Distance disintegration delineates the brain connectivity failure of Alzheimer's disease

Víctor Costumero; Federico d'Oleire Uquillas; Ibai Diez; Magi Andorrà; Silvia Basaia; Elisenda Bueichekú; Laura Ortiz-Terán; Vicente Belloch; Joaquin Escudero; César Ávila; Jorge Sepulcre

doi:10.1016/j.neurobiolaging.2019.12.005

Distance disintegration delineates the brain connectivity failure of Alzheimer's disease

Neurobiol Aging. 2020 Apr:88:51-60. doi: 10.1016/j.neurobiolaging.2019.12.005. Epub 2019 Dec 14.

Authors

Affiliations

¹ Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Center for Brain and Cognition, University Pompeu Fabra, Barcelona, Catalonia, Spain; Neuropsychology and Functional Neuroimaging Group, Department of basic Psychology, University Jaume I, Castellón, Valencian Community, Spain.
² Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
³ Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Neurotechnology Laboratory, Tecnalia Health Department, Basque Country, Spain.
⁴ Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Center of Neuroimmunology, Department of Neurology, Hospital Clinic of Barcelona, Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), University of Barcelona, Barcelona, Catalonia, Spain.
⁵ Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Neuroimaging Research Unit Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy.
⁶ Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Neuropsychology and Functional Neuroimaging Group, Department of basic Psychology, University Jaume I, Castellón, Valencian Community, Spain.
⁷ Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
⁸ ERESA Medical Group, Valencia, Valencian community, Spain.
⁹ Department of Neurology, General Hospital of Valencia, Valencia, Valencian Community, Spain.
¹⁰ Neuropsychology and Functional Neuroimaging Group, Department of basic Psychology, University Jaume I, Castellón, Valencian Community, Spain.
¹¹ Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA. Electronic address: sepulcre@nmr.mgh.harvard.edu.

PMID: 31941578
PMCID: PMC7085436
DOI: 10.1016/j.neurobiolaging.2019.12.005

Abstract

Alzheimer's disease (AD) is associated with brain network dysfunction. Network-based investigations of brain connectivity have mainly focused on alterations in the strength of connectivity; however, the network breakdown in AD spectrum is a complex scenario in which multiple pathways of connectivity are affected. To integrate connectivity changes that occur under AD-related conditions, here we developed a novel metric that computes the connectivity distance between cortical regions at the voxel level (or nodes). We studied 114 individuals with mild cognitive impairment, 24 with AD, and 27 healthy controls. Results showed that areas of the default mode network, salience network, and frontoparietal network display a remarkable network separation, or greater connectivity distances, from the rest of the brain. Furthermore, this greater connectivity distance was associated with lower global cognition. Overall, the investigation of AD-related changes in paths and distances of connectivity provides a novel framework for characterizing subjects with cognitive impairment; a framework that integrates the overall network topology changes of the brain and avoids biases toward unreferenced connectivity effects.

Keywords: Alzheimer's disease; Functional connectivity; Graph-theory; Mild Cognitive impairment; Optimal distance; Stepwise connectivity.

Publication types

Research Support, N.I.H., Extramural

MeSH terms

Aged
Alzheimer Disease / physiopathology*
Alzheimer Disease / psychology*
Brain / physiopathology*
Cognition*
Cognitive Dysfunction / psychology
Executive Function*
Female
Humans
Male
Neural Pathways / physiopathology*

Abstract

Publication types

MeSH terms

Grants and funding