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Related Experiment Video

Updated: May 6, 2026

Noninvasive Sampling of Mucosal Lining Fluid for the Quantification of In Vivo Upper Airway Immune-mediator Levels

Noninvasive Sampling of Mucosal Lining Fluid for the Quantification of In Vivo Upper Airway Immune-mediator Levels

Published on: August 7, 2017

Testing multiple biological mediators simultaneously.

Simina M Boca¹, Rashmi Sinha, Amanda J Cross

¹Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA.

Bioinformatics (Oxford, England)

|November 9, 2013

Summary

This summary is machine-generated.

A new permutation approach enhances the detection of biological mediators in large-scale studies. This method significantly improves statistical power compared to traditional Bonferroni correction for identifying disease risk factors.

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Last Updated: May 6, 2026

Noninvasive Sampling of Mucosal Lining Fluid for the Quantification of In Vivo Upper Airway Immune-mediator Levels

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Published on: August 7, 2017

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Human In-Vivo Bioassay for the Tissue-Specific Measurement of Nociceptive and Inflammatory Mediators

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Published on: December 1, 2008

Area of Science:

Biostatistics
Genomics
Epidemiology

Background:

Biomedical studies analyze numerous biomarkers (e.g., gene expression, metabolites).
Testing direct biomarker-disease associations has established methods for multiple comparisons.
Identifying biological mediators between risk factors and diseases presents unique statistical challenges due to complex null hypotheses.

Purpose of the Study:

To develop a novel statistical method for testing multiple biological mediators.
To improve the power of detecting mediators compared to existing methods.
To control the family-wise error rate in mediation analysis.

Main Methods:

A permutation approach is proposed to test multiple putative mediators.
The method focuses on the maximum of test statistics for improved power.
An R-package is available in the supplementary material.

Main Results:

The permutation approach significantly increases power to detect mediators, even with independent biomarkers.
Simulations show 2-5x greater power compared to Bonferroni correction.
Docosahexaenoate was identified as a potential mediator between fish consumption and reduced colorectal adenoma risk in a case-control study.

Conclusions:

The proposed permutation test offers a powerful tool for mediation analysis in high-dimensional biomedical data.
This method enhances the ability to discover biological pathways linking risk factors to diseases.
The findings have implications for understanding disease etiology and developing targeted interventions.