## 8 Homo- and Heteronuclear Two-Dimensional (2D) NMR Analysis of Human Saliva
### Sample Size Considerations and MV Power Calculations
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Metabolite Variable** & **R\({}^{2}\)** & **Q\({}^{2}\)** & \(\sigma_{i}{}^{2}\)/\(\sigma_{(ij)}{}^{2}\) * & \
\begin{tabular}{c} **Significance** \\ \(\sigma_{i}{}^{2}\) \\ \end{tabular} &
\begin{tabular}{c} **Significance** \\ \(\sigma_{(ij)}{}^{2}\) \\ \end{tabular} \\ \hline \(n\)-Caproate & 0.72 & 0.55 & 184 & \textless{}10\({}^{-6}\) & ns \\ \(n\)-Butyrate & 0.70 & 0.52 & 61 & \textless{}10\({}^{-6}\) & 0.06 \\ Propionate & 0.69 & 0.50 & 321 & \textless{}10\({}^{-6}\) & \textless{}0.01 \\ Valine & 0.38 & \textless{}0.01 & n/a (\(\sigma_{(ij)}{}^{2}\approx 0\)) & \textless{}10\({}^{-4}\) & ns \\ iso-Butyrate & 0.74 & 0.58 & n/a (\(\sigma_{(ij)}{}^{2}\approx 0\)) & \textless{}10\({}^{-6}\) & ns \\
3-D-Hydroxybutyrate & 0.66 & 0.44 & 885 & \textless{}10\({}^{-6}\) & ns \\ Lactate & 0.68 & 0.47 & 126 & \textless{}10\({}^{-6}\) & ns \\ Acetoin & 0.69 & 0.50 & 63 & \textless{}10\({}^{-6}\) & ns \\ Alanine & 0.70 & 0.50 & 75 & \textless{}10\({}^{-6}\) & ns \\ Thymine & 0.65 & 0.43 & 85 & \textless{}10\({}^{-6}\) & ns \\ Acetate & 0.63 & 0.39 & 24 & \textless{}10\({}^{-6}\) & \textless{}0.01 \\ N-Ac-1 & 0.71 & 0.55 & 33 & \textless{}10\({}^{-6}\) & \textless{}0.01 \\ N-Ac-2 & 0.68 & 0.48 & 50 & \textless{}10\({}^{-6}\) & \textless{}0.05 \\ N-Ac-3 & 0.66 & 0.44 & 27 & \textless{}10\({}^{-6}\) & \textless{}0.01 \\
5-Aminovalerate & 0.63 & 0.40 & n/a (\(\sigma_{(ij)}{}^{2}\approx 0\)) & \textless{}10\({}^{-6}\) & ns \\ Glutamate & 0.65 & 0.43 & 49 & \textless{}10\({}^{-6}\) & ns \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Statistical significance of the ‘between-participants’ and ‘between-sampling days-within-participants’ (\(\sigma_{i}{}^{2}\) and \(\sigma_{(ij)}{}^{2}\), respectively) components of variance in a random effects ANOVA model to determine their contributions towards the WMS supernatant concentrations of a total of 31 \({}^{1}\)H NMR-assigned metabolite variables. All TSP-normalized datasets were glog-transformed and Pareto-scaled prior to analysis. Also shown are the R\({}^{2}\) and Q\({}^{2}\) values for each of these UV models, along with their \(\sigma_{i}{}^{2}/\sigma_{(ij)}{}^{2}\) ratios. * Indicates that values were rounded to the nearest integer. **Figure 8**. _Cont._Figure 8: Plots of observed metabolite concentrations vs. that predicted from the ANOVA-based experimental design model shown in Equation (3) for (**a**) \(n\)-butyrate, (**b**) propionate, and (**c**) urea. Biomolecule concentrations were glog-transformed and Pareto-scaled prior to statistical analysis. 10.1.2. Multivariate Metabolomics Analysis of Distinctive Salivary Phenotypes  
In view of these observations, we further extended these investigations to include MV metabolomics analysis approaches. Therefore, here for the first time, we also preliminarily report a sizeable MV salivary phenotyping study involving the above dataset with n = 48 healthy human participants donating WMS supernatant specimens on five sequential sampling days according to our early morning awakening collection regimen (Section 6). Figure 9 shows the orthogonal T score [1] versus T score [1] plot for (a) an OPLS-DA model performed on only n = 6 randomly selected participants, and (b) the 3D Component 3 vs. Component 2 vs. Component 1 scores plots results from a PLS-DA strategy, which sought to distinguish between and provide phenotypic information on the study participants.