## 3 Results  
### Method Development  
Thirteen chromatographic methods in positive mode and twelve methods in negative mode were tested on both the Accucore C18 HPLC column and the Accucore C30 HPLC column. Overall, both columns provided similar separation of lipids and good peak shapes. The Accucore C30 column resulted in slightly narrower peaks with less tailing. Thus, the Accucore C30 column was selected as the more favorable column for lipid analysis. Each chromatographic method that was then tested on the Accucore C30 HPLC column had different solvents, additives, and gradients. Many of the methods were not capable of generating a good separation of lipids with a good peak shape. Methods that used water and acetonitrile as mobile phases tended to perform poorly, while methods that used methanol instead of acetonitrile in their mobile phase B were found to generate good separation of lipids and good peak shapes. No singular method, however, was able to capture all lipids adequately. The method that was best for analyzing larger lipids such as glycerophospholipids, glycerolipids, sterol lipids, and sphingolipids was not the best for analyzing smaller lipids such as fatty acids. These differences in lipid analysis may be due to the lipid categories or may be because of the size of the lipids. Method 11 in positive mode and method 8 in negative mode were selected as the chromatographic methods of choice because they provided narrow, symmetrical peaks for most of the fatty acids and fatty acid-like molecules, which were our focus, as mentioned, based on previous research. Regardless, the methods also performed well for many of the other lipids. The two selected methods were then optimized to achieve the best initial conditions and gradient. The initial percentage of solvent B was increased from 0% to 30%. Both methods showed a similar pattern, where larger initial percentages of B resulted in wider, more asymmetrical peaks. In positive mode, the method showed the best peak shapes at 5% solvent B. In negative mode, solvent B was selected to be the best at 0%. The curvature of each method's gradient was then modified into a concave down or concave up curve. A concave up gradient increased the retention time of almost all the compounds, while a concave down gradient decreased the retention time. The concave down gradient was selected for both methods because the lower retention time elution of metabolites would allow for more compounds to be separated on the column while preserving good peak shape and a shorter chromatographic method. The final optimized methods are shown in Figure 1 with the extraction ion chromatograms of our fatty acid-like molecules and derivatives. Although the methods captured many of the lipids with great ability, there were a few lipids that were not observed as narrow, symmetrical peaks (see Tables 7 and 8 for full list). Dodecanedioloic acid and 12-aminolauric acid were well detected in both positive and negative modes. Isobutyryl-L-carnitine was poorly analyzed in negative mode but well analyzed in positive mode. 1,11-undecanediolcarboxylic acid and 10-hydroxy-2-decenoic acid were only able to be analyzed in negative mode. the retention time were recorded. All quality control standards had a peak area RSD < 9% and a retention time RSD < 1%. Deuterated internal standards added to each sample for monitoring metabolite extraction and instrumental analysis had peak area RSDs < 6% and retention time RSDs < 1%. The low variation (<9% and 1% RSD) indicates the method performed well during serum sample instrumental acquisition over a three-day run. Principal component analysis (PCA) was employed to produce a graphical representation of the dataset (Figure 2). PCA is an unsupervised multivariate approach that facilitates the identification of patterns, laying the groundwork for the construction of subsequent supervised models. The pooled QC (a composite of all samples) was injected throughout the analysis every 10 samples.