Gillanders E M, Pearson J V, Sorant A J M, Trent J M, O'Connell J R, Bailey-Wilson J E
Inherited Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, Baltimore, MD 21224, USA.
Am J Hum Genet. 2006 Sep;79(3):458-68. doi: 10.1086/506626. Epub 2006 Jun 28.
Novel methods that could improve the power of conventional methods of gene discovery for complex diseases should be investigated. In a simulation study, we aimed to investigate the value of molecular haplotypes in the context of a family-based linkage study. The term "haplotype" (or "haploid genotype") refers to syntenic alleles inherited on a single chromosome, and we use the term "molecular haplotype" to refer to haplotypes that have been determined directly by use of a molecular technique such as long-range allele-specific polymerase chain reaction. In our study, we simulated genotype and phenotype data and then compared the powers of analyzing these data under the assumptions that various levels of information from molecular haplotypes were available. (This information was available because of the simulation procedure.) Several conclusions can be drawn. First, as expected, when genetic homogeneity is expected or when marker data are complete, it is not efficient to generate molecular haplotyping information. However, with levels of heterogeneity and missing data patterns typical of complex diseases, we observed a 23%-77% relative increase in the power to detect linkage in the presence of heterogeneity with heterogeneity LOD scores >3.0 when all individuals are molecularly haplotyped (compared with the power when only standard genotypes are used). Furthermore, our simulations indicate that most of the increase in power can be achieved by molecularly haplotyping a single individual in each family, thereby making molecular haplotyping a valuable strategy for increasing the power of gene mapping studies of complex diseases. Maximization of power, given an existing family set, can be particularly important for late-onset, often-fatal diseases such as cancer, for which informative families are difficult to collect.
应研究能够提高传统复杂疾病基因发现方法效能的新方法。在一项模拟研究中,我们旨在探讨在基于家系的连锁研究背景下分子单倍型的价值。术语“单倍型”(或“单倍体基因型”)指的是在一条染色体上遗传的同线等位基因,我们使用“分子单倍型”一词来指代通过使用分子技术(如长程等位基因特异性聚合酶链反应)直接确定的单倍型。在我们的研究中,我们模拟了基因型和表型数据,然后在假设可获得来自分子单倍型的不同水平信息的情况下,比较分析这些数据的效能。(由于模拟过程,此信息是可获得的。)可以得出几个结论。首先,正如预期的那样,当预期基因同质性或标记数据完整时,生成分子单倍型信息并不高效。然而,对于复杂疾病典型的异质性水平和缺失数据模式,我们观察到当所有个体都进行分子单倍型分型时,在异质性LOD评分>3.0的情况下检测连锁的效能相对提高了23% - 77%(与仅使用标准基因型时的效能相比)。此外,我们的模拟表明,通过对每个家系中的单个个体进行分子单倍型分型,大部分效能的提高是可以实现的,从而使分子单倍型分型成为提高复杂疾病基因定位研究效能的一种有价值的策略。对于现有家系集而言,效能最大化对于诸如癌症等晚发性、通常致命的疾病可能尤为重要,因为对于这些疾病,难以收集到信息丰富的家系。