# Effects of Workers Exposure to Nanoparticles Studied by NMR Metabolomics
## 3 Results and Discussion
### Exhaled Breath Condensate  
Since exhaled breath condensate is composed of 99.9% water, the other constituents are rather diluted. For this reason, quantitative analysis of 1H NMR spectra using the Chenomx reference library provided only 15 metabolites. Due to the limited number of metabolites quantified, a meaningful multivariate statistical analysis cannot be performed on such a dataset. However, univariate statistical analysis identified some of the metabolites as statistically significant for discrimination of the groups studied. A Wilcoxon rank-sum test showed that pre-shift and post-shift EBC samples are mainly characterized by significantly elevated levels of acetoin and propionate, and decreased acetone, isopropanol and lactate levels when compared to control samples (Table S2, Supplementary Materials). On the other hand, an increase in dimethylamine and decrease in acetoin are the most significant changes induced by NPs exposure as observed in comparison of pre-shift and post-shift EBC samples (Figure 1). Final group discrimination analysis was performed using binning data. Fingerprinting of individual 1H NMR spectra provided 320 bins which subsequently served as an input into multivariate statistical analysis. Principal component analysis (PCA) of all binned spectra did not show any significantly outlying sample. It also indicated certain trends in group separation; however, a clear discrimination was not achieved (Figure S3, Supplementary Materials). Satisfactory group separation was achieved by orthogonal partial least squares discriminant analysis (OPLS-DA), which was applied to the pre-shift and control group to reveal the chronic effect of NPs exposure and to the pre-shift/post-shift and post-shift/control group to uncover the acute effect. An excellent separation between the pre-shift and control group was achieved using three components. The model was characterized by 81.4% sensitivity, 94.8% specificity and 88.1% accuracy after Monte Carlo cross-validation (Figure 2a). Similarly, the separation of post-shift and the control group was achieved using a seven-component model yielding 88.7% accuracy, 93.9% sensitivity and 83.5% specificity after Monte Carlo cross-validation (Figure 2b). Figure 1: Fold change projections depicting differences in levels of individual metabolites observed in EBC samples between individual groups. The bins contributing significantly to the group separation were identified from OPLS-DA loadings provided by Metaboanalyst. These bins show increased EBC concentration of acetoin, acetate and propionate in the pre-shift and post-shift samples when compared to the controls. Mainly increased signal intensities of alcohols were found in controls. These findings correspond well with the statistically significant compounds identified by univariate statistics as discussed above (Figure 1). The comparison of the pre-shift and post-shift groups should reveal the acute effect of NPs exposure. The performed OPLS-DA provided a very good discrimination of the two groups using six components with accuracy of 83.1%, sensitivity of 84.1% and specificity of 82.1% after Monte Carlo cross-validation (Figure 3a). As both groups consist of the same 20 subjects whose samples were collected before and after the shift, a pairwise multilevel partial least squares (mPLS) analysis can be applied [36]. Compared to other PLS analyses, mPLS does not focus on investigation of the studied groups as a whole, but rather observes changes in each individual before and after the stimulus of the change and reflects the changes occurring within the same subject. The mPLS analysis showed a satisfactory discrimination of the two groups using three components with 82.0% accuracy after Monte Carlo cross-validation (Figure 3b). Although the OPLS and the mPLS models show similar accuracy, the mPLS model requires fewer components. Figure 3: OPLS-DA of pre-shift (yellow circles) and post-shift subjects (red squares); Acc. 83.1%, Sen. 84.1%, Spe. 82.1% (a).