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Lower-order effects adjustment in quantitative traits model-based multifactor dimensionality reduction.

Jestinah M Mahachie John1, Tom Cattaert, François Van Lishout

  • 1Systems and Modeling Unit, Montefiore Institute, University of Liege, Liege, Belgium.

Plos One
|January 14, 2012
PubMed
Summary
This summary is machine-generated.

Accurately detecting gene interactions in complex diseases is challenging. This study recommends adjusting for main genetic effects during epistasis analysis to control false positives, especially using co-dominant coding.

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Area of Science:

  • Genetic Epidemiology
  • Statistical Genetics
  • Human Complex Diseases

Background:

  • Identifying gene-gene and gene-environment interactions is crucial but challenging for complex diseases.
  • Lower-order genetic effects can obscure genuine epistasis by artificially boosting interaction signals.
  • This study focuses on quantitative traits and two-way SNP-SNP interactions.

Purpose of the Study:

  • To evaluate corrective measures for lower-order genetic effects in epistasis detection using Model-Based Multifactor Dimensionality Reduction (MB-MDR).
  • To assess the impact of different coding schemes (additive, co-dominant) on power and familywise error rate.
  • To provide recommendations for robust epistasis analysis in genetic epidemiology.

Main Methods:

  • Simulations were used to assess the performance of various correction strategies for lower-order genetic effects.
  • Model-Based Multifactor Dimensionality Reduction (MB-MDR) was employed for epistasis detection.
  • Performance was evaluated based on statistical power and familywise error rate.

Main Results:

  • Correcting for lower-order effects reduced empirical power and familywise error rates.
  • Automatic SNP selection methods decreased power but also minimized false positives.
  • Consistent adjustment for main effects within the analyzed SNP-SNP pair, particularly with co-dominant coding, effectively controlled false positive epistasis findings.

Conclusions:

  • Automatic search procedures for lower-order effects and pre-analysis adjustments using residuals should be avoided.
  • On-the-fly adjustment for lower-order effects during MB-MDR analysis is recommended for accurate SNP-SNP interaction screening.
  • This approach enhances the reliability of epistasis detection in genetic studies of complex diseases.