the Hispanic population is a significant finding. Screening for this polymorphism could potentially identify vulnerable populations at risk for CVD, leading to targeted interventions and early detection.