## 5 Conclusions  
In this study, sample preparation with Thin-Film SPME with LC-HRMS analysis facilitated the untargeted metabolomics assessment of psoriasis disease activity in serum samples obtained from PsA patients classified according to the PASI. The PCA did not exhibit any clear separation between PASI-based disease activity groups, but machine learning models were able to predict disease activity to an acceptable degree of success. Features used in the creation of successful ML models were tentatively identified, and commonly belong to compound classes like bile acids, lipoxins, and phospholipids. These compounds have been found to be associated with pathways such as fatty acid metabolism  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Time (min)** & **\% Mobile Phase B** \\  & **(Methanol + 0.1\% Formic Acid)** \\ \hline
0 & 5 \\ \hline
1 & 5 \\ \hline
20 & 100 (curve 3) \\ \hline
22.5 & 100 \\ \hline
25 & 5 \\ \hline
30 & 5 \\ \hline \hline \end{tabular}
\end{table}
Table 7: Liquid chromatographic gradient used for separation in positive mode with an accucore C30 HPLC column (100 mm \(\times\) 2.1 mm, 2.6 μm).  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Time (min)** & **\% Mobile Phase B (Methanol)** \\ \hline
2 & 0 \\ \hline
12 & 100 (curve 3) \\ \hline
15 & 100 \\ \hline
18 & 0 \\ \hline
20 & 0 \\ \hline \hline \end{tabular}
\end{table}
Table 8: Liquid chromatographic gradient used for separation in negative mode with an accucore C30 HPLC column (100 mm \(\times\) 2.1 mm, 2.6 μm).  
and immune-mediated pathways that have been implicated in PsA. This opens a possible direction for future research in metabolite differences based on disease severity in psoriatic arthritis disease. A follow-up study using the same SPME-LC-MS method should be conducted to confirm the results, but should include rigorous patient selection to account for comorbidities, treatments, and should also include rigorous MS/MS spectral validation.  
The supporting information can be downloaded at: [[https://www.mdpi.com/article/10.3390/ijms242015299/s1](https://www.mdpi.com/article/10.3390/ijms242015299/s1)]([https://www.mdpi.com/article/10.3390/ijms242015299/s1](https://www.mdpi.com/article/10.3390/ijms242015299/s1)).  
Conceptualization, V.C., I.J. and V.K.; Methodology, N.L., H.C. and S.L.; Software, N.L. and M.K.; Formal Analysis, H.C., S.L., N.L. and M.K.; Investigation, H.C., S.L. and N.L.; Resources, I.J., V.K. and V.C.; Data Curation, H.C. and S.L.; Writing--Original Draft Preparation, H.C. and S.L.; Writing--Review and Editing, S.L., H.C., N.L., M.K., I.J., V.K. and V.C.; Visualization, S.L., H.C., M.K. and N.L.; Supervision, V.C., I.J. and V.K.; Project Administration, N.L.; Funding Acquisition, V.C. All authors have read and agreed to the published version of the manuscript.  
This research was funded by Canadian Institutes of Health Research, grant number 178388. H.C. is supported by the Canadian Association of Psoriasis Patients and the Canadian Institutes of Health Research Studentship in Psoriatic Disease. S.L. is supported by the Canada Graduate Scholarship--Master's. V.C. is supported by a Pfizer Chair Research Award, Rheumatology, University of Toronto. The Psoriatic Disease Program at the Schroeder Arthritis Institute, University Health Network is supported by the Krembil Foundation.  
The study was conducted in accordance with the Declaration of Helsinki, and approved by the University Health Network Research Ethics Board (protocol code 21-5311, 14 July 2022).  
Informed Consent Statement: Informed consent was obtained from all subjects involved in the study.  
The authors thank [PERSON] for administrative support and [PERSON] for biobank support.  
The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.