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Variability in Resting State Network and Functional Network Connectivity Associated With Schizophrenia Genetic Risk: A Pilot Study
Chen, Jiayu1; Rashid, Barnaly1,2; Yu, Qingbao1; Liu, Jingyu1,3; Lin, Dongdong1; Du, Yuhui1,4; Sui, Jing1,5,6; Calhoun, Vince D.1,3,7,8
Source PublicationFRONTIERS IN NEUROSCIENCE
2018-03-01
Volume12
SubtypeArticle
AbstractImaging 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.
KeywordVariability Resting State Network Functional Network Connectivity Schizophrenia Pgc Parallel Ica
WOS HeadingsScience & Technology ; Life Sciences & Biomedicine
DOI10.3389/fnins.2018.00114
WOS KeywordINDEPENDENT COMPONENT ANALYSIS ; GENOME-WIDE ASSOCIATION ; BIPOLAR DISORDER ; AUDITORY HALLUCINATIONS ; SYNAPTIC PLASTICITY ; BRAIN CONNECTIVITY ; HEALTHY CONTROLS ; NEUROANATOMY ; ACTIVATION ; FMRI
Indexed BySCI ; SSCI
Language英语
Funding OrganizationNational 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)
WOS Research AreaNeurosciences & Neurology
WOS SubjectNeurosciences
WOS IDWOS:000426390800001
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/21967
Collection脑网络组研究中心
Affiliation1.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
Recommended Citation
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).
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