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A tree-based model for allele-sharing-based linkage analysis in human complex diseases.

W Xu1, T G Schulze, J R DePaulo

  • 1Department of Public Health Sciences, University of Toronto, Toronto, Ontario, Canada.

Genetic Epidemiology
|December 31, 2005
PubMed
Summary

A new recursive-partitioning (RP) model enhances linkage analysis by identifying specific patient subgroups. This tree-based method revealed suggestive linkage regions for bipolar affective disorder (BPAD) by considering gene-environment interactions.

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Area of Science:

  • Genetics
  • Biostatistics
  • Psychiatric Genetics

Background:

  • Identifying genetic loci for complex diseases like bipolar affective disorder (BPAD) is challenging.
  • Traditional linkage analysis may overlook gene-environment interactions that influence disease susceptibility.
  • Subgroup analysis can increase the power to detect linkage by accounting for genetic heterogeneity.

Purpose of the Study:

  • To develop and validate a recursive-partitioning (RP) algorithm for identifying phenotype and covariate groupings that interact with linkage evidence.
  • To apply the RP model to a BPAD dataset to uncover potential gene-environment interactions and refine linkage findings.
  • To assess the utility of the RP model in detecting suggestive linkage regions missed by standard methods.

Main Methods:

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  • Adapted a relative-pair linkage model to incorporate covariate information using a recursive-partitioning (tree-based) approach.
  • Employed tree pruning and bootstrap algorithms to optimize tree structure and covariate selection.
  • Applied the RP model to families with BPAD, comparing results with traditional NPL tests using Genehunter.

    • Main Results:

    • Simulation studies demonstrated that the RP model can increase power to detect linkage in the presence of gene-environment interactions.
    • The RP model identified suggestive linkage regions on chromosome 18 for BPAD, which were not detected by standard NPL tests.
    • Two covariates, BPAD subtype II and the temporal pattern of mania relative to depression, significantly influenced linkage evidence.

    Conclusions:

    • The recursive-partitioning model is a valuable tool for identifying gene-environment interactions in genetic linkage studies.
    • This methodology has practical utility for uncovering previously undetected linkage signals in complex disorders like BPAD.
    • The RP model offers a promising approach to dissecting genetic contributions to disease by considering subgroup-specific effects.