Work has progressed in family-based statistical methods for studying genetic effects on qualitative and quantitative traits. We had previously developed methods for qualitative traits using genotypes for affected individuals and their parents. The loglinear approach we had proposed provides a likelihood ratio test and estimation of relative penetrances for variant alleles without requiring knowledge of the genetic model and is robust against bias due to population stratificatio. The method can incorporate parent-of-origin effects, and maternally-mediated genetic effects, and allows for the possibility that one or both parental genotypes may be missing. For early-onset conditions, grandparental genotypes can provide markedly improved statistical power. We have now extended the general approach to allow the identification of alleles related to a complex quantitative trait, and showed that our method provides improved power and robustness over analytic alternatives in widespread use. We are now extending the method to allow for multiple offspring from the same nuclear family, and we are studying potential power advantages of letting the sampling depend on the quantitative trait. For early onset disorders, or traits such as birth weight or adiposity, the prenatal environment can be particularly important and maternally-mediated genetic effects expressed during gestation can influence the phenotype of the offspring. We are extending our methods for quantitative trait analysis to allow for maternally-mediated effects, and also for gene-by-environmetn interaction. Work has also begun on methods based on genotyping of pooled DNA samples in epidemiologic studies, using case-parent designs for a qualitative trait.

Agency
National Institute of Health (NIH)
Institute
National Institute of Environmental Health Sciences (NIEHS)
Type
Intramural Research (Z01)
Project #
1Z01ES040007-08
Application #
7007133
Study Section
(BB)
Project Start
Project End
Budget Start
Budget End
Support Year
8
Fiscal Year
2004
Total Cost
Indirect Cost
Name
U.S. National Inst of Environ Hlth Scis
Department
Type
DUNS #
City
State
Country
United States
Zip Code
Shi, M; Umbach, D M; Wise, A S et al. (2018) Simulating autosomal genotypes with realistic linkage disequilibrium and a spiked-in genetic effect. BMC Bioinformatics 19:2
Chen, Lu; Weinberg, Clarice R; Chen, Jinbo (2016) Using family members to augment genetic case-control studies of a life-threatening disease. Stat Med 35:2815-30
Wise, Alison S; Shi, Min; Weinberg, Clarice R (2016) Family-Based Multi-SNP X Chromosome Analysis Using Parent Information. Front Genet 7:20
Wise, Alison S; Shi, Min; Weinberg, Clarice R (2015) Learning about the X from our parents. Front Genet 6:15
Shi, Min; Umbach, David M; Weinberg, Clarice R (2015) Using parental phenotypes in case-parent studies. Front Genet 6:221
Weinberg, Clarice R; Shi, Min; DeRoo, Lisa A et al. (2014) Asymmetry in family history implicates nonstandard genetic mechanisms: application to the genetics of breast cancer. PLoS Genet 10:e1004174
Shi, Min; Umbach, David M; Weinberg, Clarice R (2014) Disentangling pooled triad genotypes for association studies. Ann Hum Genet 78:345-56
Kim, Jinsil; Stirling, Kara J; Cooper, Margaret E et al. (2013) Sequence variants in oxytocin pathway genes and preterm birth: a candidate gene association study. BMC Med Genet 14:77
Shi, Min; Umbach, David M; Weinberg, Clarice R (2013) Case-sibling studies that acknowledge unstudied parents and permit the inclusion of unmatched individuals. Int J Epidemiol 42:298-307
Weinberg, Clarice R (2012) Interaction and exposure modification: are we asking the right questions? Am J Epidemiol 175:602-5

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