Statistical Methods For Genetic Epidemiology

尽管已经进行了广泛的GWAS研究，将遗传变异与疾病联系起来，取得了一些进展，但已知的变异只能解释大多数可遗传健康状况的一小部分遗传性。先天缺陷，唇裂，就是一个很好的例子。已知在随后的兄弟姐妹中复发的风险约为30-40倍，但已知的变异几乎不能解释这种复发。考虑到许多生物途径中设计的保护性冗余，可能在这种缺陷表达之前，某些特定的snp必须共同存在。考虑到这些因素，环境暴露可能也很重要。我们的算法能够模拟具有真实连锁结构的基因组数据，为我们开发评估GxGxG相互作用和GxGxE相互作用的新方法提供了实验室。该方法现在能够识别多个上位性途径，其中某些变异snp的同时存在会给结果带来风险。我们现在回到了裂点数据，并在亚洲数据和欧洲数据中分别挖掘了上位性。

Despite some advances due to the extensive GWAS studies that have been done to associate genetic variants with diseases, the known variants have only explained a small proportion of the heritability of most heritable health conditions. The birth defect, oral cleft, is a good example. The recurrence risk is known to be about 30-40 fold in a subsequent sibling, but known variants explain little of that recurrence. Given the protective redundancy designed into many biologic pathways, it may be that certain particular SNPs must be jointly present before this defect is expressed. Given that combination, an environmental exposure might also be important. The availability of our algorithm for simulating genomic data with realistic linkage structure provides us with a laboratory for development of new methods for assessing both GxGxG interactions and GxGxE interactions. The method is now able to identify multiple epistatic pathways where the simultaneous presence of certain variant SNPs confers risk for the outcome. We have now gone back to the clefting data and mined for epistasis there, separately in the Asian data and the European data. Using our (publicly available) simulation algorithm to create toy data sets, we have refined our machine-learning approach to stochastically search for multi-SNP effects. This paper represents an important advance over existing methods because it can handle a much larger set of candidate SNPs and can also test specifically for epistasis in a fundamentally model-free way. This method was first published in Bioinformatics and earned the Larry Kupper Award for the best paper arising from a dissertation this year at UNC Biostatistics. We are revising our paper that extended the method to enable inclusion of maternal SNPs as part of the etiology. We have also extended the work to allow the genetic pathways to interact with environmental exposures, and have applied the new methods to oral clefting in relation to maternal smoking during pregnancy. That paper will be submitted soon. The approach can also be used to disentangle possibly distinct epistatic effects in relation to more specific disease subcategories, e.g. the molecular subtypes of breast cancer, or to severity of the outcome, e.g. extreme prematurity versus less extreme prematurity. Future plans include evaluating epistasis for quantitative outcomes like blood pressure.