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. 2016 Aug;58(8 Suppl 1):S111-6.
doi: 10.1097/JOM.0000000000000763.

Metabolic Pathways and Networks Associated With Tobacco Use in Military Personnel

Dean P Jones  1 , Douglas I Walker, Karan Uppal, Patricia Rohrbeck, Col Timothy M Mallon, Young-Mi Go
Affiliations

Metabolic Pathways and Networks Associated With Tobacco Use in Military Personnel

Dean P Jones et al. J Occup Environ Med. 2016 Aug.

Abstract

Objective: The aim of this study is to use high-resolution metabolomics (HRM) to identify metabolic pathways and networks associated with tobacco use in military personnel.

Methods: Four hundred deidentified samples obtained from the Department of Defense Serum Repository were classified as tobacco users or nonusers according to cotinine content. HRM and bioinformatic methods were used to determine pathways and networks associated with classification.

Results: Eighty individuals were classified as tobacco users compared with 320 nonusers on the basis of cotinine levels at least 10 ng/mL. Alterations in lipid and xenobiotic metabolism, and diverse effects on amino acid, sialic acid, and purine and pyrimidine metabolism were observed. Importantly, network analysis showed broad effects on metabolic associations not simply linked to well-defined pathways.

Conclusions: Tobacco use has complex metabolic effects that must be considered in evaluation of deployment-associated environmental exposures in military personnel.

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Conflict of interest statement

Conflicts of interest: None to declare

Figures

Figure 1
Figure 1
Confirmation of cotinine in serum samples. A, Extracted ion chromatogram of m/z (M+H+) and retention time (sec) detected for cotinine. B, Comparison of MS2 of cotinine in serum sample and authentic reference sample.
Figure 2
Figure 2
PLS-DA-identified 41 metabolites at cotinine threshold of 10 ng/mL. Top metabolites included nicotine metabolites, cotinine and hydroxycotinine. Additional discriminatory metabolites included endogenous metabolic intermediates, xenobiotics and lipids.
Figure 3
Figure 3
Hierarchical clustering and correlation of cotinine and hydroxycotinine. A, Unsupervised, hierarchical clustering showed clustering of individuals with high serum cotinine and hydroxycotinine levels. B, Correlation of cotinine and hydroxycotinine for 400 samples.
Figure 4
Figure 4
Pathway enrichment analysis. Metabolic pathways exhibiting a Mummichog significance score < 0.1 and with ≥ 4 metabolites present from either the PLS-DA selected or network correlation significant features. Significant pathways included fatty acid, amino acid, purine, pyrimidine and xenobiotic metabolism.
Figure 5
Figure 5
Network correlation analysis. 225 m/z features (green triangles) were correlated with 15 metabolites (red circles) selected using PLS-DA (blue edges; r ≥ 0.5, red edges; r ≤ 0.5). Annotation of network correlation features included amino acids, xenobiotics, vitamins and cofactors.
See this image and copyright information in PMC

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