Accelerated functional brain aging in major depressive disorder: evidence from a large scale fMRI analysis of Chinese participants
Yunsong Luo, Wenyu Chen, Jiang Qiu, Tao Jia

TL;DR
This study demonstrates that major depressive disorder (MDD) is associated with accelerated brain aging in Chinese participants, using a large-scale fMRI dataset and machine learning to estimate brain age differences.
Contribution
It validates the brain age acceleration biomarker in a Chinese cohort using resting-state fMRI and machine learning, expanding previous findings beyond Caucasian populations.
Findings
MDD patients show +4.43 years higher brain-PAD compared to controls
Antidepressant users exhibit +2.09 years higher brain-PAD than medication-free patients
Functional connectivity-based age estimation confirms accelerated brain aging in MDD
Abstract
Major depressive disorder (MDD) is one of the most common mental health conditions that has been intensively investigated for its association with brain atrophy and mortality. Recent studies reveal that the deviation between the predicted and the chronological age can be a marker of accelerated brain aging to characterize MDD. However, current conclusions are usually drawn based on structural MRI information collected from Caucasian participants. The universality of this biomarker needs to be further validated by subjects with different ethnic/racial backgrounds and by different types of data. Here we make use of the REST-meta-MDD, a large scale resting-state fMRI dataset collected from multiple cohort participants in China. We develop a stacking machine learning model based on 1101 healthy controls, which estimates a subject's chronological age from fMRI with promising accuracy. The…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
