A metabolomic approach for predicting diurnal changes in cortisol

Jarrett Eshima, Trenton J. Davis, Heather D. Bean, John Fricks, Barbara S. Smith

Research output: Contribution to journalArticle

Abstract

Introduction: The dysregulation of cortisol secretion has been associated with a number of mental health and mood disorders. However, diagnostics for mental health and mood disorders are behavioral and lack biological contexts. Objectives: The goal of this work is to identify volatile metabolites capable of predicting changes in total urinary cortisol across the diurnal cycle for long-term stress monitoring in psychological disorders. Methods: We applied comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry to sample the urinary volatile metabolome using an untargeted approach across three time points in a single day for 60 subjects. Results: The finalized multiple regression model includes 14 volatile metabolites and 7 interaction terms. A review of the selected metabolites suggests pyrrole, 6-methyl-5-hepten-2-one and 1-iodo-2-methylundecane may originate from endogenous metabolic mechanisms influenced by glucocorticoid signaling mechanisms. Conclusion: This analysis demonstrated the feasibility of using specific volatile metabolites for the prediction of secreted cortisol across time.

Original languageEnglish (US)
Article number194
JournalMetabolites
Volume10
Issue number5
DOIs
StatePublished - May 2020

Keywords

  • Biomarkers
  • Cortisol
  • Diurnal
  • Gcxgc-tofms
  • Mental health
  • Personalized diagnostics
  • Predictive modeling
  • Volatile metabolomics

ASJC Scopus subject areas

  • Endocrinology, Diabetes and Metabolism
  • Biochemistry
  • Molecular Biology

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