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Genetic and environmental influences on total plasma homocysteine and its role in coronary artery disease risk
Authors:Ghassibe-Sabbagh Michella,Platt Daniel E,Youhanna Sonia,Abchee Antoine B,Stewart Krista,Badro Danielle A,Haber Marc,Salloum Angelique K,Douaihy Bouchra,el Bayeh Hamid,Othman Raed,Shasha Nabil,Kibbani Samer,Chammas Elie,Milane Aline,Nemr Rita,Kamatani Yoichiro,Hager Jörg,Cazier Jean-Baptiste,Gauguier Dominique,Zalloua Pierre A  FGENTCARD Consortium
Affiliation:Lebanese American University, School of Medicine, Beirut 1102 2801, Lebanon.
Abstract:BackgroundElevated levels of total plasma homocysteine are a risk factor for atherosclerotic disease.AimsThe rationale behind this study is to explore the correlation between degree and site of coronary lesion and hyperhomocysteinemia in Lebanese CAD patients and assess environmental and genetic factors for elevated levels of total plasma homocysteine.MethodsA total of 2644 patients were analyzed for traditional CAD risk factors. Logistic regression was performed to determine the association of hyperhomocysteinemia with degree and site of coronary lesions controlling for risk factors. Environmental and genetic factors for hyperhomocysteinemia were analyzed by logistic regression using a candidate gene approach.ResultsTraditional risk factors were correlated with stenosis. Hyperhomocysteinemia associated with increased risk of overall stenosis, and risk of mild and severe occlusion in major arteries. Hyperhomocysteinemia and hypertension were highly correlated suggesting that hyperhomocysteinemia acts as a hypertensive agent leading to CAD. Diuretics and genetic polymorphisms in MTHFR and SLCO1B1 were associated with hyperhomocysteinemia.ConclusionsHyperhomocysteinemia is a medical indicator of specific vessel stenosis in the Lebanese population. Hypertension is a major link between hyperhomocysteinemia and CAD occurrence. Genetic polymorphisms and diuretics’ intake explain partly elevated homocysteine levels. This study has important implications in CAD risk prediction.
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