A cladistic analysis of phenotypic associations with haplotypes inferred from restriction endonuclease mapping or DNA sequencing. V. Analysis of case/control sampling designs: Alzheimer's disease and the apoprotein E locus.
A cladistic analysis of phenotypic associations with haplotypes inferred from restriction endonuclease mapping or DNA sequencing. V. Analysis of case/control sampling designs: Alzheimer's disease and the apoprotein E locus.
复制标题
DOI：
10.1093/genetics/140.1.403
复制
发表时间：
1995-05
期刊：
影响因子：
3.3
通讯作者：
Alan R. Templeton
中科院分区：
文献类型：
--
作者：
Alan R. Templeton
在当前的遗传变异进化过程中，当重要的表型突变发生时，候选位点上的单倍型与表型之间存在关联。可以通过使用候选DNA区域的进化史来定义一个分支统计设计，以集中力量。本文展示了如何使用进化方法分析病例/对照数据，这是遗传/疾病关联研究中常见的抽样设计。本文提出了一个实例，说明散发性早发性和晚发性阿尔茨海默病与19q13.2染色体区域（包括载脂蛋白E、CI和CII位点）之间的关联。这一分析证实了早前关于ApoE ε 4等位基因与阿尔茨海默病密切相关的报道，但表明认为这种关联是因果关系还为时过早，特别是对于早发病例。与先前报道的epsilon 2等位基因和ApoCI位点的1等位基因也存在关联。然而，该分析表明，当单倍型数据可用时，使用单个标记作为风险预测因子在统计学和医学上都是不合适的，即使导致该标记的突变被确定为具有很强的表型关联。
Present-day associations between haplotypes at a candidate locus and phenotypes exist when phenotypically important mutations occurred at some point during the evolution of the current array of genetic variation. A cladistic statistical design can be defined that focuses power by using the evolutionary history of the candidate DNA region. This paper shows how cladistic methodology is used for the analysis of case/control data, a common sampling design in genetic/disease association studies. A worked example is presented of the associations for sporadic early and late-onset forms of Alzheimer's disease with the 19q13.2 chromosomal region that includes the loci for apoproteins E, CI, and CII. This analysis confirms earlier reports of a strong association of the ApoE epsilon 4 allele with Alzheimer's disease but indicates that it is premature to consider this association causal, particularly for early onset cases. Associations were also found with the epsilon 2 allele, as previously reported, and with the 1 allele at the ApoCI locus. However, this analysis indicates that it is inappropriate both statistically and medically to use single markers as risk predictors when haplotype data are available, even when the mutation leading to the marker is identified as having a strong phenotypic association.