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Structural Network Efficiency Predicts Resilience to Cognitive Decline in Elderly at Risk for Alzheimer's Disease.

Florian U Fischer | Dominik Wolf | Oliver Tüscher | Andreas Fellgiebel | Alzheimer’s Disease Neuroimaging Initiative
Frontiers in aging neuroscience | 2021

Introduction: Functional imaging studies have demonstrated the recruitment of additional neural resources as a possible mechanism to compensate for age and Alzheimer's disease (AD)-related cerebral pathology, the efficacy of which is potentially modulated by underlying structural network connectivity. Additionally, structural network efficiency (SNE) is associated with intelligence across the lifespan, which is a known factor for resilience to cognitive decline. We hypothesized that SNE may be a surrogate of the physiological basis of resilience to cognitive decline in elderly persons without dementia and with age- and AD-related cerebral pathology.Methods: We included 85 cognitively normal elderly subjects or mild cognitive impairment (MCI) patients submitted to baseline diffusion imaging, liquor specimens, amyloid-PET and longitudinal cognitive assessments. SNE was calculated from baseline MRI scans using fiber tractography and graph theory. Mixed linear effects models were estimated to investigate the association of higher resilience to cognitive decline with higher SNE and the modulation of this association by increased cerebral amyloid, liquor tau or WMHV. Results: For the majority of cognitive outcome measures, higher SNE was associated with higher resilience to cognitive decline (p-values: 0.011-0.039). Additionally, subjects with higher SNE showed more resilience to cognitive decline at higher cerebral amyloid burden (p-values: <0.001-0.036) and lower tau levels (p-values: 0.002-0.015).Conclusion: These results suggest that SNE to some extent may quantify the physiological basis of resilience to cognitive decline most effective at the earliest stages of AD, namely at increased amyloid burden and before increased tauopathy.

Pubmed ID: 33692682

Research resources used in this publication

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Antibodies used in this publication

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Associated grants

  • Agency: NIA NIH HHS, United States
    Id: U01 AG024904

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ADNI - Alzheimer's Disease Neuroimaging Initiative (tool)

RRID:SCR_003007

Database of the results of the ADNI study. ADNI is an initiative to develop biomarker-based methods to detect and track the progression of Alzheimer's disease (AD) that provides access to qualified scientists to their database of imaging, clinical, genomic, and biomarker data.

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Foundation for the National Institutes of Health (tool)

RRID:SCR_004493

A public charity whose mission is to support the NIH in its mission to improve health, by forming and facilitating public-private partnerships for biomedical research and training. Its vision is Building Partnerships for Discovery and Innovation to Improve Health. The FNIH draws together the world''s foremost researchers and resources, pressing the frontier to advance critical discoveries. They are recognized as the number-one medical research charity in the countryleveraging support, and convening high level partnerships, for the greatest impact on the most urgent medical challenges we face today. Grants are awarded as part of a public-private partnership with the National Heart, Lung, and Blood Institute (NHLBI) on behalf of The Heart Truth in support of women''s heart health education and research. Funding for the Community Action Program is provided by the FNIH through donations from individuals and corporations including The Heart Truth partners Belk Department Stores, Diet Coke, and Swarovski. Successful biomedical research relies upon the knowledge, training and dedication of those who conduct it. Bringing multiple disciplines to bear on health challenges requires innovation and collaboration on the part of scientists. Foundation for NIH partnerships operate in a variety of ways and formats to recruit, train, empower and retain their next generation of researchers. From lectures and multi-week courses, to scholarships and awards through fellowships and residential training programs, their programs respond to the needs of scientists at every level and stage in their careers.

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SPM (tool)

RRID:SCR_007037

Software package for analysis of brain imaging data sequences. Sequences can be a series of images from different cohorts, or time-series from same subject. Current release is designed for analysis of fMRI, PET, SPECT, EEG and MEG.

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