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Exploring different impaired speed of genetic-related brain function and structures in schizophrenic progress using multimodal analysis
Luo N(罗娜)1,2; Tian Lin3; Vince Calhoun4; Jiayu Chen4; Dongdong Lin4; Shuquan Rao5; Jian Yang6; Chuanjun Zhuo7; Yong Xu8; Jessica A. Turner9; Jing Sui1,2,10
Conference Name40th International conference of the IEEE Engineering in Medicine and Biology Society
Conference DateHonolulu, Hawaii
Conference PlaceJuly 17-21, 2018

Schizophrenia (SZ) is a highly heritable disease exhibiting substantial structural and functional brain impairments. The duration of illness and medication use may cause different presentations of impairments in patients. To understand the progressive variations of the disease, most
recent studies have reported brain functional or structural abnormalities associated with illness duration, but a comprehensive study of pathology underlying brain structure, function and illness duration is still limited. In this work, we employed a three-way parallel independent component analysis (pICA) algorithm to jointly analyze grey matter volume(GM),
functional connectivity (FC) and single nucleotide polymorphisms (SNPs) from drug-naïve first-episode [FESZ], chronic schizophrenia [CSZ]) and healthy controls[HC], aiming to identify the linked alterations in SNP-GM-FC components, and evaluate the impairment speed of imaging measures
associated with SZ-susceptible genetic variants in different disease stages (FESZ and CSZ). Results demonstrated significant group differences on GM and FC in hippocampus, temporal gyrus and cerebellum between SZ and HC, which are also significantly correlated with SNPs residing in genes like GABBR2, SATB2, CACNA1C, PDE4B, involved in pathways of
cell junction, synapse and neuron projection. Moreover, two-sample t-tests showed that GM volume and FC strength presented similar trends of progressive decrease with the increase of the illness duration (HC>FESZ>CSZ). Besides that genetic-related GM and FC components both showed significant associations with illness duration, FC indicates the higher impairment speed than GM, suggesting that functional connectivity may serve as a more sensitive measure to detect the
disruptions in SZ at the very early stage.

Indexed ByEI
Document Type会议论文
Affiliation1.Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences.
2.University of Chinese Academy of Sciences, Beijing 100190, China
3.Wuxi Mental Health Center, Wuxi 214000, China
4.Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS): {Georgia State University, Georgia Institute of Technology, and Emory University}, Atlanta, GA 30303, USA
5.School of Life Science and Engineering, Southwest Jiaotong University
6.Beijing Engineering Research Center of Mixed Reality and Advanced Display, School of Optics and Electronics, Beijing Institute of Technology, Beijing, China
7.Department of Psychiatric-Neuroimaging-Genetics and Morbidity Laboratory (PNGC-Lab), Tianjin Mental Health Center
8.Department of Psychiatry, First Clinical Medical College, First Hospital of Shanxi Medical University, Taiyuan 030000, China
9.Department of Psychology, Neuroscience Institute, Georgia State University, Atlanta, GA, USA
10.CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences
First Author AffilicationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Luo N,Tian Lin,Vince Calhoun,et al. Exploring different impaired speed of genetic-related brain function and structures in schizophrenic progress using multimodal analysis[C],2018.
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