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United States Department of Agriculture

Agricultural Research Service

Research Project: NUTRITION, OBESITY, CARDIOVASCULAR HEALTH AND GENOMICS Title: A powerful test of parent-of-origin effects for quantitative traits using haplotypes

Authors
item Feng, Rui -
item Wu, Yinghua -
item Jang, Gun Ho -
item Ordovas, Jose -
item Arnett, Donna -

Submitted to: PLoS One
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: November 17, 2011
Publication Date: December 13, 2011
Citation: Feng, R., Wu, Y., Jang, G., Ordovas, J.M., Arnett, D.K. 2011. A powerful test of parent-of-origin effects for quantitative traits using haplotypes. PLoS One. 6(12):e28909.

Interpretive Summary: Imprinting is an epigenetic phenomenon where the same alleles have unequal transcriptions and thus contribute differently to a trait depending on their parent of origin. This mechanism has been found to affect a variety of human disorders. Although various methods for testing parent-of-origin effects have been proposed in linkage analysis settings, only a few are available for association analysis and they are usually restricted to small families and particular study designs. In this study, we develop a powerful test to evaluate the parent-of-origin effects of SNPs on phenotypes in family studies. Moreover, it provides guidance for recruitment of family members in future studies. As a demonstration, we applied our method to a dataset from the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) to test the parent-of-origin effects of the SNPs within the PPARGC1A, MTP and FABP2 genes on diabetes-related phenotypes, and found that several SNPs in the MTP gene show parent-of-origin effects on insulin and glucose levels.

Technical Abstract: Imprinting is an epigenetic phenomenon where the same alleles have unequal transcriptions and thus contribute differently to a trait depending on their parent of origin. This mechanism has been found to affect a variety of human disorders. Although various methods for testing parent-of-origin effects have been proposed in linkage analysis settings, only a few are available for association analysis and they are usually restricted to small families and particular study designs. In this study, we develop a powerful maximum likelihood test to evaluate the parent-of-origin effects of SNPs on quantitative phenotypes in general family studies. Our method incorporates haplotype distribution to take advantage of inter-marker LD information in genome-wide association studies (GWAS). Our method also accommodates missing genotypes that often occur in genetic studies. Our simulation studies with various minor allele frequencies, LD structures, family sizes, and missing schemes have uniformly shown that using the new method significantly improves the power of detecting imprinted genes compared with the method using the SNP at the testing locus only. Our simulations suggest that the most efficient strategy to investigate parent-of-origin effects is to recruit one parent and as many offspring as possible under practical constraints. As a demonstration, we applied our method to a dataset from the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) to test the parent-of-origin effects of the SNPs within the PPARGC1A, MTP and FABP2 genes on diabetes-related phenotypes, and found that several SNPs in the MTP gene show parent-of-origin effects on insulin and glucose levels.

Last Modified: 11/26/2014
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