Methods for Genetic Epidemiology ? ? We developed semiparametric maximum likelihood estimates (SPMLE) for case-control studies of gene-environment interactions under the assumption of independence of gene and environmental factors. Traditional logistic regression analysis is not efficient in this setting. We use a profile-likelihood technique to obtain SPMLE and study its asymptotic theory. The results are extended to deal with situations where genetic and environmental factors are independent conditional on some other factors. The method is applied to ovarian case-control data to investigate the interplay of BRCA1/2 mutations and oral contraceptive use. We extended this approach for case-control studies of haplotype associations with disease by allowing for missing genotype data and missing haplotype phase, again assuming independence of genotype and environmental factors. We also exploited this assumption to increase the power of family-based case-control studies to detect gene-environment interactions, main geneeffects, and joint effects. These methods also allow one to compare various family-based designs and make design recommendations. ? ? We developed methods of analysis for case-control family data in which probands (cases or controls) are genotyped and time to disease onset information is available for first-degree relatives. Methods to estimate relative risks, cumulative risks and residual familial aggregation are given. The work indicates that case-control family design is robust to misspecification of copula models used to accommodate residual familial correlation, but that samples with case probands only are not robust to such model misspecification. ? ? We developed score tests for associations of haplotypes with disease in cohort studies and in nested case-control studies. We also developed estimation procedures away from the null hypothesis for such studies. ? ? We developed methods to combine data from family based case-control studies and from sporadic case-control studies. These methods were used to demonstrate increased melanoma risk in carriers of variants of the melanocortin-1-receptor, both in families and in the general population.? ? We developed methods to detect genetic anticipation, the tendency of later generations to have earlier ages at disease onset than preceding generations. These methods were used to study lymphoproliferative conditions in record linkage age-at-onset data. The methods, which allowed for covariate adjustments, staggered entry, censoring and correlations among relatives, showed that apparent evidence of genetic anticipation for non-Hodgkin lymphoma (NHL) disappeared when adjusted for secular changes in NHL incidence.? ? We published methods to compute sample sizes required for family-based association tests based on genotyped parents and genotyped affected and unaffected offspring, based on a score test that conditions on parental genotypes and the disease status of offspring.? ? We developed a resampling approach to control the family-wise error level of multiple testing procedures to detect genetic associations in case-control data. An omnibus test combines single nucleotide polymorphism (SNP)-based and haplotype-based procedures and has good power whether the genetic disease tendency is conferred by SNPs or haplotypes. A related two-stage procedure is also developed that controls the false discovery rate.? ? A computer program in R called BayesMendel was developed and made publicly available to allow researches to compute the probability of being a mutation carrier based on family history. We also completed research of the effects of mistakes in the family history data on the quality of the estimated mutation carrier probabilities.
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