Detection of Disease Genes by Use of Family Data. II. Application to Nuclear Families

Am J Hum Genet. 2000 Apr;66(4):1341-50. doi: 10.1086/302852. Epub 2000 Mar 29.

Abstract

Two likelihood-based score statistics are used to detect association between a disease and a single diallelic polymorphism, on the basis of data from arbitrary types of nuclear families. The first statistic, the nonfounder statistic, extends the transmission/disequilibrium test to accommodate affected and unaffected offspring and missing parental genotypes. The second statistic, the founder statistic, compares observed or inferred parental genotypes with those of some reference population. In this comparison, the genotypes of affected parents or of those with many affected offspring are weighted more heavily than are the genotypes of unaffected parents or of those with few affected offspring. Genotypes of single unrelated cases and controls can be included in this analysis. We illustrate the two statistics by applying them to data on a polymorphism of the SDR5A2 gene in nuclear families with multiple cases of prostate cancer. We also use simulations to compare the power of the nonfounder statistic with that of the score statistic, on the basis of the conditional logistic regression of offspring genotypes.

MeSH terms

  • Alleles
  • Chromosome Mapping / methods*
  • Chromosome Mapping / statistics & numerical data*
  • Computer Simulation
  • Female
  • Founder Effect
  • Genetic Diseases, Inborn / genetics*
  • Genetic Linkage / genetics*
  • Genetic Predisposition to Disease / genetics
  • Genotype
  • Humans
  • Likelihood Functions
  • Linkage Disequilibrium / genetics
  • Logistic Models
  • Male
  • Matched-Pair Analysis
  • Models, Genetic
  • Nuclear Family*
  • Phenotype
  • Polymorphism, Genetic / genetics
  • Prostatic Neoplasms / genetics