Altered brain structure age gap estimation in major depressive disorder patients with and without anhedonia: a machine learning-based study
Abstract Previous studies have found that major depressive disorder (MDD) may accelerate overall structural brain aging. Nevertheless, it still remains unknown whether anhedonia, a critical negative prognostic indicator in MDD, further leads to advanced brain aging in specific regions. A total of 31...
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Nature Publishing Group
2025-08-01
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| Series: | Translational Psychiatry |
| Online Access: | https://doi.org/10.1038/s41398-025-03555-5 |
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| author | Qingli Mu Kejing Zhang Yue Chen Yuwei Xu Shaohua Hu Manli Huang Peng Zhang Dong Cui Shaojia Lu |
| author_facet | Qingli Mu Kejing Zhang Yue Chen Yuwei Xu Shaohua Hu Manli Huang Peng Zhang Dong Cui Shaojia Lu |
| author_sort | Qingli Mu |
| collection | DOAJ |
| description | Abstract Previous studies have found that major depressive disorder (MDD) may accelerate overall structural brain aging. Nevertheless, it still remains unknown whether anhedonia, a critical negative prognostic indicator in MDD, further leads to advanced brain aging in specific regions. A total of 31 MDD with anhedonia (MDD-WA), 41 MDD without anhedonia (MDD-WoA), and 43 healthy controls (HCs) were recruited in this study. The difference between brain structure age (BSA) applied by support vector regression (SVR) and chronological age was calculated to derive the brain structure age gap estimation (BSAGE). Analyses of covariance (ANCOVAs) and intergroup comparisons were performed to obtain brain regions with significant BSAGE differences among three groups. Moreover, a support vector machine (SVM) classification model was used to verify the diagnostic value of altered BSAGE. ANCOVAs revealed significant BSAGE differences among three groups in the bilateral putamen (PU), left cerebellar white matter (CB), left cuneus (CUN), left fusiform gyrus (FuG), left subcallosal area (SCA), left superior occipital gyrus (SOG), left triangular inferior frontal gyrus (IFG-Tri), right lateral ventricle (L-V), right superior frontal gyrus medial segment (SFG-SM), right opercular inferior frontal gyrus (IFG-Oper), right precuneus (pre-CUN), right posterior insula (INS-Post), and right superior temporal gyrus (STG). Compared to HCs, the MDD-WA group showed significant BSAGE increase in all of the aforementioned brain regions, while the MDD-WoA group showed limited BSAGE increase in the CB, FuG, and SCA of left hemisphere only. However, no significant difference was found between MDD-WA and MDD-WoA. The altered BSAGE values showed promising discriminatory performance with an area under the curve (AUC) of 0.944 in classifying MDD-WA and HCs. The current findings emphasize that MDD with anhedonia may exhibit more extensive advanced brain aging, primarily in the frontal-limbic system, temporal lobe, and parietal lobe. |
| format | Article |
| id | doaj-art-0ad1ccdcd5f74af78cc275805e6ff5b1 |
| institution | Kabale University |
| issn | 2158-3188 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Nature Publishing Group |
| record_format | Article |
| series | Translational Psychiatry |
| spelling | doaj-art-0ad1ccdcd5f74af78cc275805e6ff5b12025-08-24T11:51:38ZengNature Publishing GroupTranslational Psychiatry2158-31882025-08-011511910.1038/s41398-025-03555-5Altered brain structure age gap estimation in major depressive disorder patients with and without anhedonia: a machine learning-based studyQingli Mu0Kejing Zhang1Yue Chen2Yuwei Xu3Shaohua Hu4Manli Huang5Peng Zhang6Dong Cui7Shaojia Lu8Department of Psychiatry, The First Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang Key Laboratory of Precision Psychiatry, Zhejiang Engineering Center for Mathematical Mental HealthDepartment of Psychiatry, The First Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang Key Laboratory of Precision Psychiatry, Zhejiang Engineering Center for Mathematical Mental HealthDepartment of Psychiatry, The First Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang Key Laboratory of Precision Psychiatry, Zhejiang Engineering Center for Mathematical Mental HealthDepartment of