区域大脑结构网络拓扑介导重度抑郁障碍初发、未接受治疗的青春期儿童白质损伤与疾病严重程度之间的关联。

IF 2.1 4区 医学 Q3 CLINICAL NEUROLOGY
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引用次数: 0

摘要

由于神经发育的巨大变化,青春期是重度抑郁症(MDD)的易发期。之前对抑郁症青少年进行的弥散张量成像(DTI)研究的参与者不尽相同,由于疾病的长期性和药物的干扰,对早期病理的评估具有挑战性。本研究利用全脑 DTI 和图论方法来探究白质(WM)异常以及与首次发病、未经治疗的儿科 MDD 相关的结构网络拓扑紊乱。参与者包括 36 名首次发病、未接受治疗的 MDD 青少年(平均年龄 15.8 岁)和 29 名年龄和性别匹配的健康对照组(平均年龄 15.2 岁)。与对照组相比,多发性抑郁症组的内囊和外囊各向异性分数降低,揭示了早发性抑郁症中WM紊乱的新区域。研究发现,右侧丘脑和颞上回是网络中心,其间度中心性变化介导了WM异常与抑郁严重程度之间的联系。利用神经网络算法,一个包含人口统计学、DTI和网络指标的诊断模型达到了0.88的AUROC和0.80的F1得分。通过研究首次发病、未经治疗的患者,这项研究发现了新的WM异常,以及通过大脑中枢的区域结构网络改变将WM损伤与症状严重程度联系起来的潜在因果途径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Regional brain structural network topology mediates the associations between white matter damage and disease severity in first-episode, Treatment-naïve pubertal children with major depressive disorder

Regional brain structural network topology mediates the associations between white matter damage and disease severity in first-episode, Treatment-naïve pubertal children with major depressive disorder

Puberty is a vulnerable period for the onset of major depressive disorder (MDD) due to considerable neurodevelopmental changes. Prior diffusion tensor imaging (DTI) studies in depressed youth have had heterogeneous participants, making assessment of early pathology challenging due to illness chronicity and medication confounds. This study leveraged whole-brain DTI and graph theory approaches to probe white matter (WM) abnormalities and disturbances in structural network topology related to first-episode, treatment-naïve pediatric MDD. Participants included 36 first-episode, unmedicated adolescents with MDD (mean age 15.8 years) and 29 age- and sex-matched healthy controls (mean age 15.2 years). Compared to controls, the MDD group showed reduced fractional anisotropy in the internal and external capsules, unveiling novel regions of WM disruption in early-onset depression. The right thalamus and superior temporal gyrus were identified as network hubs where betweenness centrality changes mediated links between WM anomalies and depression severity. A diagnostic model incorporating demographics, DTI, and network metrics achieved an AUROC of 0.88 and a F1 score of 0.80 using a neural network algorithm. By examining first-episode, treatment-naïve patients, this work identified novel WM abnormalities and a potential causal pathway linking WM damage to symptom severity via regional structural network alterations in brain hubs.

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来源期刊
Psychiatry Research: Neuroimaging
Psychiatry Research: Neuroimaging 医学-精神病学
CiteScore
3.80
自引率
0.00%
发文量
86
审稿时长
22.5 weeks
期刊介绍: The Neuroimaging section of Psychiatry Research publishes manuscripts on positron emission tomography, magnetic resonance imaging, computerized electroencephalographic topography, regional cerebral blood flow, computed tomography, magnetoencephalography, autoradiography, post-mortem regional analyses, and other imaging techniques. Reports concerning results in psychiatric disorders, dementias, and the effects of behaviorial tasks and pharmacological treatments are featured. We also invite manuscripts on the methods of obtaining images and computer processing of the images themselves. Selected case reports are also published.
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