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弗雷明汉心脏研究中受试者纵向收缩压表型的全基因组扫描连锁分析结果。

Genome scan linkage results for longitudinal systolic blood pressure phenotypes in subjects from the Framingham Heart Study.

作者信息

James Katherine, Weitzel Lindsay-Rae B, Engelman Corinne D, Zerbe Gary, Norris Jill M

机构信息

Department of Preventive Medicine and Biometrics, University of Colorado Health Sciences Center, Denver, Colorado, USA.

出版信息

BMC Genet. 2003 Dec 31;4 Suppl 1(Suppl 1):S83. doi: 10.1186/1471-2156-4-S1-S83.

Abstract

The relationship between elevated blood pressure and cardiovascular and cerebrovascular disease risk is well accepted. Both systolic and diastolic hypertension are associated with this risk increase, but systolic blood pressure appears to be a more important determinant of cardiovascular risk than diastolic blood pressure. Subjects for this study are derived from the Framingham Heart Study data set. Each subject had five records of clinical data of which systolic blood pressure, age, height, gender, weight, and hypertension treatment were selected to characterize the phenotype in this analysis. We modeled systolic blood pressure as a function of age using a mixed modeling methodology that enabled us to characterize the phenotype for each individual as the individual's deviation from the population average rate of change in systolic blood pressure for each year of age while controlling for gender, body mass index, and hypertension treatment. Significant (p = 0.00002) evidence for linkage was found between this normalized phenotype and a region on chromosome 1. Similar linkage results were obtained when we estimated the phenotype while excluding values obtained during hypertension treatment. The use of linear mixed models to define phenotypes is a methodology that allows for the adjustment of the main factor by covariates. Future work should be done in the area of combining this phenotype estimation directly with the linkage analysis so that the error in estimating the phenotype can be properly incorporated into the genetic analysis, which, at present, assumes that the phenotype is measured (or estimated) without error.

摘要

血压升高与心血管和脑血管疾病风险之间的关系已得到广泛认可。收缩压和舒张压升高均与这种风险增加相关,但收缩压似乎比舒张压更是心血管风险的一个更重要决定因素。本研究的受试者来自弗雷明汉心脏研究数据集。每个受试者有五条临床数据记录,在本分析中选择了收缩压、年龄、身高、性别、体重和高血压治疗情况来表征表型。我们使用混合建模方法将收缩压建模为年龄的函数,该方法使我们能够将每个个体的表型表征为该个体相对于各年龄每年收缩压总体平均变化率的偏差,同时控制性别、体重指数和高血压治疗情况。在这个标准化表型与1号染色体上的一个区域之间发现了显著的(p = 0.00002)连锁证据。当我们在排除高血压治疗期间获得的值的情况下估计表型时,得到了类似的连锁结果。使用线性混合模型来定义表型是一种允许通过协变量调整主要因素的方法。未来的工作应该在将这种表型估计直接与连锁分析相结合的领域中进行,以便在估计表型时产生的误差能够被恰当地纳入遗传分析中,目前遗传分析假定表型的测量(或估计)没有误差。

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