Genotype-based association test for general pedigrees: the genotype-PDT.

Published

Journal Article

Many family-based tests of linkage disequilibrium (LD) are based on counts of alleles rather than genotypes. However, allele-based tests may not detect interactions among alleles at a single locus that are apparent when examining associations with genotypes. Family-based tests of LD based on genotypes have been developed, but they are typically valid as tests of association only in families with a single affected individual. To take advantage of families with multiple affected individuals, we propose the genotype-pedigree disequilibrium test (geno-PDT) to test for LD between marker locus genotypes and disease. Unlike previous tests for genotypic association, the geno-PDT is valid in general pedigrees. Simulations to compare the power of the allele-based PDT and geno-PDT reveal that under an additive model, the allele-based PDT is more powerful, but that the geno-PDT can have greater power when the genetic model is recessive or dominant. Perhaps the most important property of the geno-PDT is the ability to test for association with particular genotypes, which can reveal underlying patterns of association at the genotypic level. These genotype-specific tests can be used to suggest possible underlying genetic models that are consistent with the pattern of genotypic association. This is illustrated through an application to a candidate gene analysis of the MLLT3 gene in families with Alzheimer disease. The geno-PDT approach for testing genotypes in general family data provides a useful tool for identifying genes in complex disease, and partitioning individual genotype contributions will help to dissect the influence of genotype on risk.

Full Text

Duke Authors

Cited Authors

  • Martin, ER; Bass, MP; Gilbert, JR; Pericak-Vance, MA; Hauser, ER

Published Date

  • November 2003

Published In

Volume / Issue

  • 25 / 3

Start / End Page

  • 203 - 213

PubMed ID

  • 14557988

Pubmed Central ID

  • 14557988

International Standard Serial Number (ISSN)

  • 0741-0395

Digital Object Identifier (DOI)

  • 10.1002/gepi.10258

Language

  • eng

Conference Location

  • United States