Statistical Methods For Genetic Epidemiology

National Institute Of Environmental Health Sciences

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Abstract

A particularly important design we are now considering involves a tetrad structure, with one affected and one unaffected offspring, in addition to the two parents. This design has been implemented in the Two Sister Study (funded in part by Susan G. Komen for the Cure), which is assessing the joint role of genetic and environmental risk factors in young-onset (under age 50) breast cancer. The discordant sib pair allows estimation of effects of exposures, while the embedded case-parent triad allows detection of haplotypes that confer either protection or risk. The tetrad analyzed together should provide a powerful design for assessing gene-by-environment interaction. We have been working on developing and evaluating methods for use with the tetrad design. The Two Sister Study completed enrollment of nuclear families where one daughter developed breast cancer before age 50 and the other daughter is unaffected. This is described under a separate project. Inherited genotypes, together with tumor characteristics, will need to be explored to investigate factors that predict the clinical course following treatment, and improved statistical methods will also need to be developed in that context. With support from the IRP of NIEHS and Susan G. Komen for the Cure, we undertook a genome-wide association study based on these data through a contract with the Center for Inherited Disease Research at Johns Hopkins, and those findings have now been published. We also are participating in the GAME-ON consortium, which has provided additional SNPs from the newly developed onco-chip. We have also carried out analyses based on a risk score that was developed based on the SNPs that have previously been replicated in earlier GWAS investigations (paper in review). We have begun to explore possible interactions between the genetic risk score and known risk factors. In a methodologic extension to our earlier work on case-parent triads, we developed a robust method to account for parental phenotypes, and applied those methods to our Two Sister Study, in which some 20% of the mothers also had breast cancer. Together with a graduate student from UNC Biostatistics, Alison Wise, we have developed methods for identifying variants on the X chromosome related to risk. We assessed the performance of our new method by applying it to the DbGap data on the birth defect, oral cleft. Our method, the PIX-LRT, makes use of parental information in a robust way in addition to the transmission distortion, and thus makes more efficient use of the data than do existing methods. Alison successfully defended her thesis last year. We have extended the method allow discovery of haplotypes (multiple SNPs close to each other) on the X chromosome. Another project concerns use of the Genetic Algorithm, a stochastic search algorithm, to detect multi-SNP epistatic effects based on transmissions observed from parents to their affected offspring. This work was presented at the ASHG meeting in October and a more completely developed version of the algorithm was presented at the Joint Statistical Meeting in Chicago this August.