Kaizhong Xue , Feng Liu , Sixiang Liang , Lining Guo , Yi Shan , Huijuan Xu , Jiao Xue , Yifan Jiang , Yong Zhang , Jie Lu
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Additionally, the role of brain connectivity in shaping these alterations, and their links to neuroreceptors and gene expression, have yet to be investigated.</div></div><div><h3>Methods</h3><div>Using the T1-weighted MRI data from 71 patients with first-episode, treatment-naïve MDD and 69 healthy controls, we constructed the MIND network for all participants. We then performed between-group comparisons to investigate abnormalities in the network and spatial relationships between the observed patterns of MIND disruption and the patterns of neuroreceptors were estimated. Network-based spreading was utilized to explore the abnormalities constrained by brain connectivity based on structural, functional, and transcriptional connectome architecture and to further identify potential epicenters of MDD. In addition, partial least squares regression was conducted to examine the associations of gene expression profiles with MIND changes in MDD.</div></div><div><h3>Results</h3><div>Patients with MDD showed significantly increased MIND in regions associated with sensation and cognition compared with healthy controls, with this altered pattern being influenced by a combination of transcriptional and structural connectivity, and potential epicenters of MDD were identified in the frontal, parietal, and paracentral cortices. Furthermore, the cortical map of case-control differences in MIND was spatially correlated with the cannabinoid CB<sub>1</sub> receptor and the brain-wide expression of a weighted combination of genes. These genes were enriched for neurobiologically relevant pathways and preferentially expressed in different cell classes and cortical layers.</div></div><div><h3>Conclusion</h3><div>These results highlight the abnormal pattern of morphometric similarity observed in MDD, shedding light on the complex interplay between disrupted macroscale coordinated morphology and microscale molecular organization in MDD.</div></div>","PeriodicalId":14963,"journal":{"name":"Journal of affective disorders","volume":"370 ","pages":"Pages 519-531"},"PeriodicalIF":4.9000,"publicationDate":"2024-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Brain connectivity and transcriptomic similarity inform abnormal morphometric similarity patterns in first-episode, treatment-naïve major depressive disorder\",\"authors\":\"Kaizhong Xue , Feng Liu , Sixiang Liang , Lining Guo , Yi Shan , Huijuan Xu , Jiao Xue , Yifan Jiang , Yong Zhang , Jie Lu\",\"doi\":\"10.1016/j.jad.2024.11.021\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><div>Major depressive disorder (MDD) is associated with disrupted brain structural integration. Morphometric similarity offers a means to capture the coordinated patterns of various structural features. However, it remains unknown whether MDD-related changes can be detected in cortical morphometric similarity through the Morphometric Inverse Divergence (MIND) network. Additionally, the role of brain connectivity in shaping these alterations, and their links to neuroreceptors and gene expression, have yet to be investigated.</div></div><div><h3>Methods</h3><div>Using the T1-weighted MRI data from 71 patients with first-episode, treatment-naïve MDD and 69 healthy controls, we constructed the MIND network for all participants. We then performed between-group comparisons to investigate abnormalities in the network and spatial relationships between the observed patterns of MIND disruption and the patterns of neuroreceptors were estimated. Network-based spreading was utilized to explore the abnormalities constrained by brain connectivity based on structural, functional, and transcriptional connectome architecture and to further identify potential epicenters of MDD. In addition, partial least squares regression was conducted to examine the associations of gene expression profiles with MIND changes in MDD.</div></div><div><h3>Results</h3><div>Patients with MDD showed significantly increased MIND in regions associated with sensation and cognition compared with healthy controls, with this altered pattern being influenced by a combination of transcriptional and structural connectivity, and potential epicenters of MDD were identified in the frontal, parietal, and paracentral cortices. Furthermore, the cortical map of case-control differences in MIND was spatially correlated with the cannabinoid CB<sub>1</sub> receptor and the brain-wide expression of a weighted combination of genes. 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引用次数: 0
