Multilocus linkage analysis of the German asthma data

P. P. Zandi, A. P. Klein, A. M. Addington, J. B. Hetmanski, L. Roberts, R. Peila, S. Shrestha, C. K. Shaw, Chew Kiat Heng Chew Kiat, C. D. Langefeld, T. H. Beaty

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


We analyzed data from the German Asthma Genetics Group with three methods that utilize pedigree-specific nonparametric linkage scores to facilitate the search for multiple independent and interacting susceptibility loci. The three methods included a conditional analysis, logistic regression, and neural networks. Although there were differences, the three methods identified many of the same susceptibility loci. The most consistent evidence was provided for loci on chromosomes 1, 2, 6, 9, and 15. Both the conditional and the logistic regression analyses suggested an epistatic relationship between loci on chromosomes 2 and 9. The logistic regression analysis further revealed evidence for locus heterogeneity between loci on chromosomes 6 and 15. Finally, the neural network analysis identified a potential locus on chromosome 17 that was not identified in the other analyses.

Original languageEnglish (US)
Pages (from-to)S210-S215
JournalGenetic epidemiology
Issue numberSUPPL. 1
StatePublished - Oct 23 2001


  • Conditional analysis
  • Epistasis
  • Gene×gene interaction
  • Heterogeneity
  • Neural networks
  • Nonparametric linkage regression

ASJC Scopus subject areas

  • Epidemiology
  • Genetics(clinical)


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