Multiple phenotype modeling in gene-mapping studies of quantitative traits: Power advantages
Multiple phenotype modeling in gene-mapping studies of quantitative traits: Power advantages
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DOI：
10.1086/302038
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发表时间：
1998-10-01
影响因子：
9.8
通讯作者：
Schork, NJ
中科院分区：
文献类型：
--
作者：
Allison, DB;Thiel, B;Schork, NJ
全基因组搜索影响复杂的人类特征和疾病，如糖尿病，高血压和肥胖症的基因座往往困扰低功率和解释的困难。解决这些困难的尝试通常依赖于新的主题确定方案、更大的样本量、更大密度的DNA标记物以及更复杂的统计建模和分析策略，并促进了这些方案的使用。其中许多补救措施的实施成本可能很高。我们研究了一个简单的统计模型的效用，将多个表型或诊断终点的基因定位分析的数量性状基因座的映射。该方法考虑寻找多个表型值的线性组合，最大限度地提高与基因座连锁的证据。我们的研究结果表明，显着增加的权力映射位点可以获得与所提出的技术，虽然权力的增加是一个功能的大小和方向的剩余相关性之间的表型分析中使用。广泛的模拟研究，证明这些索赔，在两个表型的措施进行了分析的情况下。这种方法可以很容易地扩展到涵盖更复杂的情况，并可能为更有见地的遗传分析范式提供基础。
Genomewide searches for loci influencing complex human traits and diseases such as diabetes, hypertension, and obesity are often plagued by low power and interpretive difficulties. Attempts to remedy these difficulties have typically relied on, and have promoted the use of, novel subject-ascertainment schemes, larger sample sizes, a greater density of DNA markers, and more-sophisticated statistical modeling and analysis strategies. Many of these remedies can be costly to implement. We investigate the utility of a simple statistical model for the mapping of quantitative-trait loci that incorporates multiple phenotypic or diagnostic endpoints into a gene-mapping analysis. The approach considers finding a linear combination of multiple phenotypic values that maximizes the evidence for linkage to a locus. Our results suggest that substantial increases in the power to map loci can be obtained with the proposed technique, although the increase in power obtained is a function of the size and direction of the residual correlation among the phenotypes used in the analysis. Extensive simulation studies are described that justify these claims, for cases in which two phenotypic measures are analyzed. This approach can be easily extended to cover more-complex situations and may provide a basis for more insightful genetic-analysis paradigms.