摘要
背景:重度抑郁障碍(MDD)与大脑结构整合紊乱有关。形态计量相似性提供了一种捕捉各种结构特征协调模式的方法。然而,能否通过形态计量反向发散(MIND)网络检测到大脑皮层形态计量相似性中与 MDD 相关的变化,目前仍是未知数。此外,大脑连通性在形成这些改变中的作用及其与神经受体和基因表达的联系也有待研究:方法:利用 71 名初次发病、未经治疗的 MDD 患者和 69 名健康对照者的 T1 加权 MRI 数据,我们为所有参与者构建了 MIND 网络。然后,我们进行了组间比较,以调查网络中的异常情况,并估计了观察到的 MIND 干扰模式与神经受体模式之间的空间关系。基于结构、功能和转录的连接组架构,我们利用基于网络的扩展来探索受大脑连接制约的异常情况,并进一步确定 MDD 的潜在震中。此外,还进行了偏最小二乘法回归,以研究 MDD 基因表达谱与 MIND 变化之间的关联:结果:与健康对照组相比,多发性硬化症患者在感觉和认知相关区域的MIND明显增加,这种改变模式受到转录和结构连接的综合影响,并在额叶、顶叶和旁中心皮层发现了多发性硬化症的潜在震中。此外,MIND 病例对照差异的皮质图谱与大麻素 CB1 受体和全脑加权基因组合的表达存在空间相关性。这些基因富集于神经生物学相关通路,并优先表达于不同的细胞类别和皮质层:这些结果突显了在 MDD 中观察到的形态计量相似性异常模式,揭示了 MDD 中宏观协调形态破坏与微观分子组织之间复杂的相互作用。
Brain connectivity and transcriptomic similarity inform abnormal morphometric similarity patterns in first-episode, treatment-naïve major depressive disorder
Background
Major depressive disorder (MDD) is associated with disrupted brain structural integration. Morphometric similarity offers a means to capture the coordinated patterns of various structural features. However, it remains unknown whether MDD-related changes can be detected in cortical morphometric similarity through the Morphometric Inverse Divergence (MIND) network. Additionally, the role of brain connectivity in shaping these alterations, and their links to neuroreceptors and gene expression, have yet to be investigated.
Methods
Using the T1-weighted MRI data from 71 patients with first-episode, treatment-naïve MDD and 69 healthy controls, we constructed the MIND network for all participants. We then performed between-group comparisons to investigate abnormalities in the network and spatial relationships between the observed patterns of MIND disruption and the patterns of neuroreceptors were estimated. Network-based spreading was utilized to explore the abnormalities constrained by brain connectivity based on structural, functional, and transcriptional connectome architecture and to further identify potential epicenters of MDD. In addition, partial least squares regression was conducted to examine the associations of gene expression profiles with MIND changes in MDD.
Results
Patients with MDD showed significantly increased MIND in regions associated with sensation and cognition compared with healthy controls, with this altered pattern being influenced by a combination of transcriptional and structural connectivity, and potential epicenters of MDD were identified in the frontal, parietal, and paracentral cortices. Furthermore, the cortical map of case-control differences in MIND was spatially correlated with the cannabinoid CB1 receptor and the brain-wide expression of a weighted combination of genes. These genes were enriched for neurobiologically relevant pathways and preferentially expressed in different cell classes and cortical layers.
Conclusion
These results highlight the abnormal pattern of morphometric similarity observed in MDD, shedding light on the complex interplay between disrupted macroscale coordinated morphology and microscale molecular organization in MDD.
期刊介绍:
The Journal of Affective Disorders publishes papers concerned with affective disorders in the widest sense: depression, mania, mood spectrum, emotions and personality, anxiety and stress. It is interdisciplinary and aims to bring together different approaches for a diverse readership. Top quality papers will be accepted dealing with any aspect of affective disorders, including neuroimaging, cognitive neurosciences, genetics, molecular biology, experimental and clinical neurosciences, pharmacology, neuroimmunoendocrinology, intervention and treatment trials.