Variability in Resting State Network and Functional Network Connectivity Associated With Schizophrenia Genetic Risk: A Pilot Study
文献类型:期刊论文
作者 | Chen, Jiayu1; Rashid, Barnaly1,2; Yu, Qingbao1; Liu, Jingyu1,3![]() ![]() |
刊名 | FRONTIERS IN NEUROSCIENCE
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出版日期 | 2018-03-01 |
卷号 | 12 |
关键词 | Variability Resting State Network Functional Network Connectivity Schizophrenia Pgc Parallel Ica |
DOI | 10.3389/fnins.2018.00114 |
文献子类 | Article |
英文摘要 | Imaging genetics posits a valuable strategy for elucidating genetic influences on brain abnormalities in psychiatric disorders. However, association analysis between 2D genetic data (subject x genetic variable) and 3D first-level functional magnetic resonance imaging (fMRI) data (subject x voxel x time) has been challenging given the asymmetry in data dimension. A summary feature needs to be derived for the imaging modality to compute inter-modality association at subject level. In this work, we propose to use variability in resting state networks (RSNs) and functional network connectivity (FNC) as potential features for purpose of association analysis. We conducted a pilot study to investigate the proposed features in a dataset of 171 healthy controls and 134 patients with schizophrenia (SZ). We computed variability in RSN and FNC in a group independent component analysis framework and tested three types of variability metrics, namely Euclidean distance, Pearson correlation and Kullback-Leibler (KL) divergence. Euclidean distance and Pearson correlation metrics more effectively discriminated controls from patients than KL divergence. The group differences observed with variability in RSN and FNC were highly consistent, indicating patients presenting increased deviation from the cohort-common pattern of RSN and FNC than controls. The variability in RSN and FNC showed significant associations with network global efficiency, the more the deviation, the lower the efficiency. Furthermore, the RSN and FNC variability were found to associate with individual SZ risk SNPs as well as cumulative polygenic risk score for SZ. Collectively the current findings provide preliminary evidence for variability in RSN and FNC being promising imaging features that may find applications as biomarkers and in imaging genetic association analysis. |
WOS关键词 | INDEPENDENT COMPONENT ANALYSIS ; GENOME-WIDE ASSOCIATION ; BIPOLAR DISORDER ; AUDITORY HALLUCINATIONS ; SYNAPTIC PLASTICITY ; BRAIN CONNECTIVITY ; HEALTHY CONTROLS ; NEUROANATOMY ; ACTIVATION ; FMRI |
WOS研究方向 | Neurosciences & Neurology |
语种 | 英语 |
WOS记录号 | WOS:000426390800001 |
资助机构 | National Institutes of Health(P20GM103472 ; National Science Foundation(1539067) ; National Natural Science Foundation of China(61703253 ; Natural Science Foundation of Shanxi(2016021077) ; Strategic Priority Research Program of the Chinese Academy of Sciences(XDB02060005) ; 1R01 EB006841 ; 81471367 ; R01MH106655) ; 61773380) |
源URL | [http://ir.ia.ac.cn/handle/173211/21967] ![]() |
专题 | 自动化研究所_脑网络组研究中心 |
作者单位 | 1.Mind Res Network, Albuquerque, NM 87106 USA 2.Harvard Univ, Harvard Med Sch, Boston, MA 02115 USA 3.Univ New Mexico, Dept Elect Engn, Albuquerque, NM 87131 USA 4.Shanxi Univ, Sch Comp & Informat Technol, Taiyuan, Shanxi, Peoples R China 5.Chinese Acad Sci, Inst Automat, Brainnetome Ctr, Beijing, Peoples R China 6.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing, Peoples R China 7.Univ New Mexico, Sch Med, Dept Neurosci, Albuquerque, NM 87131 USA 8.Univ New Mexico, Sch Med, Dept Psychiat, Albuquerque, NM 87131 USA |
推荐引用方式 GB/T 7714 | Chen, Jiayu,Rashid, Barnaly,Yu, Qingbao,et al. Variability in Resting State Network and Functional Network Connectivity Associated With Schizophrenia Genetic Risk: A Pilot Study[J]. FRONTIERS IN NEUROSCIENCE,2018,12. |
APA | Chen, Jiayu.,Rashid, Barnaly.,Yu, Qingbao.,Liu, Jingyu.,Lin, Dongdong.,...&Calhoun, Vince D..(2018).Variability in Resting State Network and Functional Network Connectivity Associated With Schizophrenia Genetic Risk: A Pilot Study.FRONTIERS IN NEUROSCIENCE,12. |
MLA | Chen, Jiayu,et al."Variability in Resting State Network and Functional Network Connectivity Associated With Schizophrenia Genetic Risk: A Pilot Study".FRONTIERS IN NEUROSCIENCE 12(2018). |
入库方式: OAI收割
来源:自动化研究所
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