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

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 schiz...

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Detalles Bibliográficos
Autores principales: Wang, Jicai, Cao, Hongbao, Liao, Yanhui, Liu, Weiqing, Tan, Liwen, Tang, Yanqing, Chen, Jindong, Xu, Xiufeng, Li, Haijun, Luo, Chunrong, Liu, Chunyu, Ries Merikangas, Kathleen, Calhoun, Vince, Tang, Jinsong, Shugart, Yin Yao, Chen, Xiaogang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4473730/
https://www.ncbi.nlm.nih.gov/pubmed/26106532
http://dx.doi.org/10.1016/j.nicl.2015.03.017
Descripción
Sumario: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 schizophrenia may 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.