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Statistical Applications in Genetics and Molecular Biology

Editor-in-Chief: Sanguinetti, Guido


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Volume 13, Issue 2

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Variance and covariance heterogeneity analysis for detection of metabolites associated with cadmium exposure

Beatriz Valcarcel Salamanca
  • Rheumatology Unit, Institute of Child Health, University College, 30 Guilford Street, London WC1N 1EH, UK
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Timothy M.D. Ebbels
  • Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London, Sir Alexander Fleming Building, South Kensington, London SW7 2AZ, UK
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Maria De Iorio
Published Online: 2014-02-25 | DOI: https://doi.org/10.1515/sagmb-2013-0041

Abstract

In this study, we propose a novel statistical framework for detecting progressive changes in molecular traits as response to a pathogenic stimulus. In particular, we propose to employ Bayesian hierarchical models to analyse changes in mean level, variance and correlation of metabolic traits in relation to covariates. To illustrate our approach we investigate changes in urinary metabolic traits in response to cadmium exposure, a toxic environmental pollutant. With the application of the proposed approach, previously unreported variations in the metabolism of urinary metabolites in relation to urinary cadmium were identified. Our analysis highlights the potential effect of urinary cadmium on the variance and correlation of a number of metabolites involved in the metabolism of choline as well as changes in urinary alanine. The results illustrate the potential of the proposed approach to investigate the gradual effect of pathogenic stimulus in molecular traits.

This article offers supplementary material which is provided at the end of the article.

Keywords: correlation networks; covariance regression; genomics; metabolomics; variance regression

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About the article

Corresponding author: Maria De Iorio, Department of Statistical Science, University College, Gower Street, London WC1E 6BT, UK, e-mail:

a Beatriz Valcarcel Salamanca and Timothy M.D. Ebbels contributed equally to the work.


Published Online: 2014-02-25

Published in Print: 2014-04-01


Citation Information: Statistical Applications in Genetics and Molecular Biology, Volume 13, Issue 2, Pages 191–201, ISSN (Online) 1544-6115, ISSN (Print) 2194-6302, DOI: https://doi.org/10.1515/sagmb-2013-0041.

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