Multivariate Analysis of Candidate Blood Pressure Response Genes in Hypertensives

高血压候选血压反应基因的多变量分析

• 批准号: 7530626
• 负责人: Andrei Rodin
• 金额: $ 7.5万
• 依托单位: UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-30 至 2011-09-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7530626
• 关键词: Accounting; Algorithms; Antihypertensive Agents; Attention; Biological; Blood Pressure; Candidate Disease Gene; Data; Data Analyses; Data Set; Decision Trees; Dependency; Engineering; Environmental Risk Factor; Generations; Genes; Genetic; Genetic Epistasis; Genetic Heterogeneity; Genetic Variation; Genotype; Goals; Guidelines; Hybrids; Hydrochlorothiazide; Hypertension; Individual; Joints; Kidney; Knowledge; Literature; Measures; Methodology; Methods; Modeling; Multivariate Analysis; Other Genetics; Pathway interactions; Pharmaceutical Preparations; Phenotype; Physiological; Plant Roots; Probability; Renin-Angiotensin-Aldosterone System; Role; Sampling; Series; Simulate; Sodium; Staging; Statistical Methods; System; Systems Biology; Testing; Thiazide Diuretics; Tubular formation; Variant; complex biological systems; computer based statistical methods; computer science; data mining; follow-up; genetic analysis; genetic epidemiology; heuristics; improved; innovation; insight; interest; network models; reconstruction; response; thiazide; tool

DESCRIPTION (provided by applicant): The primary goal of this project is to reverse-engineer the interplay of gene variation (in candidate genes influencing renal tubular sodium transport and involved in renin-angiotensin-aldosterone system) and other variables contributing to the interindividual differences in blood pressure (BP) response to a thiazide diuretic. We will apply "pathway", or "systems biology", data analysis methods to the association study of BP response to a hydrochlorothiazide in 585 hypertensive individuals. Previously, they have been genotyped for genetic variation in 16 candidate genes, and measured for a number of intermediate phenotypes and other variables. A series of univariate analyses have been carried out, and a small number of statistically significant predictors of blood pressure response (and certain other intermediate phenotypes of interest) have been identified. However, the scope of these analyses was very limited. We intend to follow up with the multivariate analysis in order to gain the systemic understanding of the dataset and the underlying biological pathways. We intend to apply innovative multivariate analysis methods, predominantly Bayesian Network (BN) modeling and boosted classifiers / clusterers, to the data. Such data mining methods have been very successful when applied to the similar datasets in other domains. Finally, we will use this dataset to confirm, in the context of genetic epidemiology, the practical utility of BN modeling with respect to sensitivity and robustness. We will also investigate various technical aspects of BN reconstruction, as applied to the genetic data.

描述（由申请人提供）： 该项目的主要目标是反向工程基因变异的相互作用（在候选基因影响肾小管钠转运和参与肾素-血管紧张素-醛固酮系统）和其他变量有助于血压（BP）对噻嗪类利尿剂反应的个体间差异。我们将应用“通路”或“系统生物学”的数据分析方法对585例高血压患者的血压对氢氯噻嗪的反应进行关联研究。以前，他们已经在16个候选基因中进行了遗传变异的基因分型，并测量了一些中间表型和其他变量。已经进行了一系列单变量分析，并且已经确定了少数具有统计学意义的血压反应预测因子（以及某些其他感兴趣的中间表型）。然而，这些分析的范围非常有限。我们打算跟进多变量分析，以获得数据集和潜在的生物学途径的系统性理解。我们打算将创新的多变量分析方法，主要是贝叶斯网络（BN）建模和提升分类器/聚类器，数据。这种数据挖掘方法在其他领域的类似数据集上得到了很好的应用。最后，我们将使用这个数据集来确认，在遗传流行病学的背景下，BN建模的灵敏度和鲁棒性方面的实际效用。我们还将研究BN重建的各种技术方面，如应用于遗传数据。