@article{347383b7a0744310ab71a3e3971f0d91,
title = "Rich club analysis in the Alzheimer's disease connectome reveals a relatively undisturbed structural core network",
abstract = "Diffusion imaging can assess the white matter connections within the brain, revealing how neural pathways break down in Alzheimer's disease (AD). We analyzed 3-Tesla whole-brain diffusion-weighted images from 202 participants scanned by the Alzheimer's Disease Neuroimaging Initiative–50 healthy controls, 110 with mild cognitive impairment (MCI) and 42 AD patients. From whole-brain tractography, we reconstructed structural brain connectivity networks to map connections between cortical regions. We tested whether AD disrupts the “rich club” – a network property where high-degree network nodes are more interconnected than expected by chance. We calculated the rich club properties at a range of degree thresholds, as well as other network topology measures including global degree, clustering coefficient, path length, and efficiency. Network disruptions predominated in the low-degree regions of the connectome in patients, relative to controls. The other metrics also showed alterations, suggesting a distinctive pattern of disruption in AD, less pronounced in MCI, targeting global brain connectivity, and focusing on more remotely connected nodes rather than the central core of the network. AD involves severely reduced structural connectivity; our step-wise rich club coefficients analyze points to disruptions predominantly in the peripheral network components; other modalities of data are needed to know if this indicates impaired communication among non rich club regions. The highly connected core was relatively preserved, offering new evidence on the neural basis of progressive risk for cognitive decline. Hum Brain Mapp 36:3087–3103, 2015.",
keywords = "Alzheimer's disease, DWI, MRI, graph theory, mild cognitive impairment, rich club",
author = "{The Alzheimer's Disease Neuroimaging Initiative} and Madelaine Daianu and Neda Jahanshad and Nir, {Talia M.} and Jack, {Clifford R.} and Weiner, {Michael W.} and Bernstein, {Matt A.} and Thompson, {Paul M.}",
note = "Funding Information: (ADNI clinical sites in Canada); Contract grant sponsor: National Institute of General Medical Sciences; Contract grant number: NIH grants P30AG010129 and K01AG030514; Contract grant sponsor: Consortium grant (U54 EB020403) (NIH Institutes contributing to the Big Data to Knowledge (BD2K) Initiative, including the NIBIB and NCI); Contract grant number: R01 EB008432 *Correspondence to: Paul Thompson, Professor of Neurology, Psychiatry, Engineering, Radiology, Pediatrics, and Ophthalmology, Imaging Genetics Center, and Institute for Neuroimaging and Informatics, Keck School of Medicine of USC, University of Southern California, 2001 N. Soto Street, SSB1-102, Los Angeles, CA 90032. E-mail: pthomp@usc.edu †Many investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data, but most of them did not participate in analysis or writing of this report. A complete list of ADNI investigators may be found at: http:// adni.loni.usc.edu/wp-content/uploads/how_to_apply/ADNI_ Acknowledgement_List.pdf Received for publication 17 October 2014; Revised 4 February 2015; Accepted 21 April 2015. DOI: 10.1002/hbm.22830 Published online 3 June 2015 in Wiley Online Library (wileyonlinelibrary.com). Funding Information: Additional Supporting Information may be found in the online version of this article. Contract grant sponsor: NIBIB (Algorithm development and image analysis) (to P.T.); Contract grant numbers: R01EB008281, R01EB008432; Contract grant sponsors: NIA, NIBIB, NIMH, the National Library of Medicine, and the National Center for Research Resources; Contract grant numbers: AG016570, AG040060, EB01651, MH097268, LM05639, RR019771 (to P.T.); Contract grant sponsor: ADNI (Data collection and sharing for this project); Contract grant number: NIH Grant U01AG024904; Contract grant sponsor: National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering (ADNI); Abbott; Alzheimer{\textquoteright}s Association; Alzheimer{\textquoteright}s Drug Discovery Foundation; Amorfix Life Sciences Ltd.; Astra Zeneca; Bayer Health Care; Bio Clinica, Inc.; Biogen Idec Inc.; Bristol-Myers Squibb Company; Eisai Inc.; Elan Pharmaceuticals Inc.; Eli Lilly and Company; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.; GE Healthcare; Innogenetics, N.V.; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Medpace, Inc.; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Servier; Synarc Inc.; and taked a Pharmaceutical Company; Contract grant sponsor: Canadian Institutes of Health Research Funding Information: Private sector contributions are facilitated by the Foundation for the National Institutes of Health. The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer's Disease Cooperative Study at the University of California, San Diego. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California. Disclosure statement ADNI is partially funded by public and private agencies. One of the authors, Michael Weiner, has received private funding unrelated to the content of this paper. Funding Information: ADNI is partially funded by public and private agencies. One of the authors, Michael Weiner, has received private funding unrelated to the content of this paper. Publisher Copyright: {\textcopyright} 2015 Wiley Periodicals, Inc.",
year = "2015",
month = aug,
doi = "10.1002/hbm.22830",
language = "English (US)",
volume = "36",
pages = "3087--3103",
journal = "Human Brain Mapping",
issn = "1065-9471",
publisher = "Wiley-Liss Inc.",
number = "8",
}