Techniques will be developed for genetic analysis of complex diseases segregating in pedigrees of arbitrary size and structure. Cardiovascular, neurological and behavioral traits are among those having both environmental and genetic components. However, identification of genes contributing to increased risk of related disorders has been limited by both computational and statistical constraints. The development of Markov chain Monte Carlo (MCMC) methods has helped overcome these limitations, and the research now proposed concerns extension of these computational and statistical methods in several areas. Improved methods will be developed for the MCMC analysis of gene identity by descent (ibd) in general pedigrees, given data at a dense genome screen of markers, together with the use of this ibd in analyses of complex traits. The ibd inferred from dense genetic markers permits the combination of information within and among pedigrees, increasing the power and resolution of linkage analyses. The ibd framework also provides for far more computationally efficient trait analyses, enabling models for discrete and quantitative trait phenotypes to be extended to a variety of complex models. Additionally, use of the same MCMC-realized ibd patterns in the analysis of multiple trait models provide measures of trait model robustness, and of confidence and significance of linkage findings. With the availability of sparser genetic marker data on extended pedigrees, together with dense localized data on a subset of individuals, the problems of haplotyping, genotype imputation, and error detection, assume increasing importance. Again, MCMC-based realization of ibd at sparser locations provides new methods for imputation of genotypes and haplotypes at denser locations, incorporating linkage disequilibrium and models for next-generation sequence data into the analysis of trait data on pedigrees. Methods will be evaluated by analyses on several simulated and real data sets, including pedigrees segregating cardiovascular disease or behavioral disorders. These real data sets include several on which are available genome-wide marker screens, localized multigene haplotypes, and next-generation sequence data. Finally, software implementing these methods will be developed, documented and released.

Public Health Relevance

Complex traits including cardiovascular, neurological and behavioral phenotypes are related to human health disorders which carry a significant public health burden. Identification of genes contributing to increased disease risk has been limited by trait complexity. Development of methods for genetic analysis offers the potential for finding the genes contributing to risk, and for resolving the interaction of genes and environment.

National Institute of Health (NIH)
National Institute of General Medical Sciences (NIGMS)
Method to Extend Research in Time (MERIT) Award (R37)
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Special Emphasis Panel (NSS)
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Krasnewich, Donna M
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University of Washington
Biostatistics & Other Math Sci
Schools of Arts and Sciences
United States
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Saad, Mohamad; Wijsman, Ellen M (2014) Combining family- and population-based imputation data for association analysis of rare and common variants in large pedigrees. Genet Epidemiol 38:579-90
Saad, Mohamad; Wijsman, Ellen M (2014) Power of family-based association designs to detect rare variants in large pedigrees using imputed genotypes. Genet Epidemiol 38:1-9
Cheung, Charles Y K; Marchani Blue, Elizabeth; Wijsman, Ellen M (2014) A statistical framework to guide sequencing choices in pedigrees. Am J Hum Genet 94:257-67
Blue, Elizabeth M; Sun, Lei; Tintle, Nathan L et al. (2014) Value of Mendelian laws of segregation in families: data quality control, imputation, and beyond. Genet Epidemiol 38 Suppl 1:S21-8
Cheung, Charles Y K; Thompson, Elizabeth A; Wijsman, Ellen M (2014) Detection of Mendelian consistent genotyping errors in pedigrees. Genet Epidemiol 38:291-9
Zheng, Chaozhi; Kuhner, Mary K; Thompson, Elizabeth A (2014) Joint inference of identity by descent along multiple chromosomes from population samples. J Comput Biol 21:185-200
Zheng, Chaozhi; Kuhner, Mary K; Thompson, Elizabeth A (2014) Bayesian inference of local trees along chromosomes by the sequential Markov coalescent. J Mol Evol 78:279-92
Ryman, Davis C; Acosta-Baena, Natalia; Aisen, Paul S et al. (2014) Symptom onset in autosomal dominant Alzheimer disease: a systematic review and meta-analysis. Neurology 83:253-60
Kim, Sulgi; Saad, Mohamad; Tsuang, Debby W et al. (2014) Visualization of haplotype sharing patterns in pedigree samples. Hum Hered 78:1-8
Koepke, Hoyt; Thompson, Elizabeth (2013) Efficient identification of equivalences in dynamic graphs and pedigree structures. J Comput Biol 20:551-70

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