Establishment of Relational Model of Congenital Heart Disease Markers and GO Functional Analysis of the Association between Its Serum Markers and Susceptibility Genes.
Establishment of Relational Model of Congenital Heart Disease Markers and GO Functional Analysis of the Association between Its Serum Markers and Susceptibility Genes.
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DOI：
10.1155/2016/9506829
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发表时间：
2016
影响因子：
--
通讯作者：
Yuan J
中科院分区：
文献类型：
--
作者：
Liu M;Zhao L;Yuan J
目的。本研究旨在构建先天性心脏病血清标志物的最佳筛选模型，为进一步预防和治疗先天性心脏病提供参考。方法：研究方法。收集2006-2014年间的文献，应用Meta分析筛选与先天性心脏病诊断密切相关的易感基因和血清标志物。分别提取80例先天性心脏病患者和80例健康对照的血清标志物数据，利用Logistic回归分析和支持向量机建立血清标志物预测模型和基因本体论(GO)功能标注。结果。结果表明，NKX2.5、GATA4和FOG2是先天性心脏病的易感基因。CRP、BNP和cTnI是先天性心脏病的危险因素(p<；0.05)，cTnI、hs-CRP、BNP和Lp(A)与先天性心脏病密切相关(p<；0.01)。ROC曲线显示，Lp(A)与cTnI、Lp(A)与BNP、BNP与cTnI联合预测的准确率分别为93.4%、87.1%、97.2%。而支持向量机建立的标记物关系模型的检测准确率仅为85%。GO分析表明，NKX2.5、GATA4和FOG2与Lp(A)和BNP在功能上相关。结论。BNP和cTnI联合标志物模型准确率最高，为先天性心脏病的诊断提供了理论依据。
Purpose. The purpose of present study was to construct the best screening model of congenital heart disease serum markers and to provide reference for further prevention and treatment of the disease. Methods. Documents from 2006 to 2014 were collected and meta-analysis was used for screening susceptibility genes and serum markers closely related to the diagnosis of congenital heart disease. Data of serum markers were extracted from 80 congenital heart disease patients and 80 healthy controls, respectively, and then logistic regression analysis and support vector machine were utilized to establish prediction models of serum markers and Gene Ontology (GO) functional annotation. Results. Results showed that NKX2.5, GATA4, and FOG2 were susceptibility genes of congenital heart disease. CRP, BNP, and cTnI were risk factors of congenital heart disease (p < 0.05); cTnI, hs-CRP, BNP, and Lp(a) were significantly close to congenital heart disease (p < 0.01). ROC curve indicated that the accuracy rate of Lp(a) and cTnI, Lp(a) and BNP, and BNP and cTnI joint prediction was 93.4%, 87.1%, and 97.2%, respectively. But the detection accuracy rate of the markers' relational model established by support vector machine was only 85%. GO analysis suggested that NKX2.5, GATA4, and FOG2 were functionally related to Lp(a) and BNP. Conclusions. The combined markers model of BNP and cTnI had the highest accuracy rate, providing a theoretical basis for the diagnosis of congenital heart disease.