Grey matter networks in people at increased familial risk for schizophrenia

被引:28
作者
Tijms, Betty M. [1 ,2 ,3 ,4 ]
Sprooten, Emma [1 ,5 ]
Job, Dominic [6 ]
Johnstone, Eve C. [1 ]
Owens, David G. C. [1 ]
Willshaw, David [2 ]
Series, Peggy [2 ]
Lawrie, Stephen M. [1 ]
机构
[1] Univ Edinburgh, Royal Edinburgh Hosp, Sch Clin Sci, Div Psychiat, Edinburgh EH10 5HF, Midlothian, Scotland
[2] Univ Edinburgh, Sch Informat, Edinburgh EH8 9AB, Midlothian, Scotland
[3] Vrije Univ Amsterdam, Med Ctr, Alzheimer Ctr, NL-1081 HZ Amsterdam, Netherlands
[4] Vrije Univ Amsterdam, Med Ctr, Dept Neurol, NL-1081 HZ Amsterdam, Netherlands
[5] Icahn Sch Med Mt Sinai, Dept Psychiat, New York, NY 10029 USA
[6] Univ Edinburgh, Div Clin Neurosci, Brain Res Imaging Ctr, Edinburgh EH4 2XU, Midlothian, Scotland
基金
英国医学研究理事会; 英国工程与自然科学研究理事会;
关键词
High risk; Neuroimaging; Graph theory; Structural MRI; Psychiatry; Schizophrenia; FALSE DISCOVERY RATE; ULTRA-HIGH-RISK; GRAY-MATTER; BRAIN NETWORKS; STRUCTURAL COVARIANCE; CORTICAL NETWORKS; TWINS DISCORDANT; WHITE-MATTER; CORTEX; ORGANIZATION;
D O I
10.1016/j.schres.2015.08.025
中图分类号
R749 [精神病学];
学科分类号
100205 ;
摘要
Grey matter brain networks are disrupted in schizophrenia, but it is still unclear at which point during the development of the illness these disruptions arise and whether these can be associated with behavioural predictors of schizophrenia. We investigated if single-subject grey matter networks were disrupted in a sample of people at familial risk of schizophrenia. Single-subject grey matter networks were extracted from structural MRI scans of 144 high risk subjects, 32 recent-onset patients and 36 healthy controls. The following network properties were calculated: size, connectivity density, degree, path length, clustering coefficient, betweenness centrality and small world properties. People at risk of schizophrenia showed decreased path length and clustering in mostly prefrontal and temporal areas. Within the high risk sample, the path length of the posterior cingulate cortex and the betweenness centrality of the left inferior frontal operculum explained 81% of the variance in schizotypal cognitions, which was previously shown to be the strongest behavioural predictor of schizophrenia in the study. In contrast, local grey matter volume measurements explained 48% of variance in schizotypy. The present results suggest that single-subject grey matter networks can quantify behaviourally relevant biological alterations in people at increased risk for schizophrenia before disease onset. (C) 2015 Elsevier B.V. All rights reserved.
引用
收藏
页码:1 / 8
页数:8
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