Metabolome-Wide Association Study of Deployment to Balad, Iraq or Bagram, Afghanistan

Abstract

Objective: To use high-resolution metabolomics (HRM) to identify metabolic changes in military personnel associated with deployment to Balad, Iraq, or Bagram, Afghanistan.

Methods: Pre- and post-deployment samples were obtained from the Department of Defense Serum Repository (DoDSR). HRM and bioinformatics were used to identify metabolic differences associated with deployment.

Results: Differences at baseline (pre-deployment) between personnel deployed to Bagram compared with Balad or Controls included sex hormone and keratan sulfate metabolism. Deployment to Balad was associated with alterations to amino acid and lipid metabolism, consistent with inflammation and oxidative stress, and pathways linked to metabolic adaptation and repair. Difference associated with deployment to Bagram included lipid pathways linked to cell signaling and inflammation.

Conclusions: Metabolic variations in pre- and post-deployment are consistent with deployment-associated responses to air pollution and other environmental stressors.

FIGURE 1.

Central model for exposome research. The human exposome consists of many exposures (left). Internal doses of many chemicals (middle left), along with metabolic responses (middle right), are measured by high-resolution metabolomics. The internal metabolic responses are correlated with outcomes (right).

FIGURE 2.

Metabolic responses associated with pre- and post-deployment. The 373 serum samples of pre-deployment [Balad (n = 150), Bagram (n = 37), Control (n = 186)] were analyzed for HRM and differences of metabolic features in pre-deployment were presented by unsupervised HCA-heatmap after selection of significant features determined by LIMMA using FDR < 0.2 (A) and PCA [Green (control), Red (Bagram), Yellow (Balad), B]. C, Mummichog pathway enrichment analysis on 1034 m/z features showed that alterations in metabolic pathways of androgen and estrogen, keratin, N-glycan, and vitamin E were observed in the 3 groups prior to deployment. (Filled bars indicate significance and the cutoff (p<0.05) is indicated by the dotted line). D, The 374 serum samples of pre- and post-deployment [Balad (n = 150), Bagram (n = 37)] were analyzed for HRM and 1757 m/z features associated with deployment were presented by unsupervised HCA-heatmap.

FIGURE 3.

Metabolic responses associated with deployment to Balad, Afghanistan. The 300 serum samples (n = 150 each pre and post-deployment) collected from pre- and post-deployment to Balad were analyzed by HRM. A, Type I Manhattan plot of m/z features plotted against the −Log₁₀ P value indicates that 1030 features are altered after deployment to Balad [red (658 increased after deployment) and blue (377 decreased after deployment) at FDR < 0.2; gray (2180) were not affected by deployment], B, Type II Manhattan plot using retention time (RT, s) plotted against −Log₁₀ P value. C, Unsupervised HCA-heatmap indicates that intensity of 1035 m/z features drive the separation between the pre and post-deployment to Balad. D, PCA plot of selected significant features using the above selection criteria showing separation of the pre-deployment (red) and post-deployment group (green), through the 1^st (19% variation) and 2^nd (6% variation) principal components.

FIGURE 4.

Pathway enrichment analysis associated with deployment. Mummichog pathway analysis on metabolic features differentiating Pre and Post deployment to Balad (A), Bagram (B), and Control (C). (Filled bars indicate significance and the cutoff (p<0.05) is indicated by the dotted line). For complete annotation of metabolites in each respective pathway, please see Supplemental Table 4.

FIGURE 5.

Metabolic responses associated with deployment to Bagram. The 74 serum samples (n = 37 each pre and post-deployment) collected from pre- and post-deployment to Bagram were analyzed for HRM. A, Type I Manhattan plot of m/z features plotted against the −Log₁₀ P value indicates that 75 features are altered after deployment to Bagram [red (20 increased after deployment) and blue (55 decreased after deployment) at FDR < 0.2; gray (3255) were not affected by deployment], B, Type II Manhattan plot using retention time (RT, s) plotted against −Log₁₀ P value. C, Unsupervised HCA-heatmap indicates that intensity of 75 m/z features drive the separation between the pre and post-deployment to Bagram. D, PCA plot of selected significant features using the above selection criteria showing separation of the pre-deployment (red) and post-deployment group (green), through the 1^st (38% variation) and 2^nd (9% variation) principal components.

FIGURE 6.

Metabolic responses associated with deployment in Control group. The 372 serum samples (n = 186 each pre and post-deployment) collected from pre- and post-deployment to Bagram were analyzed for HRM. A, Type I Manhattan plot of m/z features plotted against the −Log₁₀ P value indicates that 56 features are altered after deployment to Bagram [red (25 increased after deployment) and blue (31 decreased after deployment) at FDR < 0.2; gray (3037) were not affected by deployment], B, Type II Manhattan plot using retention time (RT, s) plotted against −Log₁₀ P value. C, Unsupervised HCA-heatmap indicates that intensity of 56 m/z features drive the separation between the pre and post-deployment to Bagram. D, PCA plot selected significant features using the above selection criteria showing separation of the pre-deployment (red) and post-deployment group (green), through the 1^st (23% variation) and 2^nd (7% variation) principal components.

FIGURE 7.

Association of environmental chemicals with the metabolome. The 1037 m/z features associated with deployment to Balad (Fig 3) were examined for association with 271 environmental chemicals (See Smith et al. in the present Supplement) (A), PAH (B) and cotinine (3) (C) using xMWAS (12). A, Two major metabolic communities are identified; blue, environmental chemicals Ametryn and Dinotefuran association with 32 m/z features, which included the putative annotations the pesticide Sulfuramid, and the bacterial metabolite Janthitrem C; orange, metabolic community with anthelmintic agent metrifonate are shown, which was associated 119 m/z features which included the purine metabolites guanosine pentaphosphate and guanosyl-methylene triphosphate, the biopterin pathway metabolite dihydroneopterin 3-triphosphate, and the dipeptide arginyl-glutamine (r < 0.5 at p < 0.05). B, Two metabolic communities were associated with PAH’s. Blue, community includes two m/z features associated with benzo(ghi)perylene, one of which was annotated as the alkaloid neurine. Orange, includes twenty-four m/z features associated fluoranthene, and included the (protein breakdown product glutamyl-glutamine and (iso)leucyl-(iso)leucine), the lipids sphingosine and sphinganine, and the omega-3 fatty acid eicosapentaenoic acid (r < 0.25 at p < 0.05). C, cotinine is associated with 19 m/z features and include Sulfuramid, Janthitrem C, metrifonate, and the alkaloid isococculidine r < 0.35 at p < 0.05).