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Cornblath EJ, Li HL, Changolkar L, et al. Computational modeling of tau pathology spread reveals patterns of regional vulnerability and the impact of a genetic risk factor. Sci Adv. 2021;7(24)doi: 10.1126/sciadv.abg6677.
Cornblath, E. J., Li, H. L., Changolkar, L., Zhang, B., Brown, H. J., Gathagan, R. J., Olufemi, M. F., Trojanowski, J. Q., Bassett, D. S., Lee, V. M. Y., & Henderson, M. X. (2021). Computational modeling of tau pathology spread reveals patterns of regional vulnerability and the impact of a genetic risk factor. Science advances, 7(24), . https://doi.org/10.1126/sciadv.abg6677
Cornblath, Eli J, et al. "Computational modeling of tau pathology spread reveals patterns of regional vulnerability and the impact of a genetic risk factor." Science advances vol. 7,24 (2021). doi: https://doi.org/10.1126/sciadv.abg6677
Cornblath EJ, Li HL, Changolkar L, Zhang B, Brown HJ, Gathagan RJ, Olufemi MF, Trojanowski JQ, Bassett DS, Lee VMY, Henderson MX. Computational modeling of tau pathology spread reveals patterns of regional vulnerability and the impact of a genetic risk factor. Sci Adv. 2021 Jun 09;7(24). doi: 10.1126/sciadv.abg6677. Print 2021 Jun. PMID: 34108219; PMCID: PMC8189700.
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Sci Adv. 2021 Jun 09;7(24). doi: 10.1126/sciadv.abg6677. Print 2021 Jun.

Computational modeling of tau pathology spread reveals patterns of regional vulnerability and the impact of a genetic risk factor.

Science advances

Eli J Cornblath, Howard L Li, Lakshmi Changolkar, Bin Zhang, Hannah J Brown, Ronald J Gathagan, Modupe F Olufemi, John Q Trojanowski, Danielle S Bassett, Virginia M Y Lee, Michael X Henderson

Affiliations

  1. Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA.
  2. Department of Neuroscience, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
  3. Institute on Aging and Center for Neurodegenerative Disease Research, Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
  4. Department of Electrical and Systems Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA.
  5. Department of Physics and Astronomy, College of Arts and Sciences, University of Pennsylvania, Philadelphia, PA 19104, USA.
  6. Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
  7. Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
  8. Santa Fe Institute, Santa Fe, NM 87501, USA.
  9. Department of Neurodegenerative Science, Van Andel Institute, Grand Rapids, MI 49503, USA. [email protected].

PMID: 34108219 PMCID: PMC8189700 DOI: 10.1126/sciadv.abg6677

Abstract

Neuropathological staging studies have suggested that tau pathology spreads through the brain in Alzheimer's disease (AD) and other tauopathies, but it is unclear how neuroanatomical connections, spatial proximity, and regional vulnerability contribute. In this study, we seed tau pathology in the brains of nontransgenic mice with AD tau and quantify pathology development over 9 months in 134 brain regions. Network modeling of pathology progression shows that diffusion through the connectome is the best predictor of tau pathology patterns. Further, deviations from pure neuroanatomical spread are used to estimate regional vulnerability to tau pathology and identify related gene expression patterns. Last, we show that pathology spread is altered in mice harboring a mutation in leucine-rich repeat kinase 2. While tau pathology spread is still constrained by anatomical connectivity in these mice, it spreads preferentially in a retrograde direction. This study provides a framework for understanding neuropathological progression in tauopathies.

Copyright © 2021 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC).

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