In vitro/in vivo screening of oxidative homeostasis and damage to DNA, protein, and lipids using UPLC/MS-MS

Aitor Carretero1, Zacarías León, Juan Carlos García-Cañaveras

  • 1Unidad de Hepatología Experimental, Instituto de Investigación Sanitaria - Fundación Hospital La Fe, CIBERehd, Centro de Investigaciones Biomédicas en Red de Enfermedades Hepáticas y Digestivas, FIS, 46026, Valencia, Spain.

Insights

A new UPLC-MS/MS method quantifies 16 oxidative stress biomarkers for assessing cellular damage. This approach efficiently measures oxidative homeostasis in both lab and patient samples, identifying ophthalmic acid as a novel biomarker.

Area of Science:

  • Biochemistry
  • Analytical Chemistry
  • Biomarker Discovery

Background:

  • Assessing oxidative homeostasis and macromolecular damage requires multiple analytical methods.
  • A need exists for a streamlined approach to quantify global oxidative status and specific damage to DNA, proteins, and lipids.

Purpose of the Study:

  • To develop a straightforward, fast analytical strategy for assessing oxidative stress (OS) biomarkers.
  • To quantify 16 OS biomarkers using a single, validated method.

Main Methods:

  • Ultra-performance liquid chromatography coupled to tandem mass spectrometry (UPLC-MS/MS).
  • Sample treatment involving fractionation and derivatization for unstable markers.
  • Validation according to Food and Drug Administration (FDA) guidelines.

Main Results:

  • The UPLC-MS/MS method quantified 16 OS biomarkers with good precision, accuracy, and linearity.
  • The method successfully assessed oxidative insult in cultured rat hepatocytes and in liver/serum samples from nonalcoholic steatohepatitis patients.
  • Ophthalmic acid was identified as an OS biomarker in both experimental models for the first time.

Conclusions:

  • A single UPLC-MS/MS method can comprehensively assess 16 OS biomarkers, simplifying multi-method approaches.
  • The validated method is suitable for profiling oxidative homeostasis and damage in both in vitro and clinical samples.
  • This approach aids in evaluating the extent of OS involvement in physiological signals, diseases, and toxic events.

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