Affiliations: Quantitative Neuroimaging Laboratory, Brain Health Imaging Institute, Department of Radiology, Weill Cornell Medicine, New York, NY, USA
Correspondence:
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Correspondence to: Qolamreza R. Razlighi, PhD, Associate Professor of Neuroscience, Director of Quantitative Neuroimaging Laboratory, Brain Health Imaging Institute, Department of Radiology, Weill Cornell Medicine, 413 East 69th Street, BRB 1504, New York, NY 10065, USA. Tel.: +1 646 962 6771; Fax: +1 646 962 0577; E-mail: qrr4001@med.cornell.edu.
Note: [1] Data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (http://adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found at: http://adni.loni.usc.edu/wp-content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf
Abstract: Background:While amyloid-β (Aβ) plaques and tau tangles are the well-recognized pathologies of Alzheimer’s disease (AD), they are more often observed in healthy individuals than in AD patients. This discrepancy makes it extremely challenging to utilize these two proteinopathies as reliable biomarkers for the early detection as well as later diagnosis of AD. Objective:We hypothesize and provide preliminary evidence that topographically overlapping Aβ and tau within the default mode network (DMN) play more critical roles in the underlying pathophysiology of AD than each of the tau and/or Aβ pathologies alone. Methods:We used our newly developed quantification methods and publicly available neuroimaging data from 303 individuals to provide preliminary evidence of our hypothesis. Results:We first showed that the probability of observing overlapping Aβ and tau is significantly higher within than outside the DMN. We then showed evidence that using Aβ and tau overlap can increase the reliability of the prediction of healthy individuals converting to mild cognitive impairment (MCI) and to a lesser degree converting from MCI to AD. Finally, we provided evidence that while the initial accumulations of Aβ and tau seems to be started independently in the healthy participants, the accumulations of the two pathologies interact in the MCI and AD groups. Conclusion:These findings shed some light on the complex pathophysiology of AD and suggest that overlapping Aβ and tau pathologies within the DMN might be a more reliable biomarker of AD for early detection and later diagnosis of the disease.
