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Three dysconnectivity patterns in treatment-resistant schizophrenia patients and their unaffected siblings

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机构: [1]Cent S Univ, Xiangya Hosp 2, Inst Mental Hlth, Changsha 410011, Hunan, Peoples R China [2]NIMH, Unit Stat Genom, NIH, Bethesda, MD 20892 USA [3]Kunming Med Univ, Affiliated Hosp 1, Dept Psychiat, Kunming 650032, Yunnan, Peoples R China [4]China Med Univ, Affiliated Hosp 1, Dept Psychiat, Shenyang 110001, Liaoning, Peoples R China [5]Cent S Univ, State Key Lab Med Genet, Changsha 410078, Hunan, Peoples R China [6]NIMH, Genet Epidemiol Res Branch, Intramural Res Program, Bethesda, MD 20892 USA [7]Mind Res Network, Albuquerque, NM 87131 USA [8]Univ New Mexico, Dept Elect & Comp Engn, Albuquerque, NM 87106 USA [9]Cent S Univ, Natl Technol Inst Psychiat, Changsha 410011, Hunan, Peoples R China [10]First Peoples Hosp Kunming, Dept Radiol, Kunming 650011, Yunnan, Peoples R China
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关键词: Schizophrenia TRS Brain plasticity Functional connectivity Sibling controls

摘要:
Among individuals diagnosed with schizophrenia, approximately 20%-33% are recognized as treatment-resistant schizophrenia (TRS) patients. These TRS patients suffer more severely from the disease but struggle to benefit from existing antipsychotic treatments. A few recent studies suggested that schizophreniamay be caused by impaired synaptic plasticity that manifests as functional dysconnectivity in the brain, however, few of those studies focused on the functional connectivity changes in the brains of TRS groups. In this study, we compared the whole brain connectivity variations in TRS patients, their unaffected siblings, and healthy controls. Connectivity network features between and within the 116 automated anatomical labeling (AAL) brain regions were calculated and compared using maps created with three contrasts: patient vs. control, patient vs. sibling, and sibling vs. control. To evaluate the predictive power of the selected features, we performed a multivariate classification approach. We also evaluated the influence of six important clinical measures (e.g. age, education level) on the connectivity features. This study identified abnormal significant connectivity changes of three patterns in TRS patients and their unaffected siblings: 1) 69 patient-specific connectivity (PCN); 2) 102 shared connectivity (SCN); and 3) 457 unshared connectivity (UCN). While the first two patterns were widely reported by previous non-TRS specific studies, we were among the first to report widespread significant connectivity differences between TRS patient groups and their healthy sibling groups. Observations of this study may provide new insights for the understanding of the neurophysiological mechanisms of TRS. (C) 2015 The Authors. Published by Elsevier Inc.

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出版当年[2016]版:
大类 | 3 区 医学
小类 | 3 区 神经成像
最新[2023]版:
大类 | 2 区 医学
小类 | 2 区 神经成像
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出版当年[2015]版:
Q1 NEUROIMAGING
最新[2023]版:
Q2 NEUROIMAGING

影响因子: 最新[2023版] 最新五年平均 出版当年[2015版] 出版当年五年平均 出版前一年[2014版] 出版后一年[2016版]

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第一作者机构: [1]Cent S Univ, Xiangya Hosp 2, Inst Mental Hlth, Changsha 410011, Hunan, Peoples R China [3]Kunming Med Univ, Affiliated Hosp 1, Dept Psychiat, Kunming 650032, Yunnan, Peoples R China
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通讯机构: [1]Cent S Univ, Xiangya Hosp 2, Inst Mental Hlth, Changsha 410011, Hunan, Peoples R China
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