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. 2023 Nov 10;14:7293. doi: 10.1038/s41467-023-41767-9

Fig. 1. Reanalysis of baseline plasma lipid mediator profiles supports their potential utility as biomarkers.

Fig. 1

Plasma was collected from RA patients prior to the initiation of treatment with DMARDs and lipid mediator concentrations established using LC-MS/MS-based lipid mediator profiling (see Supplementary Methods for details). A, B OPLS-DA analysis of peripheral blood lipid mediator concentrations for DMARD responders (Resp) and DMARD non-Responders (Non-Resp). A Two-dimensional score plot with the gray circle representing the 95% confidence regions. B Two-dimensional loading plots. Lipid mediators with VIP score greater than 1 are highlighted in blue and upregulated in Non-Resp. Results are representative of n = 30 Resp and n = 22 Non-Resp. C Percentage accuracy score of prediction models based on the combination of all lipid mediators identified and quantified (AL LM) or individual fatty acid metabolomes as indicated. Clin. Score = clinical score (see methods from Gomez et al., for parameters included). D Classification predictions for each class (sensitivity and specificity) of the n-3 DPA model. Green indicates the samples that were predicted as Resp while blue indicates those patients predicted Non-Resp. Percentages indicate true positives (Resp class) and true negatives (Non-Resp class). E Relevance of lipid mediators in the prediction performance of the “ALL LM” model based on decreasing accuracy. F Percentage accuracy score of models using the indicated SPM. G Receiver operating characteristic (ROC) curves and AUC values for predictive models based on the indicated SPM. All the models were created using the random forest methodology (“randomForest” package from R).