Department of Biostatistics and Epidemiology, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA.
Genet Epidemiol. 2013 Feb;37(2):152-62. doi: 10.1002/gepi.21700. Epub 2012 Nov 26.
Parent-of-origin effects have been pointed out to be one plausible source of the heritability that was unexplained by genome-wide association studies. Here, we consider a case-control mother-child pair design for studying parent-of-origin effects of offspring genes on neonatal/early-life disorders or pregnancy-related conditions. In contrast to the standard case-control design, the case-control mother-child pair design contains valuable parental information and therefore permits powerful assessment of parent-of-origin effects. Suppose the region under study is in Hardy-Weinberg equilibrium, inheritance is Mendelian at the diallelic locus under study, there is random mating in the source population, and the SNP under study is not related to risk for the phenotype under study because of linkage disequilibrium (LD) with other SNPs. Using a maximum likelihood method that simultaneously assesses likely parental sources and estimates effect sizes of the two offspring genotypes, we investigate the extent of power increase for testing parent-of-origin effects through the incorporation of genotype data for adjacent markers that are in LD with the test locus. Our method does not need to assume the outcome is rare because it exploits supplementary information on phenotype prevalence. Analysis with simulated SNP data indicates that incorporating genotype data for adjacent markers greatly help recover the parent-of-origin information. This recovery can sometimes substantially improve statistical power for detecting parent-of-origin effects. We demonstrate our method by examining parent-of-origin effects of the gene PPARGC1A on low birth weight using data from 636 mother-child pairs in the Jerusalem Perinatal Study.
亲本来源效应被指出是全基因组关联研究无法解释的遗传率的一个合理来源。在这里,我们考虑了一种病例对照母子对设计,用于研究后代基因对新生儿/早期生命障碍或与妊娠相关的疾病的亲本来源效应。与标准病例对照设计相比,病例对照母子对设计包含有价值的父母信息,因此可以对亲本来源效应进行强大的评估。假设研究区域处于哈迪-温伯格平衡状态,在研究的双等位基因座上遗传是孟德尔式的,在源群体中存在随机交配,并且由于与其他 SNP 的连锁不平衡(LD),研究中的 SNP 与研究中的表型风险无关。我们使用一种最大似然方法,同时评估可能的亲本来源,并估计两个后代基因型的效应大小,通过纳入与测试位点 LD 的相邻标记的基因型数据,研究了通过纳入与测试位点 LD 的相邻标记的基因型数据来增加检测亲本来源效应的功效的程度。我们的方法不需要假设结果是罕见的,因为它利用了表型流行率的补充信息。使用模拟 SNP 数据的分析表明,纳入与测试位点 LD 的相邻标记的基因型数据有助于恢复亲本来源信息。这种恢复有时可以大大提高检测亲本来源效应的统计功效。我们通过使用来自耶路撒冷围产期研究的 636 对母子对的数据来检查基因 PPARGC1A 对低出生体重的亲本来源效应,展示了我们的方法。