Rao Shaoqi, Li Lin, Li Xia, Moser Kathy L, Guo Zheng, Shen Gongqing, Cannata Ruth, Zirzow Erich, Topol Eric J, Wang Qing
Center for Cardiovascular Genetics, Department of Cardiovascular Medicine, The Cleveland Clinic Foundation, 9500 Euclid Avenue, Cleveland, Ohio, USA.
BMC Genet. 2003 Dec 31;4 Suppl 1(Suppl 1):S24. doi: 10.1186/1471-2156-4-S1-S24.
Longitudinal data often have multiple (repeated) measures recorded along a time trajectory. For example, the two cohorts from the Framingham Heart Study (GAW13 Problem 1) contain 21 and 5 repeated measures for hypertension phenotypes as well as epidemiological risk factors, respectively. Direct modelling of a large number of serially and biologically correlated traits in the context of linkage analysis can be prohibitively complex. Alternatively, we may consider using univariate transformation for linkage analysis of longitudinal repeated measures.
We evaluated the utility of three conventional summary measures (mean, slope, and principal components) for genetic linkage analysis of longitudinal phenotypes by analyzing the chromosome 10 data of the Framingham Heart Study. Except for the temporal slope, all of the summary methods and the multivariate analysis identified the previously reported region, marker GATA64A09, for systolic blood pressure or high blood pressure. Further analysis revealed that this region may harbor gene(s) affecting human blood pressure at multiple stages of life.
We conclude that mean and principal components are feasible alternatives for genetic linkage analysis of longitudinal phenotypes, but the slope might have a separate genetic basis from that of the original longitudinal phenotypes.
纵向数据通常沿着时间轨迹记录有多个（重复）测量值。例如，弗明汉心脏研究（GAW13问题1）中的两个队列分别包含21个和5个关于高血压表型以及流行病学危险因素的重复测量值。在连锁分析的背景下，对大量序列相关且生物学相关的性状进行直接建模可能极其复杂。另外，我们可以考虑使用单变量变换对纵向重复测量值进行连锁分析。
通过分析弗明汉心脏研究的10号染色体数据，我们评估了三种传统汇总测量值（均值、斜率和主成分）在纵向表型遗传连锁分析中的效用。除了时间斜率外，所有汇总方法和多变量分析均确定了先前报道的收缩压或高血压区域，即标记GATA64A09。进一步分析表明，该区域可能含有在生命多个阶段影响人类血压的基因。
我们得出结论，均值和主成分是纵向表型遗传连锁分析的可行替代方法，但斜率可能具有与原始纵向表型不同的遗传基础。
