Graduate Program in Genetics, Department of Ecology and Evolution, Stony Brook University, Stony Brook, NY 11794-5222, USA.
BMC Med Genomics. 2010 Dec 10;3:57. doi: 10.1186/1755-8794-3-57.
Genome-wide association studies give insight into the genetic basis of common diseases. An open question is whether the allele frequency distributions and ancestral vs. derived states of disease-associated alleles differ from the rest of the genome. Characteristics of disease-associated alleles can be used to increase the yield of future studies.
The set of all common disease-associated alleles found in genome-wide association studies prior to January 2010 was analyzed and compared with HapMap and theoretical null expectations. In addition, allele frequency distributions of different disease classes were assessed. Ages of HapMap and disease-associated alleles were also estimated.
The allele frequency distribution of HapMap alleles was qualitatively similar to neutral expectations. However, disease-associated alleles were more likely to be low frequency derived alleles relative to null expectations. 43.7% of disease-associated alleles were ancestral alleles. The mean frequency of disease-associated alleles was less than randomly chosen CEU HapMap alleles (0.394 vs. 0.610, after accounting for probability of detection). Similar patterns were observed for the subset of disease-associated alleles that have been verified in multiple studies. SNPs implicated in genome-wide association studies were enriched for young SNPs compared to randomly selected HapMap loci. Odds ratios of disease-associated alleles tended to be less than 1.5 and varied by frequency, confirming previous studies.
Alleles associated with genetic disease differ from randomly selected HapMap alleles and neutral expectations. The evolutionary history of alleles (frequency and ancestral vs. derived state) influences whether they are implicated in genome-wide association studies.
全基因组关联研究揭示了常见疾病的遗传基础。一个悬而未决的问题是,疾病相关等位基因的等位基因频率分布和祖先与衍生状态是否与基因组的其他部分不同。疾病相关等位基因的特征可用于提高未来研究的产量。
分析了 2010 年 1 月之前在全基因组关联研究中发现的所有常见疾病相关等位基因,并将其与 HapMap 和理论无效预期进行了比较。此外,还评估了不同疾病类别的等位基因频率分布。还估计了 HapMap 和疾病相关等位基因的年龄。
HapMap 等位基因的等位基因频率分布在质上与中性预期相似。然而,与无效预期相比,疾病相关等位基因更有可能是低频衍生等位基因。43.7%的疾病相关等位基因是祖先等位基因。疾病相关等位基因的平均频率低于随机选择的 CEU HapMap 等位基因(考虑到检测概率后为 0.394 对 0.610)。在经过多次研究验证的疾病相关等位基因子集上观察到了类似的模式。与随机选择的 HapMap 基因座相比,全基因组关联研究中涉及的 SNPs 富含年轻的 SNPs。疾病相关等位基因的比值比倾向于小于 1.5,并随频率而变化,证实了以前的研究。
与遗传疾病相关的等位基因与随机选择的 HapMap 等位基因和中性预期不同。等位基因的进化历史(频率和祖先与衍生状态)影响它们是否与全基因组关联研究有关。