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不同的结构大脑回路表明双相情感障碍的情绪和淡漠特征。

Distinct structural brain circuits indicate mood and apathy profiles in bipolar disorder.

机构信息

Department of Psychology, Georgia State University, USA.

NORMENT, Institute of Clinical Medicine, University of Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Norway.

出版信息

Neuroimage Clin. 2020;26:101989. doi: 10.1016/j.nicl.2019.101989. Epub 2019 Aug 19.

Abstract

Bipolar disorder (BD) is a severe manic-depressive illness. Patients with BD have been shown to have gray matter (GM) deficits in prefrontal, frontal, parietal, and temporal regions; however, the relationship between structural effects and clinical profiles has proved elusive when considered on a region by region or voxel by voxel basis. In this study, we applied parallel independent component analysis (pICA) to structural neuroimaging measures and the positive and negative syndrome scale (PANSS) in 110 patients (mean age 34.9 ± 11.65) with bipolar disorder, to examine networks of brain regions that relate to symptom profiles. The pICA revealed two distinct symptom profiles and associated GM concentration alteration circuits. The first PANSS pICA profile mainly involved anxiety, depression and guilty feelings, reflecting mood symptoms. Reduced GM concentration in right temporal regions predicted worse mood symptoms in this profile. The second PANSS pICA profile generally covered blunted affect, emotional withdrawal, passive/apathetic social withdrawal, depression and active social avoidance, exhibiting a withdrawal or apathy dominating component. Lower GM concentration in bilateral parietal and frontal regions showed worse symptom severity in this profile. In summary, a pICA decomposition suggested BD patients showed distinct mood and apathy profiles differing from the original PANSS subscales, relating to distinct brain structural networks.

摘要

双相障碍(BD)是一种严重的躁郁症。研究表明,BD 患者的前额叶、额叶、顶叶和颞叶等区域存在灰质(GM)缺陷;然而,当按区域或体素进行考虑时,结构效应与临床特征之间的关系仍难以捉摸。在这项研究中,我们应用平行独立成分分析(pICA)对 110 名(平均年龄 34.9±11.65)双相障碍患者的结构神经影像学测量和阳性和阴性症状量表(PANSS)进行了分析,以检查与症状特征相关的脑区网络。pICA 揭示了两个不同的症状特征和相关的 GM 浓度改变回路。第一个 PANSS pICA 特征主要涉及焦虑、抑郁和内疚感,反映了情绪症状。右侧颞叶 GM 浓度降低预示着该特征下的情绪症状更差。第二个 PANSS pICA 特征通常涵盖了迟钝的情感、情感退缩、被动/冷漠的社交退缩、抑郁和主动社交回避,表现出退缩或冷漠为主的成分。双侧顶叶和额叶区域 GM 浓度降低预示着该特征下的症状严重程度更差。总之,pICA 分解表明,BD 患者表现出不同的情绪和冷漠特征,与原始 PANSS 分量表不同,与不同的大脑结构网络有关。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/54a7/7229320/0069aa72e328/gr1.jpg

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