Using multiple biomarkers and determinants to obtain a better measurement of oxidative stress: a latent variable structural equation model approach

Ronald C. Eldridge, W. Dana Flanders, Roberd M. Bostick, Veronika Fedirko, Myron Gross, Bharat Thyagarajan, Michael Goodman

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

Purpose: Since oxidative stress involves a variety of cellular changes, no single biomarker can serve as a complete measure of this complex biological process. The analytic technique of structural equation modeling (SEM) provides a possible solution to this problem by modelling a latent (unobserved) variable constructed from the covariance of multiple biomarkers. Methods: Using three pooled datasets, we modelled a latent oxidative stress variable from five biomarkers related to oxidative stress: F2-isoprostanes (FIP), fluorescent oxidation products, mitochondrial DNA copy number, γ-tocopherol (Gtoc) and C-reactive protein (CRP, an inflammation marker closely linked to oxidative stress). We validated the latent variable by assessing its relation to pro- and anti-oxidant exposures. Results: FIP, Gtoc and CRP characterized the latent oxidative stress variable. Obesity, smoking, aspirin use and β-carotene were statistically significantly associated with oxidative stress in the theorized directions; the same exposures were weakly and inconsistently associated with the individual biomarkers. Conclusions: Our results suggest that using SEM with latent variables decreases the biomarker-specific variability, and may produce a better measure of oxidative stress than do single variables. This methodology can be applied to similar areas of research in which a single biomarker is not sufficient to fully describe a complex biological phenomenon.

Original languageEnglish (US)
Pages (from-to)517-524
Number of pages8
JournalBiomarkers
Volume22
Issue number6
DOIs
StatePublished - Aug 18 2017

Bibliographical note

Funding Information:
This work was funded by Laney Graduate School, Emory University (RCE), R01 CA66539 (RMB), Fullerton Foundation (RMB), Georgia Cancer Coalition (RMB), R01 CA116795 (RMB), Kaiser Foundation Health Plan of Georgia (MG).

Publisher Copyright:
© 2017 Informa UK Limited, trading as Taylor & Francis Group.

Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.

Keywords

  • Oxidative stress
  • anti-oxidant
  • biomarkers
  • latent variable
  • structural equation modeling

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