Statistical Methods For Genetic Epidemiology

National Institute Of Environmental Health Sciences

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Linked publications & trials

Abstract

Despite some advances due to the extensive work that has been done to associate genetic variants with diseases, those variants explain a small proportion of the heritability of most heritable health problems. The birth defect, oral cleft, is a good example. The recurrence risk is know 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 a number of particular SNPs must be simultaneously 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. The software for carrying out simulations is now freely available. Using that 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 paper is now undergoing revision for publication. We are next extending the work to allow the genetic pathways to interact with environmental exposures, with plans to apply the new methods to oral cleating in relation to maternal smoking during pregnancy. The approach can also be used to disentangle possibly distinct epistatic effects in relation to more specific disease categories, e.g. the molecular subtypes of breast cancer, or to severity of the outcome, e.g. extreme prematurity versus less extreme prematurity. Epistasis for quantitative outcomes like blood pressure can also be probed. We are also continuing to work with Steve Kleeberger and colleagues to find genetic variants, both nuclear and mitochondrial, that are related to a quantitative trait. We are studying baby-parent triads where the baby was born with very low birth weight and some developed broncho-pulmonary dysplasia, a serious complication of preterm birth.