{"title":"结构连接体结构影响重性抑郁症的皮质萎缩:一项中国DIRECT联合研究。","authors":"Yuhao Shen, Chunli Wang, Xiao Chen, Bin Lu, Xue-Ying Li, Zi-Han Wang, Li-Ping Cao, Guan-Mao Chen, Jian-Shan Chen, Tao Chen, Tao-Lin Chen, Yu-Qi Cheng, Zhao-Song Chu, Shi-Xian Cui, Xi-Long Cui, Zhao-Yu Deng, Qi-Yong Gong, Wen-Bin Guo, Can-Can He, Zheng-Jia-Yi Hu, Qian Huang, Xin-Lei Ji, Feng-Nan Jia, Li Kuang, Bao-Juan Li, Feng Li, Hui-Xian Li, Tao Li, Tao Lian, Yi-Fan Liao, Xiao-Yun Liu, Yan-Song Liu, Zhe-Ning Liu, Yi-Cheng Long, Jian-Ping Lu, Jiang Qiu, Xiao-Xiao Shan, Tian-Mei Si, Peng-Feng Sun, Chuan-Yue Wang, Hua-Ning Wang, Xiang Wang, Ying Wang, Yu-Wei Wang, Xiao-Ping Wu, Xin-Ran Wu, Yan-Kun Wu, Chun-Ming Xie, Guang-Rong Xie, Peng Xie, Xiu-Feng Xu, Zhen-Peng Xue, Hong Yang, Hua Yu, Min-Lan Yuan, Yong-Gui Yuan, Ai-Xia Zhang, Jing-Ping Zhao, Ke-Rang Zhang, Wei Zhang, Zi-Jing Zhang, Chao-Gan Yan, Jiajia Zhu, Yongqiang Yu","doi":"10.1016/j.biopsych.2025.06.030","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Cortical morphological alterations are evident in major depressive disorder (MDD), yet the underlying neurobiological processes that contribute to their characteristic spatial pattern remain unclear.</p><p><strong>Methods: </strong>Large-scale, multi-site structural MRI data from a homogeneous Chinese cohort of 1,442 MDD patients and 1,277 healthy controls were used to calculate cortical morphological measures, which were compared between groups to determine cortical morphological alterations in MDD. A connectome constraint model was then used to examine whether structural connectome shapes MDD-related cortical morphological alterations, followed by performance of a network diffusion model to identify the epicenters.</p><p><strong>Results: </strong>Group comparisons demonstrated a broadly distributed cortical thickness (CT) reduction in MDD, with the prefrontal cortex affected more prominently. Based on the normative structural connectome, we derived the estimated CT alteration of each brain node according to its connected neighbors, and found a strong spatial correlation between the empirical and estimated CT alterations, indicating structural connectome constraint on cortical atrophy in MDD. Concurrently, we identified the left lateral prefrontal cortex as the putative epicenters of cortical atrophy. Moreover, analyses across first-episode, early-stage, and chronic MDD subgroups revealed reduced connectome constraint with increasing illness duration. Additionally, our results were robust against several methodological variations and were largely reproducible in the cross-ethnic ENIGMA cohort of 1,902 MDD patients and 7,658 controls.</p><p><strong>Conclusions: </strong>These findings represent a substantial advance in our understanding of the network-based spread of cortical atrophy in MDD and highlight the prospect of the left prefrontal cortex as a key target for early interventions.</p>","PeriodicalId":8918,"journal":{"name":"Biological Psychiatry","volume":" ","pages":""},"PeriodicalIF":9.6000,"publicationDate":"2025-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Structural connectome architecture shapes cortical atrophy in major depression disorder: a Chinese DIRECT consortium study.\",\"authors\":\"Yuhao Shen, Chunli Wang, Xiao Chen, Bin Lu, Xue-Ying Li, Zi-Han Wang, Li-Ping Cao, Guan-Mao Chen, Jian-Shan Chen, Tao Chen, Tao-Lin Chen, Yu-Qi Cheng, Zhao-Song Chu, Shi-Xian Cui, Xi-Long Cui, Zhao-Yu Deng, Qi-Yong Gong, Wen-Bin Guo, Can-Can He, Zheng-Jia-Yi Hu, Qian Huang, Xin-Lei Ji, Feng-Nan Jia, Li Kuang, Bao-Juan Li, Feng Li, Hui-Xian Li, Tao Li, Tao Lian, Yi-Fan Liao, Xiao-Yun Liu, Yan-Song Liu, Zhe-Ning Liu, Yi-Cheng Long, Jian-Ping Lu, Jiang Qiu, Xiao-Xiao Shan, Tian-Mei Si, Peng-Feng Sun, Chuan-Yue Wang, Hua-Ning Wang, Xiang Wang, Ying Wang, Yu-Wei Wang, Xiao-Ping Wu, Xin-Ran Wu, Yan-Kun Wu, Chun-Ming Xie, Guang-Rong Xie, Peng Xie, Xiu-Feng Xu, Zhen-Peng Xue, Hong Yang, Hua Yu, Min-Lan Yuan, Yong-Gui Yuan, Ai-Xia Zhang, Jing-Ping Zhao, Ke-Rang Zhang, Wei Zhang, Zi-Jing Zhang, Chao-Gan Yan, Jiajia Zhu, Yongqiang Yu\",\"doi\":\"10.1016/j.biopsych.2025.06.030\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Cortical morphological alterations are evident in major depressive disorder (MDD), yet the underlying neurobiological processes that contribute to their characteristic spatial pattern remain unclear.</p><p><strong>Methods: </strong>Large-scale, multi-site structural MRI data from a homogeneous Chinese cohort of 1,442 MDD patients and 1,277 healthy controls were used to calculate cortical morphological measures, which were compared between groups to determine cortical morphological alterations in MDD. A connectome constraint model was then used to examine whether structural connectome shapes MDD-related cortical morphological alterations, followed by performance of a network diffusion model to identify the epicenters.