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Region-based association tests for sequencing data on survival traits.

Li-Chu Chien1, Donald W Bowden2,3,4, Yen-Feng Chiu5

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Genetic Epidemiology
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Summary

We developed novel family-based rare variant association tests for survival traits (FamRATS) to analyze time-to-event outcomes. The proposed kernel test demonstrated superior power and robustness in identifying genetic associations with diseases like type 2 diabetes.

Keywords:
burden testfamily studyhybrid designkernel testrare variant

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Area of Science:

  • Genetics
  • Biostatistics
  • Computational Biology

Background:

  • Family-based studies increase power for identifying rare variants.
  • Limited methods exist for rare variant analysis in family-based survival traits, especially on the X chromosome.

Purpose of the Study:

  • To develop novel pedigree-based association tests for time-to-event traits with rare variants.
  • To evaluate the performance and robustness of these new tests against existing methods.

Main Methods:

  • Developed pedigree-based burden and kernel association tests (FamRATS) for time-to-event outcomes with right censoring.
  • Utilized Cox proportional hazard models for variant analysis.
  • Assessed robustness against violations of proportional hazard assumptions.

Main Results:

  • The proposed kernel test outperformed existing burden and survival association tests in power and robustness.
  • FamRATS are applicable to large-scale sequencing data and various study designs.
  • Exome variants in the JAK1 gene were significantly associated with type 2 diabetes onset age.

Conclusions:

  • FamRATS provide a powerful and robust framework for rare variant association studies in family-based survival data.
  • The JAK1 gene variants represent a potential target for understanding type 2 diabetes etiology.