Neuroimaging-derived brain age as a new promising biomarker in mental disorders

Mental disorders are frequently associated with accelerated brain aging, yet the diagnostic and classificatory utility of brain age remains uncertain. This study aimed to evaluate the diagnostic value of brain age across multiple mental disorders and to identify the underlying neural mechanisms. Articles published through November 2025 were retrieved from PubMed, Web of Science, and Embase, resulting in 68 eligible studies covering DSM-5 diagnostic categories. We compared brain age across disorders and extracted key contributing brain regions. The largest effect was observed in schizophrenia spectrum disorders (Cohen's d = 3.49, 95 % CI 2.62-4.37, p < 0.05), followed by neurocognitive disorders (Cohen's d = 3.27, 95 % CI 2.31-4.24, p < 0.05), mood disorders (Cohen's d = 1.41, 95 % CI 0.69-2.14, p < 0.05), and neurodevelopmental disorders (mean = 0.60). Analysis of covariance indicated a significant effect of diagnostic category on brain age (F = 5.13, p = 0.004), and Bonferroni tests further confirmed intergroup differences (p < 0.05). The central executive, default mode, and salience networks, emerged as a common system implicated across disorders, although the relative contributions differed by diagnosis. Overall, these findings suggest that brain age may serve as a biomarker for the diagnosis and classification of mental disorders.

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Publication Details

Journal
Neuroscience & Biobehavioral Reviews
Published
2026-02-13
DOI
https://doi.org/10.1016/j.neubiorev.2026.106606
Primary Topic
Functional Brain Connectivity Studies
Type
article
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article

Neuroimaging-derived brain age as a new promising biomarker in mental disorders

Taolin Chen, Ruopeng Zhao, Xiqin Liu, Zhiyun Jia et al.
Neuroscience & Biobehavioral Reviews
Functional Brain Connectivity Studies
article

Neuroimaging-derived brain age as a new promising biomarker in mental disorders

Taolin Chen, Ruopeng Zhao, Xiqin Liu, Zhiyun Jia, Qiyong Gong, Ruiyang Ge, Xueyi Zhang, Zheng Zhang, Weihua Zhao
article en

Abstract

Mental disorders are frequently associated with accelerated brain aging, yet the diagnostic and classificatory utility of brain age remains uncertain. This study aimed to evaluate the diagnostic value of brain age across multiple mental disorders and to identify the underlying neural mechanisms. Articles published through November 2025 were retrieved from PubMed, Web of Science, and Embase, resulting in 68 eligible studies covering DSM-5 diagnostic categories. We compared brain age across disorders and extracted key contributing brain regions. The largest effect was observed in schizophrenia spectrum disorders (Cohen's d = 3.49, 95 % CI 2.62-4.37, p < 0.05), followed by neurocognitive disorders (Cohen's d = 3.27, 95 % CI 2.31-4.24, p < 0.05), mood disorders (Cohen's d = 1.41, 95 % CI 0.69-2.14, p < 0.05), and neurodevelopmental disorders (mean = 0.60). Analysis of covariance indicated a significant effect of diagnostic category on brain age (F = 5.13, p = 0.004), and Bonferroni tests further confirmed intergroup differences (p < 0.05). The central executive, default mode, and salience networks, emerged as a common system implicated across disorders, although the relative contributions differed by diagnosis. Overall, these findings suggest that brain age may serve as a biomarker for the diagnosis and classification of mental disorders.

Neuroscience & Biobehavioral ReviewsVol. 184
University of British Columbia (CA), University of Electronic Science and Technology of China (CN), Chinese Academy of Medical Sciences & Peking Union Medical College (CN), Sichuan University (CN), West China Hospital of Sichuan University (CN)
Openalex Percentile: Top 59%
Functional Brain Connectivity Studies
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