Longitudinal Study of Impaired Intra- and Inter-Network Brain Connectivity in Subjects at High Risk for Alzheimer’s Disease

Article type: Research Article

Authors: Zhan, Yafeng^{a; b} | Ma, Jianhua^{a; *} | Alexander-Bloch, Aaron F.^c | Xu, Kaibin^{b; d} | Cui, Yue^{b; d} | Feng, Qianjin^a | Jiang, Tianzi^{b; d; e; f} | Liu, Yong^{b; d; *} | for the Alzheimer’s Disease Neuroimaging Initiative¹

Affiliations: [a] School of Biomedical Engineering, Southern Medical University, Guangzhou, China | [b] Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China | [c] Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA | [d] National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China | [e] CAS Center for Excellence in Brain Science, Institute of Automation, Chinese Academy of Sciences, Beijing, China | [f] Queensland Brain Institute, University of Queensland, Brisbane, Australia

Correspondence: [*] Correspondence to: Yong Liu, PhD, Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China. E-mail: yliu@nlpr.ia.ac.cn.

Correspondence: [*] Correspondence to: Jianhua Ma, PhD, School of Biomedical Engineering, Southern Medical University, Guangzhou, 510515, China. E-mail: jhma@smu.edu.cn.

Note: [1] Data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (http://adni.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: Alzheimer’s disease (AD) is associated with abnormal resting-state network (RSN) architecture of the default mode network (DMN), the dorsal attention network (DAN), the executive control network (CON), the salience network (SAL), and the sensory-motor network (SMN). However, little is known about the disrupted intra- and inter-network architecture in mild cognitive impairment (MCI). Here, we employed a priori defined regions of interest to investigate the intra- and inter-network functional connectivity profiles of these RSNs in longitudinal participants, including normal controls (n = 23), participants with early MCI (n = 26), and participants with late MCI (n = 19). We found longitudinal alterations of functional connectivity within the DMN, where they were correlated with variation in cognitive ability. The SAL as well as the interaction between the DMN and the SAL were disrupted in MCI. Furthermore, our results demonstrate that longitudinal alterations of functional connectivity are more profound in earlier stages as opposed to later stages of the disease. The increased severity of cognitive impairment is associated with increasingly altered RSN connectivity patterns, suggesting that disruptions in functional connectivity may contribute to cognitive dysfunction and may represent a potential biomarker of impaired cognitive ability in MCI. Earlier prevention and treatment may help to delay disease progression to AD.

Keywords: Default mode network, early mild cognitive impairment, late mild cognitive impairment, resting-state network, salience network

DOI: 10.3233/JAD-160008

Journal: Journal of Alzheimer's Disease, vol. 52, no. 3, pp. 913-927, 2016