The trend of disruption in the functional brain network topology of Alzheimer’s disease

Authors

Alireza Fathian, Tarbiat Modares University
Yousef Jamali, Tarbiat Modares University
Mohammad Reza Raoufy, Tarbiat Modares University
Michael W. Weiner, University of California, San Francisco
Norbert Schuf, University of California, San Francisco
Howard J. Rosen, University of California, San Francisco
Bruce L. Miller, University of California, San Francisco
Thomas Neylan, University of California, San Francisco
Jacqueline Hayes, University of California, San Francisco
Shannon Finley, University of California, San Francisco
Paul Aisen, University of California, San Diego
Zaven Khachaturian, University of California, San Diego
Ronald G. Thomas, University of California, San Diego
Michael Donohue, University of California, San Diego
Sarah Walter, University of California, San Diego
Devon Gessert, University of California, San Diego
Tamie Sather, University of California, San Diego
Gus Jiminez, University of California, San Diego
Leon Thal, University of California, San Diego
James Brewer, University of California, San Diego
Helen Vanderswag, University of California, San Diego
Adam Fleisher, University of California, San Diego
Melissa Davis, University of California, San Diego
Rosemary Morrison, University of California, San Diego
Ronald Petersen, Mayo Clinic
Cliford R. Jack, Mayo Clinic
Matthew Bernstein, Mayo Clinic
Bret Borowski, Mayo Clinic
Jef Gunter, Mayo Clinic
Matt Senjem, Mayo Clinic

Document Type

Article

Publication Date

12-1-2022

Journal

Scientific Reports

Volume

12

Issue

1

URL with Digital Object Identifier

10.1038/s41598-022-18987-y

Abstract

Alzheimer’s disease (AD) is a progressive disorder associated with cognitive dysfunction that alters the brain’s functional connectivity. Assessing these alterations has become a topic of increasing interest. However, a few studies have examined different stages of AD from a complex network perspective that cover different topological scales. This study used resting state fMRI data to analyze the trend of functional connectivity alterations from a cognitively normal (CN) state through early and late mild cognitive impairment (EMCI and LMCI) and to Alzheimer’s disease. The analyses had been done at the local (hubs and activated links and areas), meso (clustering, assortativity, and rich-club), and global (small-world, small-worldness, and efficiency) topological scales. The results showed that the trends of changes in the topological architecture of the functional brain network were not entirely proportional to the AD progression. There were network characteristics that have changed non-linearly regarding the disease progression, especially at the earliest stage of the disease, i.e., EMCI. Further, it has been indicated that the diseased groups engaged somatomotor, frontoparietal, and default mode modules compared to the CN group. The diseased groups also shifted the functional network towards more random architecture. In the end, the methods introduced in this paper enable us to gain an extensive understanding of the pathological changes of the AD process.