Decoding chronic stress: From behavioral-molecular dynamics in mice to clinical implications of cortisol and IL-17 in...

The etiology of depression involves chronic stress, a recognized determinant of onset and severity. This study adopts a translational approach, utilizing a mouse model and a clinical cohort to explore the relationship between chronic stress, molecular changes, and depression severity.

In the mouse model, mice were exposed to varying frequencies of chronic stressors over several weeks, followed by behavioral assessments to confirm depressive-like behaviors and measurement of serum indicators to analyze their relationship with stress intensity. In the clinical cohort, we recruited 239 participants, including 137 patients with diagnosed depression and 102 healthy controls, and analyzed their plasma profiles for cortisol and inflammatory cytokines. The clinical cohort revealed distinctive plasma profiles, identifying cortisol and IL-17 as potential markers. Machine learning models were developed using these markers to distinguish depression severity.

The study revealed subtle behavioral-molecular changes in mice subjected to varying chronic stress intensities, confirming dose-response relationships. It identified cortisol and IL-17 as potential biomarkers for distinguishing depression severity and developed machine learning models demonstrating robust diagnostic capabilities.

There is a substantial disparity in the number of individuals among different groups in the clinical participants.

The study establishes a correlation between cortisol, IL-17, and chronic stress intensity, suggesting the latter accelerates depression progression. Cortisol and IL-17 exhibit diagnostic potential, providing insights into depression progression and guiding targeted interventions. This research advances our understanding of stress-induced molecular changes in depression, contributing to the comprehension of the intricate relationship between chronic stress, molecular alterations, and depression severity.