Depression and aging: insights from brain age prediction models.

Area of Science:

• Neuroscience
• Psychiatry
• Aging Research

Background:

• The relationship between depression and brain aging is not fully understood, though both are associated with stress.
• Shared biological pathways may influence structural brain changes in depression and aging.
• Investigating these links can improve understanding of depression and aging mechanisms.

Purpose of the Study:

• To investigate the association between major depressive disorder (MDD) and brain age.
• To explore the influence of childhood maltreatment and cortisol awakening response on brain age in individuals with MDD.
• To identify the optimal brain age prediction model for analyzing structural MRI data.

Main Methods:

• Structural MRI scans from 190 participants (110 controls, 80 with MDD) were analyzed using three brain age prediction models.
• DeepBrainNet was selected for its high accuracy in predicting brain age.
• Brain-predicted age difference (brain-PAD) was calculated, and linear regression examined the impact of MDD, childhood maltreatment, and cortisol awakening response.

Main Results:

• Major depressive disorder (MDD) was associated with age-dependent differences in brain-predicted age difference (brain-PAD).
• Older adults with MDD showed greater positive deviations in brain age, indicating non-uniform brain aging.
• A higher cortisol awakening response was linked to younger-appearing brains (lower brain-PAD), and females had lower brain-PAD than males.

Conclusions:

• Major depressive disorder (MDD) is associated with accelerated brain aging in an age-dependent manner.
• The cortisol awakening response may have a protective effect on brain age, highlighting the role of stress biomarkers.
• Integrating stress biomarkers is crucial for understanding neural aging in depression.