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精神分裂症临床高危患者与神经典型对照者之间的神经生理差异——生物标志物开发的初步步骤

Neurophysiological differences between patients clinically at high risk for schizophrenia and neurotypical controls--first steps in development of a biomarker.

作者信息

Duffy Frank H, D'Angelo Eugene, Rotenberg Alexander, Gonzalez-Heydrich Joseph

机构信息

Department of Neurology, Boston Children's Hospital and Harvard Medical School, 300 Longwood Ave, Boston, Massachusetts, 02115, USA.

Department of Psychiatry, Boston Children's Hospital and Harvard Medical School, 300 Longwood Ave, Boston, Massachusetts, 02115, USA.

出版信息

BMC Med. 2015 Nov 2;13:276. doi: 10.1186/s12916-015-0516-z.

DOI:10.1186/s12916-015-0516-z
PMID:26525736
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4630963/
Abstract

BACKGROUND

Schizophrenia is a severe, disabling and prevalent mental disorder without cure and with a variable, incomplete pharmacotherapeutic response. Prior to onset in adolescence or young adulthood a prodromal period of abnormal symptoms lasting weeks to years has been identified and operationalized as clinically high risk (CHR) for schizophrenia. However, only a minority of subjects prospectively identified with CHR convert to schizophrenia, thereby limiting enthusiasm for early intervention(s). This study utilized objective resting electroencephalogram (EEG) quantification to determine whether CHR constitutes a cohesive entity and an evoked potential to assess CHR cortical auditory processing.

METHODS

This study constitutes an EEG-based quantitative neurophysiological comparison between two unmedicated subject groups: 35 neurotypical controls (CON) and 22 CHR patients. After artifact management, principal component analysis (PCA) identified EEG spectral and spectral coherence factors described by associated loading patterns. Discriminant function analysis (DFA) determined factors' discrimination success between subjects in the CON and CHR groups. Loading patterns on DFA-selected factors described CHR-specific spectral and coherence differences when compared to controls. The frequency modulated auditory evoked response (FMAER) explored functional CON-CHR differences within the superior temporal gyri.

RESULTS

Variable reduction by PCA identified 40 coherence-based factors explaining 77.8% of the total variance and 40 spectral factors explaining 95.9% of the variance. DFA demonstrated significant CON-CHR group difference (P <0.00001) and successful jackknifed subject classification (CON, 85.7%; CHR, 86.4% correct). The population distribution plotted along the canonical discriminant variable was clearly bimodal. Coherence factors delineated loading patterns of altered connectivity primarily involving the bilateral posterior temporal electrodes. However, FMAER analysis showed no CON-CHR group differences.

CONCLUSIONS

CHR subjects form a cohesive group, significantly separable from CON subjects by EEG-derived indices. Symptoms of CHR may relate to altered connectivity with the posterior temporal regions but not to primary auditory processing abnormalities within these regions.

摘要

背景

精神分裂症是一种严重、致残且普遍存在的精神障碍,无法治愈,药物治疗反应多变且不完全。在青春期或成年早期发病之前,已确定存在一个持续数周甚至数年的异常症状前驱期,并将其作为精神分裂症的临床高风险(CHR)进行操作化定义。然而,前瞻性确定为CHR的受试者中只有少数会发展为精神分裂症,从而限制了对早期干预的热情。本研究利用客观静息脑电图(EEG)量化来确定CHR是否构成一个连贯的实体,并利用诱发电位评估CHR的皮质听觉处理。

方法

本研究对两个未用药的受试者组进行了基于EEG的定量神经生理学比较:35名神经典型对照者(CON)和22名CHR患者。在进行伪迹处理后,主成分分析(PCA)确定了由相关负荷模式描述的EEG频谱和频谱相干因子。判别函数分析(DFA)确定了各因子在CON组和CHR组受试者之间的判别成功率。与对照组相比,DFA选择因子上的负荷模式描述了CHR特异性的频谱和相干差异。频率调制听觉诱发电位(FMAER)探索了颞上回内CON与CHR之间的功能差异。

结果

PCA进行的变量约简确定了40个基于相干性的因子,解释了总方差的77.8%,以及40个频谱因子,解释了方差的95.9%。DFA显示CON组和CHR组之间存在显著差异(P<0.00001),留一法受试者分类成功(CON组,85.7%正确;CHR组,86.4%正确)。沿典型判别变量绘制的总体分布明显呈双峰分布。相干因子描绘了主要涉及双侧后颞电极的连接改变的负荷模式。然而,FMAER分析显示CON组和CHR组之间没有差异。

结论

CHR受试者形成一个连贯的群体,通过EEG衍生指标可与CON受试者显著区分开来。CHR的症状可能与后颞叶区域的连接改变有关,但与这些区域内的初级听觉处理异常无关。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b45c/4630963/4d215011aa23/12916_2015_516_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b45c/4630963/821213de3fa5/12916_2015_516_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b45c/4630963/5168c8662481/12916_2015_516_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b45c/4630963/335d878b6df5/12916_2015_516_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b45c/4630963/4d215011aa23/12916_2015_516_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b45c/4630963/821213de3fa5/12916_2015_516_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b45c/4630963/5168c8662481/12916_2015_516_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b45c/4630963/335d878b6df5/12916_2015_516_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b45c/4630963/4d215011aa23/12916_2015_516_Fig4_HTML.jpg

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