Tongpeng Chu, Xiaopeng Si, Haizhu Xie, Heng Ma, Yinghong Shi, Wei Yao, Dong Xing, Feng Zhao, Fanghui Dong, Qun Gai, Kaili Che, Yuting Guo, Danni Chen, Dong Ming, Ning Mao
{"title":"重度抑郁障碍的区域结构-功能连接耦合与神经递质和遗传特征有关。","authors":"Tongpeng Chu, Xiaopeng Si, Haizhu Xie, Heng Ma, Yinghong Shi, Wei Yao, Dong Xing, Feng Zhao, Fanghui Dong, Qun Gai, Kaili Che, Yuting Guo, Danni Chen, Dong Ming, Ning Mao","doi":"10.1016/j.biopsych.2024.08.022","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Abnormalities in structural-functional connectivity (SC-FC) coupling have been identified globally in patients with major depressive disorder (MDD). However, investigations have neglected the variability and hierarchical distribution of these abnormalities across different brain regions. Furthermore, the biological mechanisms that underlie regional SC-FC coupling patterns are not well understood.</p><p><strong>Methods: </strong>We enrolled 182 patients with MDD and 157 healthy control participants and quantified the intergroup differences in regional SC-FC coupling. Extreme gradient boosting (XGBoost), support vector machine, and random forest models were constructed to assess the potential of SC-FC coupling as biomarkers for MDD diagnosis and symptom prediction. Then, we examined the link between changes in regional SC-FC coupling in patients with MDD, neurotransmitter distributions, and gene expression.</p><p><strong>Results: </strong>We observed increased regional SC-FC coupling in the default mode network (t<sub>337</sub> = 3.233) and decreased coupling in the frontoparietal network (t<sub>337</sub> = -3.471) in patients with MDD compared with healthy control participants. XGBoost (area under the receiver operating characteristic curve = 0.853), support vector machine (area under the receiver operating characteristic curve = 0.832), and random forest (p < .05) models exhibited good prediction performance. The alterations in regional SC-FC coupling in patients with MDD were correlated with the distributions of 4 neurotransmitters (p < .05) and expression maps of specific genes. These enriched genes were implicated in excitatory neurons, inhibitory neurons, cellular metabolism, synapse function, and immune signaling. These findings were replicated on 2 brain atlases.</p><p><strong>Conclusions: </strong>This work enhances our understanding of MDD and paves the way for the development of additional targeted therapeutic interventions.</p>","PeriodicalId":8918,"journal":{"name":"Biological Psychiatry","volume":" ","pages":""},"PeriodicalIF":9.6000,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Regional Structural-Functional Connectivity Coupling in Major Depressive Disorder Is Associated With Neurotransmitter and Genetic Profiles.\",\"authors\":\"Tongpeng Chu, Xiaopeng Si, Haizhu Xie, Heng Ma, Yinghong Shi, Wei Yao, Dong Xing, Feng Zhao, Fanghui Dong, Qun Gai, Kaili Che, Yuting Guo, Danni Chen, Dong Ming, Ning Mao\",\"doi\":\"10.1016/j.biopsych.2024.08.022\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Abnormalities in structural-functional connectivity (SC-FC) coupling have been identified globally in patients with major depressive disorder (MDD). However, investigations have neglected the variability and hierarchical distribution of these abnormalities across different brain regions. Furthermore, the biological mechanisms that underlie regional SC-FC coupling patterns are not well understood.</p><p><strong>Methods: </strong>We enrolled 182 patients with MDD and 157 healthy control participants and quantified the intergroup differences in regional SC-FC coupling. Extreme gradient boosting (XGBoost), support vector machine, and random forest models were constructed to assess the potential of SC-FC coupling as biomarkers for MDD diagnosis and symptom prediction. Then, we examined the link between changes in regional SC-FC coupling in patients with MDD, neurotransmitter distributions, and gene expression.</p><p><strong>Results: </strong>We observed increased regional SC-FC coupling in the default mode network (t<sub>337</sub> = 3.233) and decreased coupling in the frontoparietal network (t<sub>337</sub> = -3.471) in patients with MDD compared with healthy control participants. XGBoost (area under the receiver operating characteristic curve = 0.853), support vector machine (area under the receiver operating characteristic curve = 0.832), and random forest (p < .05) models exhibited good prediction performance. The alterations in regional SC-FC coupling in patients with MDD were correlated with the distributions of 4 neurotransmitters (p < .05) and expression maps of specific genes. These enriched genes were implicated in excitatory neurons, inhibitory neurons, cellular metabolism, synapse function, and immune signaling. These findings were replicated on 2 brain atlases.</p><p><strong>Conclusions: </strong>This work enhances our understanding of MDD and paves the way for the development of additional targeted therapeutic interventions.</p>\",\"PeriodicalId\":8918,\"journal\":{\"name\":\"Biological Psychiatry\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":9.6000,\"publicationDate\":\"2024-08-30\",\"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.2024.08.022\",\"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.2024.08.022","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"NEUROSCIENCES","Score":null,"Total":0}
Regional Structural-Functional Connectivity Coupling in Major Depressive Disorder Is Associated With Neurotransmitter and Genetic Profiles.
Background: Abnormalities in structural-functional connectivity (SC-FC) coupling have been identified globally in patients with major depressive disorder (MDD). However, investigations have neglected the variability and hierarchical distribution of these abnormalities across different brain regions. Furthermore, the biological mechanisms that underlie regional SC-FC coupling patterns are not well understood.
Methods: We enrolled 182 patients with MDD and 157 healthy control participants and quantified the intergroup differences in regional SC-FC coupling. Extreme gradient boosting (XGBoost), support vector machine, and random forest models were constructed to assess the potential of SC-FC coupling as biomarkers for MDD diagnosis and symptom prediction. Then, we examined the link between changes in regional SC-FC coupling in patients with MDD, neurotransmitter distributions, and gene expression.
Results: We observed increased regional SC-FC coupling in the default mode network (t337 = 3.233) and decreased coupling in the frontoparietal network (t337 = -3.471) in patients with MDD compared with healthy control participants. XGBoost (area under the receiver operating characteristic curve = 0.853), support vector machine (area under the receiver operating characteristic curve = 0.832), and random forest (p < .05) models exhibited good prediction performance. The alterations in regional SC-FC coupling in patients with MDD were correlated with the distributions of 4 neurotransmitters (p < .05) and expression maps of specific genes. These enriched genes were implicated in excitatory neurons, inhibitory neurons, cellular metabolism, synapse function, and immune signaling. These findings were replicated on 2 brain atlases.
Conclusions: This work enhances our understanding of MDD and paves the way for the development of additional targeted therapeutic 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.