4.7 Article

Tau-Atrophy Variability Reveals Phenotypic Heterogeneity in Alzheimer's Disease

Journal

ANNALS OF NEUROLOGY
Volume 90, Issue 5, Pages 751-762

Publisher

WILEY
DOI: 10.1002/ana.26233

Keywords

-

Funding

  1. Alzheimer's Disease Neuroimaging Initiative (ADNI) (National Institutes of Health) [U01 AG024904]
  2. DOD ADNI (Department of Defense) [W81XWH-12-2-0012]
  3. National Institute on Aging
  4. National Institute of Biomedical Imaging and Bioengineering
  5. AbbVie
  6. Alzheimer's Association
  7. Alzheimer's Drug Discovery Foundation
  8. Araclon Biotech
  9. BioClinica, Inc.
  10. Biogen
  11. Bristol-Myers Squibb Company
  12. CereSpir, Inc.
  13. Cogstate
  14. Eisai Inc.
  15. Elan Pharmaceuticals, Inc.
  16. Eli Lilly and Company
  17. EuroImmun
  18. F. Hoffmann-La Roche Ltd
  19. Genentech, Inc.
  20. Fujirebio
  21. GE Healthcare
  22. IXICO Ltd.
  23. Janssen Alzheimer Immunotherapy Research & Development, LLC.
  24. Johnson & Johnson Pharmaceutical Research & Development LLC.
  25. Lumosity
  26. Lundbeck
  27. Merck Co., Inc.
  28. Meso Scale Diagnostics, LLC.
  29. NeuroRx Research
  30. Neurotrack Technologies
  31. Novartis Pharmaceuticals Corporation
  32. Pfizer Inc.
  33. Piramal Imaging
  34. Servier
  35. Takeda Pharmaceutical Company
  36. Transition Therapeutics
  37. Northern California Institute for Research and Education

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The study aimed to investigate the impact of Tau neurofibrillary tangles on neurodegeneration, and identified age and burden of white matter hyperintensity lesions as related modulatory factors. Data analysis showed that grouping individuals based on the relationship between Tau neurofibrillary tangles and neurodegeneration may help identify potential contributors to neurodegeneration.
Objective Tau neurofibrillary tangles (T) are the primary driver of downstream neurodegeneration (N) and subsequent cognitive impairment in Alzheimer's disease (AD). However, there is substantial variability in the T-N relationship - manifested in higher or lower atrophy than expected for level of tau in a given brain region. The goal of this study was to determine if region-based quantitation of this variability allows for identification of underlying modulatory factors, including polypathology. Methods Cortical thickness (N) and F-18-Flortaucipir SUVR (T) were computed in 104 gray matter regions from a cohort of cognitively-impaired, amyloid-positive (A+) individuals. Region-specific residuals from a robust linear fit between SUVR and cortical thickness were computed as a surrogate for T-N mismatch. A summary T-N mismatch metric defined using residuals were correlated with demographic and imaging-based modulatory factors, and to partition the cohort into data-driven subgroups. Results The summary T-N mismatch metric correlated with underlying factors such as age and burden of white matter hyperintensity lesions. Data-driven subgroups based on clustering of residuals appear to represent different biologically relevant phenotypes, with groups showing distinct spatial patterns of higher or lower atrophy than expected. Interpretation These data support the notion that a measure of deviation from a normative relationship between tau burden and neurodegeneration across brain regions in individuals on the AD continuum captures variability due to multiple underlying factors, and can reveal phenotypes, which if validated, may help identify possible contributors to neurodegeneration in addition to tau, which may ultimately be useful for cohort selection in clinical trials. ANN NEUROL 2021

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