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Sample size needed to detect gene-gene interactions using linkage analysis.

Shuang Wang1, Hongyu Zhao

  • 1Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY, USA. sw2206@columbia.edu

Annals of Human Genetics
|May 25, 2007
PubMed
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Detecting gene-gene interactions is crucial for understanding complex traits. This study compares the power of affected sib pair (ASP) and association designs, finding their effectiveness depends heavily on the interaction definition and disease prevalence.

Area of Science:

  • Genetics
  • Statistical genetics
  • Human disease genetics

Background:

  • Gene-gene interactions are vital for complex human traits.
  • Previous studies focused on statistical power in association studies for gene-gene interactions.
  • The affected sib pair (ASP) design offers an alternative approach to investigate these interactions.

Purpose of the Study:

  • To investigate the statistical power of the affected sib pair (ASP) design for detecting gene-gene interactions at two disease loci.
  • To compare the power of ASP designs with association designs under various definitions of gene-gene interaction and disease models.
  • To examine the influence of disease prevalence on the relative power of different designs and models.

Main Methods:

  • Evaluated the power of the affected sib pair (ASP) design to detect gene-gene interactions.

Related Experiment Videos

  • Considered multiple definitions of gene-gene interaction, including departure from independence, multiplicative, additive, and heterogeneity models.
  • Examined various disease models, including logistic and two-locus models with fixed penetrances.

    • Main Results:

    • The relative power of ASP versus association designs is highly dependent on the definition of gene-gene interaction.
    • For departure from independence, association designs are more powerful; model choice (additive vs. recessive) depends on disease prevalence.
    • For multiplicative, additive, and heterogeneity models, ASP designs are more powerful for rare diseases but less so for common diseases compared to association designs.

    Conclusions:

    • The choice of gene-gene interaction definition significantly impacts the comparison of ASP and association design power.
    • ASP designs show advantages for rare diseases under certain interaction models, while association designs are generally more powerful for common diseases.
    • Understanding these nuances is critical for selecting appropriate study designs in genetic research.