Suppr超能文献

通过个体化结构协方差网络分析识别精神障碍中大脑网络异常的共同和独特模式。

Identification of shared and distinct patterns of brain network abnormality across mental disorders through individualized structural covariance network analysis.

作者信息

Han Shaoqiang, Xue Kangkang, Chen Yuan, Xu Yinhuan, Li Shuying, Song Xueqin, Guo Hui-Rong, Fang Keke, Zheng Ruiping, Zhou Bingqian, Chen Jingli, Wei Yarui, Zhang Yong, Cheng Jingliang

机构信息

Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.

Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China.

出版信息

Psychol Med. 2023 Oct;53(14):6780-6791. doi: 10.1017/S0033291723000302. Epub 2023 Mar 6.

Abstract

BACKGROUND

Mental disorders, including depression, obsessive compulsive disorder (OCD), and schizophrenia, share a common neuropathy of disturbed large-scale coordinated brain maturation. However, high-interindividual heterogeneity hinders the identification of shared and distinct patterns of brain network abnormalities across mental disorders. This study aimed to identify shared and distinct patterns of altered structural covariance across mental disorders.

METHODS

Subject-level structural covariance aberrance in patients with mental disorders was investigated using individualized differential structural covariance network. This method inferred structural covariance aberrance at the individual level by measuring the degree of structural covariance in patients deviating from matched healthy controls (HCs). T1-weighted anatomical images of 513 participants (105, 98, 190 participants with depression, OCD and schizophrenia, respectively, and 130 age- and sex-matched HCs) were acquired and analyzed.

RESULTS

Patients with mental disorders exhibited notable heterogeneity in terms of altered edges, which were otherwise obscured by group-level analysis. The three disorders shared high difference variability in edges attached to the frontal network and the subcortical-cerebellum network, and they also exhibited disease-specific variability distributions. Despite notable variability, patients with the same disorder shared disease-specific groups of altered edges. Specifically, depression was characterized by altered edges attached to the subcortical-cerebellum network; OCD, by altered edges linking the subcortical-cerebellum and motor networks; and schizophrenia, by altered edges related to the frontal network.

CONCLUSIONS

These results have potential implications for understanding heterogeneity and facilitating personalized diagnosis and interventions for mental disorders.

摘要

背景

精神障碍,包括抑郁症、强迫症(OCD)和精神分裂症,都存在一种共同的神经病变,即大规模协调的大脑成熟过程受到干扰。然而,个体间的高度异质性阻碍了跨精神障碍识别大脑网络异常的共同和独特模式。本研究旨在识别跨精神障碍改变的结构协方差的共同和独特模式。

方法

使用个体化差异结构协方差网络研究精神障碍患者个体水平的结构协方差异常。该方法通过测量患者结构协方差偏离匹配健康对照(HCs)的程度来推断个体水平的结构协方差异常。获取并分析了513名参与者(分别有105名、98名、190名抑郁症、强迫症和精神分裂症患者,以及130名年龄和性别匹配的健康对照)的T1加权解剖图像。

结果

精神障碍患者在改变的边方面表现出显著的异质性,而这些在组水平分析中被掩盖。这三种障碍在与额叶网络和皮质下 - 小脑网络相连的边上具有高度差异变异性,并且它们还表现出疾病特异性的变异性分布。尽管存在显著变异性,但患有相同障碍的患者共享疾病特异性的改变边的组。具体而言,抑郁症的特征是与皮质下 - 小脑网络相连的边发生改变;强迫症是与皮质下 - 小脑和运动网络相连的边发生改变;精神分裂症是与额叶网络相关的边发生改变。

结论

这些结果对于理解异质性以及促进精神障碍的个性化诊断和干预具有潜在意义。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验