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A powerful test for ordinal trait genetic association analysis.

Yuan Xue1,2, Jinjuan Wang3, Juan Ding4

  • 1School of Mathematical Sciences, University of Chinese Academy of Sciences, Beijing, China.

Statistical Applications in Genetics and Molecular Biology
|January 28, 2019
PubMed
Summary

This study introduces a new genetic association test for response selective sampling designs. The proposed test offers improved power for identifying disease-predisposing genetic variants compared to existing methods.

Keywords:
ordinal responsepowerproportional odds modelresponse selective sampling

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Area of Science:

  • Genetic Epidemiology
  • Statistical Genetics
  • Biostatistics

Background:

  • Response selective sampling designs are efficient in genetic epidemiology, reducing costs and increasing power for complex disease studies.
  • Traditional proportional odds models (POM) yield inconsistent genetic effect estimates when applied to prospective data, leading to suboptimal power.
  • Existing modified POM and Wald tests have limitations, particularly for small genetic effects.

Purpose of the Study:

  • To develop a novel association test for response selective sampling designs in genetic epidemiology.
  • To address the limitations of existing methods in accurately estimating genetic effects and maintaining statistical power.
  • To provide a more powerful and reliable tool for identifying genetic variants associated with complex diseases.

Main Methods:

  • Proposed a new association test tailored for response selective sampling data.
  • Conducted simulation studies to evaluate the proposed test's performance.
  • Compared the proposed test against two existing methods in terms of type I error rate and power.
  • Applied the developed test and existing methods to real-world genetic data (Anticyclic Citrullinated Protein Antibody).

Main Results:

  • The proposed association test correctly controls the type I error rate.
  • Simulation studies demonstrated superior power of the proposed test over two existing methods.
  • The test showed effectiveness when applied to the Anticyclic Citrullinated Protein Antibody dataset.

Conclusions:

  • The new association test is a robust and powerful tool for genetic association studies using response selective sampling.
  • This method enhances the identification of genetic variants linked to complex human diseases.
  • The findings have implications for improving the efficiency and accuracy of genetic epidemiological research.