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Group testing in mediation analysis.

Andriy Derkach1, Steven C Moore2, Simina M Boca3

  • 1Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland, USA.

Statistics in Medicine
|May 5, 2020
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Summary
This summary is machine-generated.

This study introduces a new two-step method to identify biomarker sets that mediate relationships between exposures and outcomes. The procedure enhances statistical power for detecting true mediators, like lysine metabolites in breast cancer risk.

Keywords:
group testinghigh-dimensional mediationpathway analysis

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Area of Science:

  • Biostatistics
  • Biomarker Discovery
  • Epidemiology

Background:

  • Understanding mediation in exposure-outcome relationships is crucial for public health.
  • Existing methods for identifying mediating biomarkers often lack statistical power or control for familywise error rates.
  • Biologically defined sets of biomarkers offer a structured approach to mediation analysis.

Purpose of the Study:

  • To develop and validate a novel two-step statistical procedure for identifying mediating biomarker sets.
  • To maintain a prespecified familywise error rate during mediation analysis.
  • To improve statistical power in detecting true mediating pathways.

Main Methods:

  • A two-step procedure involving an initial screening step to remove non-associated biomarker sets.
  • A second step employing postselection inference to test for mediation in candidate sets.
  • Simulation studies to compare the proposed method's power against existing procedures.

Main Results:

  • The proposed two-step procedure demonstrated higher statistical power in simulations compared to existing methods.
  • The method successfully identified a set of lysine-related metabolites as potential mediators.
  • A significant mediation pathway was identified between body mass index and estrogen-receptor positive breast cancer risk.

Conclusions:

  • The novel two-step procedure is an effective and powerful tool for identifying mediating biomarker sets.
  • Lysine-related metabolites may play a mediating role in the association between BMI and breast cancer risk in postmenopausal women.
  • This approach advances the field of mediation analysis in epidemiological and biomarker research.