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Author:

Yao, Zhijun (Yao, Zhijun.) | Hu, Bin (Hu, Bin.) | Hu, Tao (Hu, Tao.) | An, Jianping (An, Jianping.) | Song, Dawei (Song, Dawei.) | Zhong, Ning (Zhong, Ning.)

Indexed by:

EI Scopus

Abstract:

As the 4 allele of apolipoprotein E (APOE4) is proved a high risk factor of Alzheimer's disease (AD), numerous studies have used modalities of neuroimaging data to investigate the alterations of brain caused by APOE4. A recent study has shown that APOE4-related pathological changes of cortical networks during rest exist in APOE4 carriers. However, the interrelationship among the resting intrinsic networks (ICNs) has not been adequately explored. In the present study, seven ICNs were detected in both of APOE4 carriers and APOE4 non-carriers with spatial independent component analysis (ICA). Then the effective connectivity patterns of the two groups were acquired using multivariate Granger causality analysis (mGCA) the results of which reflect the information flow among ICNs. Compared with APOE4 non-carriers, significant difference in activity was found within default mode network in APOE4 carriers. Moreover, the significantly reduced intensity of causal interaction from auditory network to cerebellum network was found in APOE4 carriers. And we found the significantly causal relationship from cerebellum network to default mode network only existed in the connectivity pattern of APOE4 carriers but not in that of APOE4 non-carriers. In addition, the subcortical network and cognitive control network in APOE4 carriers were found less influenced by other ICNs. The findings in our study suggest that APOE4 indeed modulates the activities and interactions of ICNs, which might be the genetic cause of the dysfunctional process in APOE4 carriers. Our findings may shed new light on the ways how APOE4 affects the functions of nervous systems and provide a perspective to understand genetic basis of pathogenesis of AD. © 2017 IEEE.

Keyword:

Acoustic intensity Neurodegenerative diseases Neuroimaging Bioinformatics Genes Independent component analysis Brain

Author Community:

  • [ 1 ] [Yao, Zhijun]Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou, China
  • [ 2 ] [Hu, Bin]Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou, China
  • [ 3 ] [Hu, Tao]Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou, China
  • [ 4 ] [An, Jianping]Nuclear Medicine Department, Affiliated Lanzhou General Hospital of Lanzhou, Military Area Command, Lanzhou, China
  • [ 5 ] [Song, Dawei]Tianjin Key Laboratory of Cognitive Computing and Application, School of Computer Science and Technology, Tianjin University, Tianjin, China
  • [ 6 ] [Zhong, Ning]Beijing Advanced Innovation Center for Future Internet Technology, Beijing University of Technology, Beijing, China

Reprint Author's Address:

  • [hu, bin]gansu provincial key laboratory of wearable computing, school of information science and engineering, lanzhou university, lanzhou, china

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Source :

Year: 2017

Volume: 2017-January

Page: 754-758

Language: English

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 1

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 12

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