A liquid chromatography- tandem mass spectrometry method for the analysis of oxidative stress, nitrative stress, metabolic, and inflammatory biomarkers in serum: comparison to urinary concentrations.

Precision medicine relies on the analysis of biofluids to detect and quantify biomarkers, among others, of health effects. Urine and serum are key biofluids that provide critical information about a patient's health and disease burden. In this study, a liquid chromatography-tandem mass spectrometry (LC-MS/MS) method was developed and validated for the analysis of 18 serum biomarkers of oxidative stress [dityrosine (diY), 8-hydroxy-2'-deoxyguanosine (8-OHdG), 8-hydroxyguanine (8-HG), and 8-hydroxyguanosine (8-HdG), 8-isoprostaglandin-F2α (8-PGF2α), 11-β-prostaglandin-F2α (11-PGF2α), 15-prostaglandin-F2α (15-PGF2α), 8-iso-15-prostaglandin-F2α (8,15-PGF2α), malondialdehyde (MDA), 4-hydroxynonenal glutathione (HNE-GHS), 4-hydroxynonenal mercapturic acid (HNE-MA), and allantoin (Alla)], nitrative stress [nitrotyrosine (NY), and 8-nitroguanosine (8-NdG)], inflammation [bromotyrosine (BY), and chlorotyrosine (CY)], and metabolic disorder [Nε-(1-carboxyethyl)-l-lysine (CEL), and Nε-(1-carboxymethyl)-l-lysine (CML)]. The method was applied for the analysis of 15 serum samples, and the results were compared with paired urine samples analyzed using a previously validated method for the same panel of biomarkers. The mean volumetric concentrations of MDA, 8-PGF2α, 11-PGF2α, 15-PGF2α, and 8,15-PGF2α were significantly higher in serum than urine (p < 0.05). A moderate positive correlation (ρ = 0.775, p < 0.05) existed for the concentrations of CML, but not other biomarkers, between serum and urine. Our results showed that the target biomarkers analyzed in urine and serum exhibited distinct profiles. The health implications of biomarkers measured in urine relative to that in serum require further investigation. Paired analysis of urine and serum biomarkers may offer a more comprehensive approach to health monitoring, disease diagnosis and personalized medicine.