Palmer Lyle J, Scurrah Katrina J, Tobin Martin, Patel Sanjay R, Celedon Juan C, Burton Paul R, Weiss Scott T
Channing Laboratory, Brigham & Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA.
BMC Genet. 2003 Dec 31;4 Suppl 1(Suppl 1):S12. doi: 10.1186/1471-2156-4-S1-S12.
The study of change in intermediate phenotypes over time is important in genetics. In this paper we explore a new approach to phenotype definition in the genetic analysis of longitudinal phenotypes. We utilized data from the longitudinal Framingham Heart Study Family Cohort to investigate the familial aggregation and evidence for linkage to change in systolic blood pressure (SBP) over time. We used Gibbs sampling to derive sigma-squared-A-random-effects (SSARs) for the longitudinal phenotype, and then used these as a new phenotype in subsequent genome-wide linkage analyses. Additive genetic effects (sigma2A.time) were estimated to account for approximately 9.2% of the variance in the rate of change of SBP with age, while additive genetic effects (sigma2A) were estimated to account for approximately 43.9% of the variance in SBP at the mean age. The linkage results suggested that one or more major loci regulating change in SBP over time may localize to chromosomes 2, 3, 4, 6, 10, 11, 17, and 19. The results also suggested that one or more major loci regulating level of SBP may localize to chromosomes 3, 8, and 14. Our results support a genetic component to both SBP and change in SBP with age, and are consistent with a complex, multifactorial susceptibility to the development of hypertension. The use of SSARs derived from quantitative traits as input to a conventional linkage analysis appears to be valuable in the linkage analysis of genetically complex traits. We have now demonstrated in this paper the use of SSARs in the context of longitudinal family data.
研究中间表型随时间的变化在遗传学中很重要。在本文中,我们探索了一种在纵向表型的遗传分析中定义表型的新方法。我们利用了弗雷明汉心脏研究家族队列的纵向数据,来研究家族聚集情况以及与收缩压(SBP)随时间变化的连锁证据。我们使用吉布斯采样来推导纵向表型的σ²A随机效应(SSARs),然后在后续的全基因组连锁分析中将这些作为新的表型。估计加性遗传效应(σ2A.time)占SBP随年龄变化率方差的约9.2%,而加性遗传效应(σ2A)估计占平均年龄时SBP方差的约43.9%。连锁结果表明,一个或多个调节SBP随时间变化的主要基因座可能定位于2号、3号、4号、6号、10号、11号、17号和19号染色体。结果还表明,一个或多个调节SBP水平的主要基因座可能定位于3号、8号和14号染色体。我们的结果支持SBP及其随年龄变化存在遗传成分,并且与高血压发生的复杂多因素易感性一致。将从数量性状导出的SSARs用作传统连锁分析的输入,在遗传复杂性状的连锁分析中似乎很有价值。我们现在已在本文中展示了在纵向家族数据背景下使用SSARs的情况。