This dissertation describes new statistical methods designed to improve the power of genetic association studies. Of particular interest are studies with a response-selective sampling design, i.e.... Show moreThis dissertation describes new statistical methods designed to improve the power of genetic association studies. Of particular interest are studies with a response-selective sampling design, i.e. case-control studies of unrelated individuals and case-control studies of family members. The statistical methods presented in this dissertation (a) take advantage of information available in the distribution of the covariates in case-control studies by modeling the ascertainment process; (b) incorporate information from both family-based studies and case-control studies of unrelated individuals; (c) use "richer" models of the relationship between genetic variants and phenotypes, compared to models used in standard genetic association studies; and (d) integrate different types of data, such as genomic, epigenomic, transcriptomic and environmental information. Together, these methods will improve the ability of the genetics community to identify the genetic basis of complex human phenotypes. Show less
Balliu, B.; Tsonaka, R.; Boehringer, S.; Houwing-Duistermaat, J. 2015
It is hypothesized that certain alleles can have a protective effect not only when inherited by the offspring but also as noninherited maternal antigens (NIMA). To estimate the NIMA effect, large... Show moreIt is hypothesized that certain alleles can have a protective effect not only when inherited by the offspring but also as noninherited maternal antigens (NIMA). To estimate the NIMA effect, large samples of families are needed. When large samples are not available, we propose a combined approach to estimate the NIMA effect from ascertained nuclear families and twin pairs. We develop a likelihood-based approach allowing for several ascertainment schemes, to accommodate for the outcome-dependent sampling scheme, and a family-specific random term, to take into account the correlation between family members. We estimate the parameters using maximum likelihood based on the combined joint likelihood (CJL) approach. Simulations show that the CJL is more efficient for estimating the NIMA odds ratios as compared to a families-only approach. To illustrate our approach, we used data from a family and a twin study from the United Kingdom on rheumatoid arthritis, and confirmed the protective NIMA effect, with an odds ratio of 0.477 (95% CI 0.264-0.864). Show less
