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The affected sib method. III. Selection and recombination.

H Payami, G Thomson, E J Louis

    American Journal of Human Genetics
    |March 1, 1984
    PubMed
    Summary
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    The affected sib-pair method for HLA-associated diseases needs adjustment for selection against affected individuals. Ignoring selection can alter estimates of disease allele frequency and mode of inheritance, especially for dominant models.

    Area of Science:

    • Human Genetics
    • Immunogenetics
    • Disease Inheritance

    Background:

    • The affected sib-pair (ASP) method is crucial for studying HLA-associated diseases.
    • A key assumption of the original ASP method is the absence of selective disadvantage for affected individuals.
    • This assumption is often violated in real-world disease scenarios.

    Purpose of the Study:

    • To determine the expected HLA haplotype-sharing distribution in affected sib-pairs considering selection.
    • To evaluate the impact of ignoring selection on estimates of disease inheritance and allele frequency.
    • To assess the influence of recombination between disease and HLA loci.

    Main Methods:

    • Developed a model to account for selective disadvantage in affected sib-pairs.

    Related Experiment Videos

  • Analyzed expected HLA haplotype-sharing distributions under various inheritance models (recessive, additive, dominant).
  • Investigated the effects of recombination between disease and HLA loci.

    • Main Results:

    • For recessive or additive models, ignoring selection still estimates the correct mode of inheritance but underestimates allele frequency.
    • For dominant models, ignoring selection alters estimates of penetrance and allele frequency.
    • Ignoring recombination overestimates disease allele frequency across all studied models.

    Conclusions:

    • Selection against affected individuals significantly impacts ASP analysis for HLA-associated diseases.
    • Adjustments for selection and recombination are necessary for accurate genetic parameter estimation.
    • The study highlights the importance of refining the ASP method for complex genetic diseases.