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Default Mode Network Functional Connectivity in Early and Late Mild Cognitive Impairment: Results From the Alzheimer’s Disease Neuroimaging Initiative

Lee, Eek-Sung MD; Yoo, Kwangsun PhD; Lee, Young-Beom MS; Chung, Jinyong BSc; Lim, Ji-Eun; Yoon, Bora MD, PhD; Jeong, Yong MD, PhDfor the Alzheimer’s Disease Neuroimaging Initiative

Alzheimer Disease & Associated Disorders: October-December 2016 - Volume 30 - Issue 4 - p 289–296
doi: 10.1097/WAD.0000000000000143
Original Articles
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Background: Default mode network (DMN) functional connectivity is one of the neuroimaging candidate biomarkers of Alzheimer disease. However, no studies have investigated DMN connectivity at different stages of mild cognitive impairment (MCI). The aim of this study was to investigate patterns of DMN connectivity and its breakdown among cognitively normal (CN), early MCI (EMCI), and late MCI (LMCI) subjects.

Methods: Magnetic resonance imaging data and neuropsychological test scores from 130 subjects (CN=43, EMCI=47, LMCI=40) were obtained from the Alzheimer’s Disease Neuroimaging Initiative. DMN functional connectivity was extracted using independent components analysis and compared between groups.

Results: Functional connectivity in the precuneus, bilateral medial frontal, parahippocampal, middle temporal, right superior temporal, and left angular gyri was decreased in EMCI subjects compared with CN subjects. When the 2 MCI groups were directly compared, LMCI subjects exhibited decreased functional connectivity in the precuneus, bilateral medial frontal gyri, and left angular gyrus. There was no significant difference in gray matter volume among the 3 groups. Amyloid-positive EMCI subjects revealed more widespread breakdown of DMN connectivity than amyloid-negative EMCI subjects. A quantitative index of DMN connectivity correlated well with measures of cognitive performance.

Conclusions: Our results suggest that the breakdown of DMN connectivity may occur in the early stage of MCI.

Supplemental Digital Content is available in the text.

*Graduate School of Medical Science and Engineering

Laboratory for Cognitive Neuroscience and NeuroImaging, Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology

Department of Neurology, Konyang University Hospital, College of Medicine, Konyang University, Daejeon, Republic of Korea

E.-S.L. and K.Y. contributed equally.

Data used in preparing this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (http://www.loni.ucla.edu/ADNI). As such, investigators within the ADNI contributed to the design and implementation of the ADNI and/or provided data but did not participate in the analysis or writing of this report. For a complete listing of ADNI investigators, please see: http://adni.loni.ucla.edu/wp-content/uploads/how_to_apply/ADNI_Manuscript_Citations.pdf.

Author contributions: E.S.L. and K.Y.: conception design, data analysis and interpretation, and manuscript writing. Y.B.L., J.C., and J.E.L.: data analysis and interpretation. Y.J. and B.Y.: final approval of manuscript, data analysis and interpretation, and manuscript writing.

The authors declare no conflicts of interest.

Reprints: Yong Jeong, MD, PhD, Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon 305-701, Republic of Korea (e-mail: yong@kaist.ac.kr) and Bora Yoon, MD, PhD, Department of Neurology, Konyang University Hospital, College of Medicine, Konyang University, Daejeon, Republic of Korea (e-mail: boradori3@hanmail.net).

Received February 16, 2015

Accepted December 28, 2015

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