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精神分裂症的功能网络连接损伤与核心认知缺陷。

Functional network connectivity impairments and core cognitive deficits in schizophrenia.

机构信息

Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland.

Imaging Genetics Center, Mark & Mary Stevens Institute for Neuroimaging & Informatics, Keck School of Medicine of USC, Marina del Rey, California.

出版信息

Hum Brain Mapp. 2019 Nov 1;40(16):4593-4605. doi: 10.1002/hbm.24723. Epub 2019 Jul 16.

Abstract

Cognitive deficits contribute to functional disability in patients with schizophrenia and may be related to altered functional networks that serve cognition. We evaluated the integrity of major functional networks and assessed their role in supporting two cognitive functions affected in schizophrenia: processing speed (PS) and working memory (WM). Resting-state functional magnetic resonance imaging (rsfMRI) data, N = 261 patients and 327 controls, were aggregated from three independent cohorts and evaluated using Enhancing NeuroImaging Genetics through Meta Analysis rsfMRI analysis pipeline. Meta- and mega-analyses were used to evaluate patient-control differences in functional connectivity (FC) measures. Canonical correlation analysis was used to study the association between cognitive deficits and FC measures. Patients showed consistent patterns of cognitive and resting-state FC (rsFC) deficits across three cohorts. Patient-control differences in rsFC calculated using seed-based and dual-regression approaches were consistent (Cohen's d: 0.31 ± 0.09 and 0.29 ± 0.08, p < 10 ). RsFC measures explained 12-17% of the individual variations in PS and WM in the full sample and in patients and controls separately, with the strongest correlations found in salience, auditory, somatosensory, and default-mode networks. The pattern of association between rsFC (within-network) and PS (r = .45, p = .07) and WM (r = .36, p = .16), and rsFC (between-network) and PS (r = .52, p = 8.4 × 10 ) and WM (r = .47, p = .02), derived from multiple networks was related to effect size of patient-control differences in the functional networks. No association was detected between rsFC and current medication dose or psychosis ratings. Patients demonstrated significant reduction in several FC networks that may partially underlie some of the core neurocognitive deficits in schizophrenia. The strength of connectivity-cognition relationships in different networks was strongly associated with network's vulnerability to schizophrenia.

摘要

认知缺陷导致精神分裂症患者出现功能障碍,并且可能与认知相关的功能网络改变有关。我们评估了主要功能网络的完整性,并评估了它们在支持精神分裂症中受影响的两种认知功能(处理速度(PS)和工作记忆(WM))中的作用。使用通过元分析 rsfMRI 分析管道增强神经影像学遗传学的方法,从三个独立队列中汇总了静息状态功能磁共振成像(rsfMRI)数据,N = 261 名患者和 327 名对照。使用元分析和 mega 分析评估功能连接(FC)测量值的患者 - 对照差异。使用典型相关分析研究认知缺陷与 FC 测量值之间的关联。患者在三个队列中均表现出认知和静息状态 FC(rsFC)缺陷的一致模式。使用基于种子和双回归方法计算的 rsFC 患者 - 对照差异一致(Cohen's d:0.31 ± 0.09 和 0.29 ± 0.08,p < 10 )。rsFC 测量值在整个样本以及患者和对照组中分别解释了 PS 和 WM 个体变异的 12-17%,在显着性,听觉,躯体感觉和默认模式网络中发现了最强的相关性。rsFC(网络内)与 PS(r =.45,p =.07)和 WM(r =.36,p =.16)之间的关联模式以及 rsFC(网络间)与 PS(r =.52,p = 8.4×10 )和 WM(r =.47,p =.02),来自多个网络与功能网络中患者 - 对照差异的效应大小有关。在 rsFC 与当前药物剂量或精神病评分之间未检测到关联。患者表现出多个 FC 网络的显着减少,这可能部分导致精神分裂症的一些核心神经认知缺陷。不同网络中连接 - 认知关系的强度与网络对精神分裂症的易感性密切相关。

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