Symptom-based depression subtypes: brain dynamic specificity and its association with gene expression profiles
Abstract At least 227 combinations of symptoms meet the criteria for Major Depressive Disorder (MDD). However, in clinical practice, patients consistently present symptoms in a regular rather than random manner, and the neural basis underlying the MDD subtypes remains unclear. To help clarify the ne...
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Nature Publishing Group
2025-01-01
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| Series: | Translational Psychiatry |
| Online Access: | https://doi.org/10.1038/s41398-025-03238-1 |
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| author | Qunjun Liang Zhifeng Zhou Shengli Chen Shiwei Lin Xiaoshan Lin Ying Li Yingli Zhang Bo Peng Gangqiang Hou Yingwei Qiu |
| author_facet | Qunjun Liang Zhifeng Zhou Shengli Chen Shiwei Lin Xiaoshan Lin Ying Li Yingli Zhang Bo Peng Gangqiang Hou Yingwei Qiu |
| author_sort | Qunjun Liang |
| collection | DOAJ |
| description | Abstract At least 227 combinations of symptoms meet the criteria for Major Depressive Disorder (MDD). However, in clinical practice, patients consistently present symptoms in a regular rather than random manner, and the neural basis underlying the MDD subtypes remains unclear. To help clarify the neural basis, patients with MDD were clustered by symptom combinations to investigate the neural underpinning of each subtype using functional resonance imaging (fMRI). Four symptom-based subtypes of MDD were identified using latent profile analysis according to the clinical scales. Subsequently, brain dynamics were evaluated using fMRI, and the dysregulations in attention and limbic network were observed among the subtypes. Correlation between brain dynamics and symptom combinations was then assessed via canonical correlation analysis (CCA). The brain-symptom correlation was higher when evaluated in subtypes (r = 0.77 to 0.92) compared to the entire group (r = 0.5). The loading weight in CCA showed that dynamics in transmodal networks contributed the most to the correlation in the subtypes characterized by typical depression symptoms, whereas unimodal networks contributed the most to subtypes characterized by anxiety and insomnia. Finally, gene expression underlying the CCA model, along with its biological encoding process, performed using a postmortem gene expression atlas revealed distinct gene enrichments for different subtypes. These findings highlight that distinct symptom clusters in MDD have specific neural correlates, providing insights into depression’s heterogeneous diagnosis and precision medicine opportunities. |
| format | Article |
| id | doaj-art-c04d99e7c8bb42cc8d68f97aaaabc9b4 |
| institution | Kabale University |
| issn | 2158-3188 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Publishing Group |
| record_format | Article |
| series | Translational Psychiatry |
| spelling | doaj-art-c04d99e7c8bb42cc8d68f97aaaabc9b42025-02-02T12:43:34ZengNature Publishing GroupTranslational Psychiatry2158-31882025-01-0115111010.1038/s41398-025-03238-1Symptom-based depression subtypes: brain dynamic specificity and its association with gene expression profilesQunjun Liang0Zhifeng Zhou1Shengli Chen2Shiwei Lin3Xiaoshan Lin4Ying Li5Yingli Zhang6Bo Peng7Gangqiang Hou8Yingwei Qiu9Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, School of Biomedical Engineering, Shenzhen University Medical SchoolDepartment of Radiology, Shenzhen Kangning Hospital, Shenzhen Mental Health CenterDepartment of Radiology, Shenzhen Nanshan People’s HospitalDepartment of Radiology, Shenzhen Nanshan People’s HospitalDepartment of Radiology, Shenzhen Nanshan People’s HospitalDepartment of Radiology, Shenzhen Nanshan People’s HospitalDepartment of Depressive Disorders, Shenzhen Mental Health Center, Shenzhen Kangning HospitalDepartment of Depressive Disorders, Shenzhen Mental Health Center, Shenzhen Kangning HospitalDepartment of Radiology, Shenzhen Kangning Hospital, Shenzhen Mental Health CenterDepartment of Radiology, Shenzhen Nanshan People’s HospitalAbstract At least 227 combinations of symptoms meet the criteria for Major Depressive Disorder (MDD). However, in clinical practice, patients consistently present symptoms in a regular rather than random manner, and the neural basis underlying the MDD subtypes remains unclear. To help clarify the neural basis, patients with MDD were clustered by symptom combinations to investigate the neural underpinning of each subtype using functional resonance imaging (fMRI). Four symptom-based subtypes of MDD were identified using latent profile analysis according to the clinical scales. Subsequently, brain dynamics were evaluated using fMRI, and the dysregulations in attention and limbic network were observed among the subtypes. Correlation between brain dynamics and symptom combinations was then assessed via canonical correlation analysis (CCA). The brain-symptom correlation was higher when evaluated in subtypes (r = 0.77 to 0.92) compared to the entire group (r = 0.5). The loading weight in CCA showed that dynamics in transmodal networks contributed the most to the correlation in the subtypes characterized by typical depression symptoms, whereas unimodal networks contributed the most to subtypes characterized by anxiety and insomnia. Finally, gene expression underlying the CCA model, along with its biological encoding process, performed using a postmortem gene expression atlas revealed distinct gene enrichments for different subtypes. These findings highlight that distinct symptom clusters in MDD have specific neural correlates, providing insights into depression’s heterogeneous diagnosis and precision medicine opportunities.https://doi.org/10.1038/s41398-025-03238-1 |
| spellingShingle | Qunjun Liang Zhifeng Zhou Shengli Chen Shiwei Lin Xiaoshan Lin Ying Li Yingli Zhang Bo Peng Gangqiang Hou Yingwei Qiu Symptom-based depression subtypes: brain dynamic specificity and its association with gene expression profiles Translational Psychiatry |
| title | Symptom-based depression subtypes: brain dynamic specificity and its association with gene expression profiles |
| title_full | Symptom-based depression subtypes: brain dynamic specificity and its association with gene expression profiles |
| title_fullStr | Symptom-based depression subtypes: brain dynamic specificity and its association with gene expression profiles |
| title_full_unstemmed | Symptom-based depression subtypes: brain dynamic specificity and its association with gene expression profiles |
| title_short | Symptom-based depression subtypes: brain dynamic specificity and its association with gene expression profiles |
| title_sort | symptom based depression subtypes brain dynamic specificity and its association with gene expression profiles |
| url | https://doi.org/10.1038/s41398-025-03238-1 |
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