Disrupted Brain Network in Progressive Mild Cognitive Impairment Measured by Eigenvector Centrality Mapping is Linked to Cognition and Cerebrospinal Fluid Biomarkers
Affiliations: [a] Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| [b] Department of Neurology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
Correspondence:
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Correspondence to: Minming Zhang, Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, No.88 Jiefang Road, Shangcheng District, Hangzhou 310009, China. Tel./Fax: +86 057187315255; E-mail: [email protected].
Note: [1] These authors contributed equally to this work.
Note: [2] Data used in preparation of this article were obtained from the Alzheimer’s disease Neuroimaging Initiative (ADNI) database (http://www.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found at: http://adni.loni.usc.edu/wp-content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf
Abstract: Mild cognitive impairment (MCI) is a heterogeneous condition associated with a high risk of progressing to Alzheimer’s disease (AD). Although functional brain network alterations have been observed in progressive MCI (pMCI), the underlying pathological mechanisms of network alterations remain unclear. In the present study, we evaluated neuropsychological, imaging, and cerebrospinal fluid (CSF) data at baseline across a cohort of: 21 pMCI patients, 33 stable MCI (sMCI) patients, and 29 normal controls. Fast eigenvector centrality mapping (fECM) based on resting-state functional MRI (rsfMRI) was used to investigate brain network organization differences among these groups, and we further assessed its relation to cognition and AD-related pathology. Our results demonstrated that pMCI had decreased eigenvector centrality (EC) in left temporal pole and parahippocampal gyrus, and increased EC in left middle frontal gyrus compared to sMCI. In addition, compared to normal controls, patients with pMCI showed decreased EC in right hippocampus and bilateral parahippocampal gyrus, and sMCI had decreased EC in right middle frontal gyrus and superior parietal lobule. Correlation analysis showed that EC in the left temporal pole was related to Wechsler Memory Scale-Revised Logical Memory (WMS-LM) delay score (r = 0.467, p = 0.044) and total tau (t-tau) level in CSF (r = –0.509, p = 0.026) in pMCI. Our findings implicate EC changes of different brain network nodes in the prognosis of pMCI and sMCI. Importantly, the association between decreased EC of brain network node and pathological changes may provide a deeper understanding of the underlying pathophysiology of pMCI.
