Thalamic Volumes and Functional Networks Linked With Self-Regulation Dysfunction in Major Depressive Disorder

IF 4.8 1区医学 Q1 NEUROSCIENCES

CNS Neuroscience & Therapeutics Pub Date : 2024-11-10 DOI:10.1111/cns.70116

Zhang Ling, He Cancan, Liu Xinyi, Fan Dandan, Zhang Haisan, Zhang Hongxing, Xie Chunming

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Abstract

Aims

Self-regulation (SR) dysfunction is a crucial risk factor for major depressive disorder (MDD). However, neural substrates of SR linking MDD remain unclear.

Methods

Sixty-eight healthy controls and 75 MDD patients were recruited to complete regulatory orientation assessments with the Regulatory Focus Questionnaire (RFQ) and Regulatory Mode Questionnaire (RMQ). Nodal intra and inter-network functional connectivity (FC) was defined as FC sum within networks of 46 thalamic subnuclei (TS) or 88 AAL brain regions, and between the two networks separately. Group-level volumetric and functional difference were compared by two sample t-tests. Pearson's correlation analysis and mediation analysis were utilized to investigate the relationship among imaging parameters and the two behaviors. Canonical correlation analysis (CCA) was conducted to explore the inter-network FC mode of TS related to behavioral subscales. Network-based Statistics with machine learning combining powerful brain imaging features was applied to predict individual behavioral subscales.

Results

MDD patients showed no group-level volumetric difference in 46 TS but represented significant correlation of TS volume and nodal FC with behavioral subscales. Specially, inter-network FC of the orbital part of the right superior frontal gyrus and the left supplementary motor area mediated the correlation between RFQ/RMQ subscales and depressive severity. Furthermore, CCA identified how the two behaviors are linked via the inter-network FC mode of TS. More crucially, thalamic functional subnetworks could predict RFQ/RMQ subscales and psychomotor retardation for MDD individuals.

Conclusion

These findings provided neurological evidence for SR affecting depressive severity in the MDD patients and proposed potential biomarkers to identify the SR-based risk phenotype of MDD individuals.

Abstract Image

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丘脑体积和功能网络与重度抑郁障碍的自我调节功能障碍有关

目的：自我调节（SR）功能障碍是重度抑郁障碍（MDD）的一个重要风险因素。然而，SR与MDD相关的神经基质仍不清楚：方法：招募 68 名健康对照者和 75 名重度抑郁症患者，通过 "调节焦点问卷"（RFQ）和 "调节模式问卷"（RMQ）完成调节定向评估。网络内和网络间的节点功能连通性（FC）被定义为46丘脑下核（TS）或88 AAL脑区网络内的FC总和，以及这两个网络之间的FC总和。组间体积和功能差异通过双样本 t 检验进行比较。利用皮尔逊相关分析和中介分析来研究成像参数与两种行为之间的关系。还进行了典型相关分析（CCA），以探讨与行为分量表相关的 TS 网络间 FC 模式。基于网络的统计与机器学习相结合，结合强大的脑成像特征，用于预测个体行为分量表：结果：MDD 患者的 46 个 TS 没有表现出群体水平的体积差异，但 TS 体积和节点 FC 与行为分量表有显著相关性。特别是，右侧额上回眶部和左侧辅助运动区的网络间FC介导了RFQ/RMQ分量表与抑郁严重程度之间的相关性。此外，CCA 还确定了这两种行为是如何通过 TS 的网络间 FC 模式联系在一起的。更重要的是，丘脑功能亚网络可以预测MDD患者的RFQ/RMQ子量表和精神运动迟滞：这些发现为SR影响MDD患者的抑郁严重程度提供了神经学证据，并提出了识别基于SR的MDD患者风险表型的潜在生物标记物。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

CNS Neuroscience & Therapeutics 医学-神经科学

CiteScore

7.30

自引率

12.70%

发文量

240

审稿时长

2 months

期刊介绍： CNS Neuroscience & Therapeutics provides a medium for rapid publication of original clinical, experimental, and translational research papers, timely reviews and reports of novel findings of therapeutic relevance to the central nervous system, as well as papers related to clinical pharmacology, drug development and novel methodologies for drug evaluation. The journal focuses on neurological and psychiatric diseases such as stroke, Parkinson’s disease, Alzheimer’s disease, depression, schizophrenia, epilepsy, and drug abuse.