Plasma or Serum? A Pilot Evaluation of Matrix Selection for Integrated Metabolomics and Exposomics of Clinical...

Serum and plasma are the most widely used matrices in metabolomics and human biomonitoring studies; however, the optimal matrix for integrated non-targeted analysis (NTA) workflows combining metabolomics and exposomics has not been systematically evaluated. This pilot study applied parallel NTA workflows to paired serum and plasma samples from five individuals to characterize matrix-dependent differences and provide an empirical basis for matrix selection in integrated studies. Three analytical methods were employed: one metabolomic method (Method 1) using Hydrophilic Interaction Liquid Chromatography (HILIC) and Reversed-Phase Liquid Chromatography (RPLC) columns and one exposomics (Method 2) method using an RPLC column, each analyzed in both electrospray ionization (ESI) positive and negative modes. Overall, serum and plasma showed broad similarity, with substantial overlap in detected features and strong linear correlations between paired samples (R² = 0.70-0.87). However, PCA revealed systematic differences between the two matrices along PC1 and PC2, likely attributable to matrix effects arising from coagulation-related compositional changes in serum. For metabolomics, glycerophospholipids, sphingolipids, and acylcarnitines were consistently enriched in serum, attributable to platelet activation and phospholipase release during blood coagulation, consistent with prior reports. In contrast, oxidized fatty acid species were predominantly elevated in plasma, warranting caution in oxylipin-focused studies using serum. For exogenous chemical profiling, the two matrices performed comparably, with 32 out of 36 annotated features showing no significant matrix-dependent differences (p > 0.05), including PFAS, pharmaceuticals, and diverse xenobiotics. These findings support the interchangeability of serum and plasma for broad exposomics studies. Overall, while both matrices provided broadly comparable global coverage, plasma may represent a more appropriate matrix for integrated NTA workflows, as it better preserves in vivo metabolite composition and minimizes coagulation-induced confounding, though validation in larger cohorts is needed.