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Related Experiment Videos

Mapping alcoholism genes using linkage/linkage disequilibrium analysis.

C Aragaki1, F Quiaoit, L Hsu

  • 1Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, USA.

Genetic Epidemiology
|December 22, 1999
PubMed
Summary

This study used a new semiparametric method to analyze genetic data for alcohol dependence. Significant linkage and linkage-disequilibrium signals were found on chromosomes 1, 2, 4, and 7 for alcohol dependence.

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Area of Science:

  • Genetics
  • Statistical genetics
  • Human genetics

Background:

  • Alcohol dependence is a complex disorder with significant genetic components.
  • Previous genetic studies have identified potential susceptibility loci, but comprehensive analysis is ongoing.
  • The Collaborative Study on the Genetics of Alcoholism (COGA) provides valuable data for such investigations.

Purpose of the Study:

  • To apply a novel semiparametric method for combined linkage and linkage-disequilibrium analysis to COGA data.
  • To identify genetic loci associated with alcohol dependence and an "alcoholism-free" phenotype.
  • To evaluate the performance of the semiparametric approach in a genome-wide context.

Main Methods:

  • Utilized a recently developed semiparametric method for combined linkage/linkage-disequilibrium analysis.

Related Experiment Videos

  • Analyzed the Genetic Analysis Workshop 11 (GAW11) data subset from the Collaborative Study on the Genetics of Alcoholism.
  • Estimated recombination fractions for linkage, marker log odds ratios for linkage-disequilibrium, and their product, alongside z-scores, using a genome-wide significance threshold of 4.1.

    • Main Results:

    • For alcohol dependence, significant linkage signals were detected at markers on chromosomes 1, 2, 4, and 7 (e.g., D1S1588-D1S1631, D7S1824).
    • Significant linkage-disequilibrium signals for alcohol dependence were observed at D1S547 and D7S1795.
    • For the "alcoholism-free" outcome, significant linkage signals were found on chromosomes 4, 11, and 16, with linkage-disequilibrium signals on chromosomes 4, 11, and 19.

    Conclusions:

    • The semiparametric method successfully identified significant linkage and linkage-disequilibrium signals for alcohol dependence and related phenotypes.
    • The findings highlight specific chromosomal regions potentially harboring genes that influence alcohol dependence susceptibility.
    • This approach offers a powerful tool for dissecting complex genetic architectures of diseases.