Imprinting detection by extending a regression-based QTL analysis method

Olga Y. Gorlova, Lei Lei, Dakai Zhu, Shih Feng Weng, Sanjay Shete, Yiqun Zhang, Wei Dong Li, R. Arlen Price, Christopher I. Amos

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

We present an extension of a regression-based quantitative-trait linkage analysis method to incorporate parent-of-origin effects. We separately regressed total, paternal, and maternal IBD sharing on traits' squared sums and differences. We also developed a test for imprinting that indicates whether there is any difference between the paternal and maternal regression coefficients. Since this method treats the identity-by-descent information as the dependent variable that is conditioned on the trait, it can be readily applied to data from complex ascertainment processes. We performed a simulation study to examine the performance of the method. We found that when using empirical critical values, the method shows identical or higher power compared to existing methods for evaluation of parent-of-origin effect in linkage analysis of quantitative traits. Missing parental genotypes increase the type I error rate of the linkage test and decrease the power of the imprinting test. When the major gene has a low heritability, the power of the method decreases considerably, but the statistical tests still perform well. We also applied a permutation algorithm, which ensures the appropriate type I error rate for the test for imprinting. The method was applied to a data from a study of 6 body size related measures and 23 loci on chromosome 7 for 255 nuclear families. Multipoint identities-by-descent (IBD) were obtained using a modification of the SIMWALK 2 program. A parent-of-origin effect consistent with maternal imprinting was suggested at 99.67-111.26 Mb for body mass index, bioelectrical impedance analysis, waist circumference, and leptin concentration.

Original languageEnglish (US)
Pages (from-to)159-174
Number of pages16
JournalHuman genetics
Volume122
Issue number2
DOIs
StatePublished - Sep 2007

ASJC Scopus subject areas

  • Genetics
  • Genetics(clinical)

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