</p><p><strong>Results: </strong>Group comparisons demonstrated a broadly distributed cortical thickness (CT) reduction in MDD, with the prefrontal cortex affected more prominently. Based on the normative structural connectome, we derived the estimated CT alteration of each brain node according to its connected neighbors, and found a strong spatial correlation between the empirical and estimated CT alterations, indicating structural connectome constraint on cortical atrophy in MDD. Concurrently, we identified the left lateral prefrontal cortex as the putative epicenters of cortical atrophy. Moreover, analyses across first-episode, early-stage, and chronic MDD subgroups revealed reduced connectome constraint with increasing illness duration. Additionally, our results were robust against several methodological variations and were largely reproducible in the cross-ethnic ENIGMA cohort of 1,902 MDD patients and 7,658 controls.</p><p><strong>Conclusions: </strong>These findings represent a substantial advance in our understanding of the network-based spread of cortical atrophy in MDD and highlight the prospect of the left prefrontal cortex as a key target for early interventions.</p>\",\"PeriodicalId\":8918,\"journal\":{\"name\":\"Biological Psychiatry\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":9.6000,\"publicationDate\":\"2025-07-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Biological Psychiatry\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1016/j.biopsych.2025.06.030\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"NEUROSCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biological Psychiatry","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1016/j.biopsych.2025.06.030","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"NEUROSCIENCES","Score":null,"Total":0}
Structural connectome architecture shapes cortical atrophy in major depression disorder: a Chinese DIRECT consortium study.
Background: Cortical morphological alterations are evident in major depressive disorder (MDD), yet the underlying neurobiological processes that contribute to their characteristic spatial pattern remain unclear.
Methods: Large-scale, multi-site structural MRI data from a homogeneous Chinese cohort of 1,442 MDD patients and 1,277 healthy controls were used to calculate cortical morphological measures, which were compared between groups to determine cortical morphological alterations in MDD. A connectome constraint model was then used to examine whether structural connectome shapes MDD-related cortical morphological alterations, followed by performance of a network diffusion model to identify the epicenters.
Results: Group comparisons demonstrated a broadly distributed cortical thickness (CT) reduction in MDD, with the prefrontal cortex affected more prominently. Based on the normative structural connectome, we derived the estimated CT alteration of each brain node according to its connected neighbors, and found a strong spatial correlation between the empirical and estimated CT alterations, indicating structural connectome constraint on cortical atrophy in MDD. Concurrently, we identified the left lateral prefrontal cortex as the putative epicenters of cortical atrophy. Moreover, analyses across first-episode, early-stage, and chronic MDD subgroups revealed reduced connectome constraint with increasing illness duration. Additionally, our results were robust against several methodological variations and were largely reproducible in the cross-ethnic ENIGMA cohort of 1,902 MDD patients and 7,658 controls.
Conclusions: These findings represent a substantial advance in our understanding of the network-based spread of cortical atrophy in MDD and highlight the prospect of the left prefrontal cortex as a key target for early interventions.
期刊介绍:
Biological Psychiatry is an official journal of the Society of Biological Psychiatry and was established in 1969. It is the first journal in the Biological Psychiatry family, which also includes Biological Psychiatry: Cognitive Neuroscience and Neuroimaging and Biological Psychiatry: Global Open Science. The Society's main goal is to promote excellence in scientific research and education in the fields related to the nature, causes, mechanisms, and treatments of disorders pertaining to thought, emotion, and behavior. To fulfill this mission, Biological Psychiatry publishes peer-reviewed, rapid-publication articles that present new findings from original basic, translational, and clinical mechanistic research, ultimately advancing our understanding of psychiatric disorders and their treatment. The journal also encourages the submission of reviews and commentaries on current research and topics of interest.