M Agirbasli, A I Guney, H S Ozturhan, D Agirbasli, K Ulucan, D Sevinc, D Kirac, K K Ryckman, S M Williams
{"title":"早发性冠心病患者MTHFR、PAI-1、ACE、PON1和eNOS基因多态性的多因素降维分析","authors":"M Agirbasli, A I Guney, H S Ozturhan, D Agirbasli, K Ulucan, D Sevinc, D Kirac, K K Ryckman, S M Williams","doi":"10.1177/1741826711398806","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Association studies in the Turkish population have investigated the single locus effects of different gene polymorphisms on coronary artery disease (CAD). CAD is a complex polygenic disease that involves complex interactions among multiple genetic and environmental conditions.</p><p><strong>Design: </strong>We evaluated associations of five candidate genetic polymorphisms (methylene tetrahydrofolate reductase C677T, plasminogen activator inhibitor 4G/5G, endothelial nitric oxide synthase (eNOS) 3-27 base pair repeat, insertion, or deletion of a 287 bp Alu repeat sequence polymorhism of angiotensin I converting enzyme, and paraoxonase Gln192Arg PON1 polymorphisms) with the presence and extent of early onset CAD.</p><p><strong>Methods: </strong>DNA was isolated and amplified from 90 consecutive patients with angiographically proven early onset CAD (ages 41 ± 5 for men, 49 ± 7 for women) and also from 90 control subjects with no significant coronary obstruction angiographically (ages 42 ± 5 for men, 48 ± 6 for women). Multifactor dimensionality reduction (MDR) analysis was performed to identify a model of CAD based on both genetic and conventional risk factors.</p><p><strong>Results: </strong>MDR analysis detected a significant model with four genes (prediction success ∼ 61%, p = 0.03). When the total number of the conventional risk factors is analysed with the candidate polymorphisms, a different model is identified that includes three of the four genes from the above model and achieves a similar prediction of CAD as the gene only model.</p><p><strong>Conclusion: </strong>These data indicate that gene-gene and gene-environmental risk interactions form significant models in predicting early onset CAD.</p>","PeriodicalId":50492,"journal":{"name":"European Journal of Cardiovascular Prevention & Rehabilitation","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/1741826711398806","citationCount":"34","resultStr":"{\"title\":\"Multifactor dimensionality reduction analysis of MTHFR, PAI-1, ACE, PON1, and eNOS gene polymorphisms in patients with early onset coronary artery disease.\",\"authors\":\"M Agirbasli, A I Guney, H S Ozturhan, D Agirbasli, K Ulucan, D Sevinc, D Kirac, K K Ryckman, S M Williams\",\"doi\":\"10.1177/1741826711398806\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Association studies in the Turkish population have investigated the single locus effects of different gene polymorphisms on coronary artery disease (CAD). CAD is a complex polygenic disease that involves complex interactions among multiple genetic and environmental conditions.</p><p><strong>Design: </strong>We evaluated associations of five candidate genetic polymorphisms (methylene tetrahydrofolate reductase C677T, plasminogen activator inhibitor 4G/5G, endothelial nitric oxide synthase (eNOS) 3-27 base pair repeat, insertion, or deletion of a 287 bp Alu repeat sequence polymorhism of angiotensin I converting enzyme, and paraoxonase Gln192Arg PON1 polymorphisms) with the presence and extent of early onset CAD.</p><p><strong>Methods: </strong>DNA was isolated and amplified from 90 consecutive patients with angiographically proven early onset CAD (ages 41 ± 5 for men, 49 ± 7 for women) and also from 90 control subjects with no significant coronary obstruction angiographically (ages 42 ± 5 for men, 48 ± 6 for women). Multifactor dimensionality reduction (MDR) analysis was performed to identify a model of CAD based on both genetic and conventional risk factors.</p><p><strong>Results: </strong>MDR analysis detected a significant model with four genes (prediction success ∼ 61%, p = 0.03). When the total number of the conventional risk factors is analysed with the candidate polymorphisms, a different model is identified that includes three of the four genes from the above model and achieves a similar prediction of CAD as the gene only model.</p><p><strong>Conclusion: </strong>These data indicate that gene-gene and gene-environmental risk interactions form significant models in predicting early onset CAD.</p>\",\"PeriodicalId\":50492,\"journal\":{\"name\":\"European Journal of Cardiovascular Prevention & Rehabilitation\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1177/1741826711398806\",\"citationCount\":\"34\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"European Journal of Cardiovascular Prevention & Rehabilitation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1177/1741826711398806\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2011/2/22 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"European Journal of Cardiovascular Prevention & Rehabilitation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/1741826711398806","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2011/2/22 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 34
摘要
背景:土耳其人群的关联研究调查了不同基因多态性对冠状动脉疾病(CAD)的单位点效应。CAD是一种复杂的多基因疾病,涉及多种遗传和环境条件之间的复杂相互作用。设计:我们评估了五种候选遗传多态性(亚甲基四氢叶酸还原酶C677T,纤溶酶原激活物抑制剂4G/5G,内皮一氧化氮合酶(eNOS) 3-27碱基对重复,血管紧张素I转换酶的287 bp Alu重复序列多态性的插入或缺失,以及对氧核糖核酸酶Gln192Arg PON1多态性)与早发性CAD的存在和程度的关联。方法:从连续90例经血管造影证实的早发性CAD患者(男性41±5岁,女性49±7岁)和90例无明显冠状动脉阻塞的对照受试者(男性42±5岁,女性48±6岁)中分离并扩增DNA。采用多因素降维分析(MDR)确定了基于遗传和常规危险因素的CAD模型。结果:MDR分析检测到包含四个基因的显著模型(预测成功率为61%,p = 0.03)。当使用候选多态性分析常规风险因素的总数时,确定了一个不同的模型,该模型包含上述模型中四个基因中的三个,并实现了与仅基因模型相似的CAD预测。结论:这些数据表明基因-基因和基因-环境风险相互作用是预测早发性CAD的重要模型。
Multifactor dimensionality reduction analysis of MTHFR, PAI-1, ACE, PON1, and eNOS gene polymorphisms in patients with early onset coronary artery disease.
Background: Association studies in the Turkish population have investigated the single locus effects of different gene polymorphisms on coronary artery disease (CAD). CAD is a complex polygenic disease that involves complex interactions among multiple genetic and environmental conditions.
Design: We evaluated associations of five candidate genetic polymorphisms (methylene tetrahydrofolate reductase C677T, plasminogen activator inhibitor 4G/5G, endothelial nitric oxide synthase (eNOS) 3-27 base pair repeat, insertion, or deletion of a 287 bp Alu repeat sequence polymorhism of angiotensin I converting enzyme, and paraoxonase Gln192Arg PON1 polymorphisms) with the presence and extent of early onset CAD.
Methods: DNA was isolated and amplified from 90 consecutive patients with angiographically proven early onset CAD (ages 41 ± 5 for men, 49 ± 7 for women) and also from 90 control subjects with no significant coronary obstruction angiographically (ages 42 ± 5 for men, 48 ± 6 for women). Multifactor dimensionality reduction (MDR) analysis was performed to identify a model of CAD based on both genetic and conventional risk factors.
Results: MDR analysis detected a significant model with four genes (prediction success ∼ 61%, p = 0.03). When the total number of the conventional risk factors is analysed with the candidate polymorphisms, a different model is identified that includes three of the four genes from the above model and achieves a similar prediction of CAD as the gene only model.
Conclusion: These data indicate that gene-gene and gene-environmental risk interactions form significant models in predicting early onset CAD.