Psychiatry, The First Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang Key Laboratory of Precision Psychiatry, Zhejiang Engineering Center for Mathematical Mental HealthDepartment of Psychiatry, The First Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang Key Laboratory of Precision Psychiatry, Zhejiang Engineering Center for Mathematical Mental HealthDepartment of Psychiatry, The First Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang Key Laboratory of Precision Psychiatry, Zhejiang Engineering Center for Mathematical Mental HealthDepartment of Psychiatry, Affiliated Xiaoshan Hospital, Hangzhou Normal UniversitySchool of Radiology, Shandong First Medical University & Shandong Academy of Medical SciencesDepartment of Psychiatry, The First Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang Key Laboratory of Precision Psychiatry, Zhejiang Engineering Center for Mathematical Mental HealthAbstract Previous studies have found that major depressive disorder (MDD) may accelerate overall structural brain aging. Nevertheless, it still remains unknown whether anhedonia, a critical negative prognostic indicator in MDD, further leads to advanced brain aging in specific regions. A total of 31 MDD with anhedonia (MDD-WA), 41 MDD without anhedonia (MDD-WoA), and 43 healthy controls (HCs) were recruited in this study. The difference between brain structure age (BSA) applied by support vector regression (SVR) and chronological age was calculated to derive the brain structure age gap estimation (BSAGE). Analyses of covariance (ANCOVAs) and intergroup comparisons were performed to obtain brain regions with significant BSAGE differences among three groups. Moreover, a support vector machine (SVM) classification model was used to verify the diagnostic value of altered BSAGE. ANCOVAs revealed significant BSAGE differences among three groups in the bilateral putamen (PU), left cerebellar white matter (CB), left cuneus (CUN), left fusiform gyrus (FuG), left subcallosal area (SCA), left superior occipital gyrus (SOG), left triangular inferior frontal gyrus (IFG-Tri), right lateral ventricle (L-V), right superior frontal gyrus medial segment (SFG-SM), right opercular inferior frontal gyrus (IFG-Oper), right precuneus (pre-CUN), right posterior insula (INS-Post), and right superior temporal gyrus (STG). Compared to HCs, the MDD-WA group showed significant BSAGE increase in all of the aforementioned brain regions, while the MDD-WoA group showed limited BSAGE increase in the CB, FuG, and SCA of left hemisphere only. However, no significant difference was found between MDD-WA and MDD-WoA. The altered BSAGE values showed promising discriminatory performance with an area under the curve (AUC) of 0.944 in classifying MDD-WA and HCs. The current findings emphasize that MDD with anhedonia may exhibit more extensive advanced brain aging, primarily in the frontal-limbic system, temporal lobe, and parietal lobe.https://doi.org/10.1038/s41398-025-03555-5 |
| spellingShingle | Qingli Mu Kejing Zhang Yue Chen Yuwei Xu Shaohua Hu Manli Huang Peng Zhang Dong Cui Shaojia Lu Altered brain structure age gap estimation in major depressive disorder patients with and without anhedonia: a machine learning-based study Translational Psychiatry |
| title | Altered brain structure age gap estimation in major depressive disorder patients with and without anhedonia: a machine learning-based study |
| title_full | Altered brain structure age gap estimation in major depressive disorder patients with and without anhedonia: a machine learning-based study |
| title_fullStr | Altered brain structure age gap estimation in major depressive disorder patients with and without anhedonia: a machine learning-based study |
| title_full_unstemmed | Altered brain structure age gap estimation in major depressive disorder patients with and without anhedonia: a machine learning-based study |
| title_short | Altered brain structure age gap estimation in major depressive disorder patients with and without anhedonia: a machine learning-based study |
| title_sort | altered brain structure age gap estimation in major depressive disorder patients with and without anhedonia a machine learning based study |
| url | https://doi.org/10.1038/s41398-025-03555-5 |
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