Korean J Biol Psychiatry.  2024 Oct;31(2):20-33. 10.22857/kjbp.2024.31.2.002.

A Review of Magnetic Resonance Imaging-Based Brain Age Prediction in Major Depressive Disorder

• Yu S
• Joo Y
• Yoon S

• KMID: 2561299
• DOI: http://doi.org/10.22857/kjbp.2024.31.2.002

Abstract

Objectives
Recent advances in brain age prediction models reveal accelerated brain aging in major depressive disorder (MDD) patients. This review investigates the complex relationship between brain aging and biological age gap (BAG) in MDD, emphasizing the influences of clinical characteristics, treatment responses, and various neuroimaging techniques on this dynamic interplay.
Methods
A systematic review of the existing literature was conducted, focusing on 18 studies that analyze brain aging patterns in MDD patients. Key factors such as age, clinical features, and lifestyle choices were examined to assess their impact on BAG and the overall neurobiological health of individuals with MDD.
Results
The findings indicate that MDD patients frequently experience accelerated brain aging, particularly in elderly populations, with BAG serving as a valuable biomarker for assessing biological aging rates. The review highlights the urgent need for more granular approaches, considering variables such as age, gender, and socioeconomic status. Specific local brain aging patterns were observed in regions related to emotional regulation, suggesting that localized BAG changes may provide critical insights into the pathophysiology of MDD and its neurobiological underpinnings.
Conclusions
BAG is a significant biomarker for evaluating accelerated brain aging in MDD, informing personalized treatment strategies. Future research should incorporate diverse clinical characteristics and advanced neuroimaging techniques in representative samples to enhance the clinical applicability of BAG and deepen the understanding of its role in depression and biological aging.

Keyword

Major depressive disorder; Brain age; Magnetic resonance imaging; Machine learning