Model-based linkage analysis with imprinting for quantitative traits: ignoring imprinting effects can severely jeopardize detection of linkage

Genet Epidemiol. 2008 Jul;32(5):487-96. doi: 10.1002/gepi.20321.

Abstract

Genes with imprinting (parent-of-origin) effects express differently when inheriting from the mother or from the father. Some genes for development and behavior in mammals are known to be imprinted. We developed parametric linkage analysis that accounts for imprinting effects for continuous traits, implementing it in MORGAN. To study misspecification of imprinting on linkage analysis, we simulated eight markers over a 35 cM region with phenotypes where imprinting contributes 0, 25, 50, and 75% of the variance of a quantitative trait locus (QTL) effect and analyzed them under all four models. Multipoint lod scores were computed and maximized over the same 35 cM region. Our most important finding is the dramatic lod score improvement under the correct imprinting model over the no-imprinting model. For data with minor QTL allele frequency 0.05, the correct model provided the highest lod scores with maximum expected lod scores over 4 in all settings. Ignoring imprinting provided the lowest lod scores with maximum expected lod scores between -9.9 and 2.4. In the extreme scenario, cases with max lod > or =3 from the correct imprinting model and max lod < or =-2 from the no-imprinting model occurred in 86% of replications. Models with misspecified imprinting produced lod scores intermediate between those with correct imprinting and with no imprinting. The effects of model misspecification were less pronounced for singlepoint analysis. Our multipoint results illustrate that ignoring true imprinting severely impairs detection of linkage and erroneously excludes genomic regions (with max lod <-2), whereas accounting for it can substantially improve linkage detection.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Genetic Linkage*
  • Genomic Imprinting*
  • Humans
  • Lod Score
  • Markov Chains
  • Models, Genetic*
  • Monte Carlo Method
  • Pedigree
  • Quantitative Trait Loci*