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Related Experiment Videos

Association studies under general disease models.

D M Nielsen1, B S Weir

  • 1Program in Statistical Genetics, Department of Statistics, North Carolina State University, Raleigh, North Carolina 27695-7566, USA.

Theoretical Population Biology
|February 22, 2002
PubMed
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Genetic marker association studies help locate disease genes by analyzing linkage disequilibrium. This study clarifies how complex genetic interactions affect these association mapping methods, including marker haplotypes.

Area of Science:

  • Genetics
  • Statistical Genetics
  • Bioinformatics

Background:

  • Association studies aim to locate disease genes by leveraging the relationship between genetic markers and disease status.
  • This relationship is often assumed to be proportional to linkage disequilibrium (LD) and inversely related to recombination.
  • However, for disease genes with multiple alleles, the association measure is a complex weighted average of LDs, complicating the direct relationship with recombination.

Purpose of the Study:

  • To develop a general framework for examining association mapping methods.
  • To clarify the nature of case-control and transmission/disequilibrium tests.
  • To reveal the relationship between association measures and linkage disequilibrium coefficients, considering additive and nonadditive genetic effects.

Main Methods:

Related Experiment Videos

  • Utilizing a general theoretical framework to analyze association mapping.
  • Examining the impact of additive and nonadditive genetic effects on test behaviors.
  • Extending concepts to marker haplotypes for two-locus analyses.

Main Results:

  • Demonstrated that for multi-allele disease genes, association is a weighted average of LDs, not simply related to recombination.
  • Clarified the behavior of case-control and transmission/disequilibrium tests under various genetic models.
  • Showed that two-locus marker haplotype association depends on three-locus disequilibria.

Conclusions:

  • The study provides a clearer understanding of association mapping principles, especially for complex genetic scenarios.
  • The framework helps interpret results from various association tests and their dependence on LD.
  • Marker haplotype analyses are likely to offer valuable insights in future association mapping studies.