Endocrine and Metabolic Science (Dec 2023)

Comprehensive assessment of cortisol and cortisol metabolites provides insight into the complex relationship between HPA axis function and BMI

  • Mark S. Newman,
  • Jaclyn Smeaton

Journal volume & issue
Vol. 13
p. 100147

Abstract

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Aims/objectives: Although considerable effort, both experimental and theoretical, has been directed towards understanding the relationship between the HPA axis and weight regulation, no true consensus exists in the literature as to the nature of the relationship. The aim of this study was to explore potential correlations between BMI and measures of cortisol and cortisol metabolites using dried urine and saliva sampling in a large sample of individuals with BMIs ranging from underweight to obese. Materials and methods: A cohort of patients with data available from urinary and/or salivary measures of cortisol and cortisol metabolites who met inclusion criteria was extracted from the database of a commercial clinical laboratory. Pearson correlation coefficients were used to determine associations between variables; Student's t-test and one-way ANOVA were used to examine differences between groups, and the Jonckheere-Terpstra trend test was used to assess for trends by BMI category. A multivariable linear regression model was created to determine which variables explained the largest amounts of variance in BMI. Results: A significant correlation was observed between the urinary cortisol metabolites and BMI (P < 0.0001). In addition, cortisol metabolites were associated with changes in BMI over time. No significant correlation was observed between urinary free cortisol and BMI, and correlations observed between BMI and other variables, with the exception of age, were either weak or not statistically significant. Conclusions: The data presented in this study suggest that cortisol metabolism is a key component of weight regulation and that cortisol metabolite concentrations may potentially serve as informative biomarkers to characterize the relationship between the HPA axis and changes in BMI. The implications of this affect both clinical practice and the research and development of both prevention and treatment strategies aimed at either decreasing or increasing BMI.

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