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Altered brain functional network in children with type 1 Gaucher disease: a longitudinal graph theory-based study

  • Miao Zhang
  • Shengpei Wang
  • Di Hu
  • Huiying Kang
  • Minhui Ouyang
  • Yonghong Zhang
  • Bo Rao
  • Hao Huang
  • Yun Peng
Functional Neuroradiology
  • 27 Downloads

Abstract

Purpose

Previous studies have investigated the brain structural abnormalities in children with type I Gaucher disease (GD). The purpose of our study is to investigate the topological efficiency of the brain functional network in children with type 1 GD.

Methods

Twenty-two children diagnosed with type 1 GD and 22 sex- and age-matched healthy controls (HCs) underwent resting-state functional MRI (rs-fMRI) examination. For longitudinal study, the GD patients underwent rs-fMRI examination again after 4.6 years. Graph theoretical analysis was used to assess the brain network topological properties at the global and regional levels.

Results

Compared with the HCs, the children with type 1 GD showed a decreased efficiency in functional segregation with a decreased γ (normalized clustering coefficient). In addition, the balance between functional segregation and integration was disrupted with decreased small-worldness (σ). At the regional level, the children with type 1 GD showed significantly decreased nodal degree and efficiency in the right precentral gyrus (PreCG.R) and left postcentral gyrus (PoCG.L). The significantly altered γ, σ, and nodal degree in the PreCG.R and PoCG.L were negatively correlated with the disease duration. No significant alterations in the global and regional topological properties were identified in these patients over time.

Conclusion

Compared with that of the HCs, the efficiency of the brain functional network in the children with type 1 GD was disrupted, and regional involvement was located in motor- and sensory-related regions. The efficiency of the brain functional network in these patients remained stable over time.

Keywords

Gaucher disease Children Resting-state functional MRI Brain functional networks Graph theory 

Notes

Acknowledgements

We thank Xuhong Liao at Beijing Normal University for consultation and support on data processing.

Compliance with ethical standards

Funding

This study was funded by the National Natural Science Foundation of China (No. 81671651).

Conflict of Interest

The authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in the studies involving human participants were in accordance with the ethical standards of the Medical Ethics Committee of the Beijing Children’s Hospital and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from the parents or legal guardians of all individual participants included in the study.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Miao Zhang
    • 1
  • Shengpei Wang
    • 2
    • 3
  • Di Hu
    • 1
  • Huiying Kang
    • 1
  • Minhui Ouyang
    • 4
  • Yonghong Zhang
    • 5
  • Bo Rao
    • 1
  • Hao Huang
    • 4
    • 6
  • Yun Peng
    • 1
  1. 1.Department of RadiologyBeijing Children’s Hospital, Capital Medical University, National Center for Children’s HealthBeijingChina
  2. 2.Research Center for Brain-Inspired Intelligence, Institute of AutomationChinese Academy of SciencesBeijingChina
  3. 3.University of Chinese Academy of SciencesBeijingChina
  4. 4.Department of RadiologyChildren’s Hospital of PhiladelphiaPhiladelphiaUSA
  5. 5.Hematology Oncology CenterBeijing Children’s Hospital, Capital Medical University, National Center for Children’s HealthBeijingChina
  6. 6.Department of Radiology, Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaUSA

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