ASSESSING THE IMPACT OF GLOBAL VERSUS LOCAL ANCESTRY IN ASSOCIATION STUDIES

这个子项目是许多研究子项目中利用 资源由NIH/NCRR资助的中心拨款提供。子项目和 调查员(PI)可能从NIH的另一个来源获得了主要资金， 并因此可以在其他清晰的条目中表示。列出的机构是 该中心不一定是调查人员的机构。 为了解释种群分层，主成分分析通常使用跨基因组的单核苷酸多态(SNPs)进行。我们使用Framingham GAW16数据来比较由局部染色体区域的SNPs估计的主成分(PC)衡量的本地祖先的表现与通过全基因组SNPs估计的PC测量的全球祖先的表现，以解决潜在的人口分层问题。来自Framingham后代队列的无关成年人的标准化身高残差是根据纵向数据平均得出的。SNP基因型数据的PC被计算来代表个体的祖先，或者1)全局地使用整个基因组中的所有SNP，或者2)局部地使用每条染色体内相邻20 Mbp区域的SNP。我们评估了身高相关性研究中存在差异的程度，这取决于是否将全球PC、本地PC或两者都作为协变量包括在内。本地PC和全球PC之间的相关性很低(r&lt；0.12)，这表明本地和全球血统估计之间的可变性。来自全基因组关联测试的p值的q-q图表明，在没有调整祖先的情况下，I型错误率被夸大了，但可以通过调整本地血统、全球血统或两者都进行合理的控制。在这个欧美人群中可以观察到虚假的关联，关联分析中的种群分层的影响可以通过与当地或全球祖先PC的调整来控制。在这个看似同质的弗雷明翰人口中，人口分层是一个潜在的偏见来源。然而，从SNP衍生的本地和全球PC似乎提供了关于祖先的足够信息。

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. To account for population stratification, principal components analysis is often performed using single nucleotide polymorphisms (SNPs) across the genome. We used Framingham GAW16 data to compare the performance of local ancestry, measured by principal components (PCs) estimated from SNPs in a local chromosomal region, with global ancestry, measured by PCs estimated from genome-wide SNPs, to address underlying population stratification. Standardized height residuals from unrelated adults from the Framingham Offspring Cohort were averaged from longitudinal data. PCs of SNP genotype data were calculated to represent individual's ancestry either 1) globally using all SNPs across the genome or 2) locally using SNPs in adjacent 20 Mbp regions within each chromosome. We assessed the extent to which there are differences in association studies of height depending on whether PCs for global, local or both are included as covariates.The correlations between local and global PCs were low (r < 0.12), suggesting variability between local and global ancestry estimates. Q-Q plots of the p values from genome-wide association tests indicate inflated type I error rate without adjusting for ancestry, but can be reasonably controlled by adjusting for local ancestry, global ancestry, or both. Spurious associations are observable in this European-American population and the effect of population stratification in association analysis can be controlled by adjustment with local or global ancestry PCs. Population stratification is a potential source of bias in this seemingly homogenous Framingham population. However, local and global PCs derived from SNPs appear to provide adequate information about ancestry.