Accelerating biomedical discoveries in brain health through transformative neuropathology of aging and neurodegeneration
(2025) In Neuron 113(22). p.3703-3721- Abstract
Transformative neuropathology is redefining human brain research by integrating foundational descriptive pathology with advanced methodologies. These approaches, spanning multi-omics studies and machine learning applications, will drive discovery for the identification of biomarkers, therapeutic targets, and complex disease patterns through comprehensive analyses of postmortem human brain tissue. Yet critical challenges remain, including the sustainability of brain banks, expanding donor participation, strengthening training pipelines, enabling rapid autopsies, supporting collaborative platforms, and integrating data across modalities. Innovations in digital pathology, tissue quality enhancement, harmonization of data standards, and... (More)
Transformative neuropathology is redefining human brain research by integrating foundational descriptive pathology with advanced methodologies. These approaches, spanning multi-omics studies and machine learning applications, will drive discovery for the identification of biomarkers, therapeutic targets, and complex disease patterns through comprehensive analyses of postmortem human brain tissue. Yet critical challenges remain, including the sustainability of brain banks, expanding donor participation, strengthening training pipelines, enabling rapid autopsies, supporting collaborative platforms, and integrating data across modalities. Innovations in digital pathology, tissue quality enhancement, harmonization of data standards, and machine learning integration offer opportunities to accelerate tissue-level “pathomics” research in brain health through cross-disciplinary collaborations. Lessons from neuroimaging, particularly in establishing common data frameworks and multi-site collaborations, offer a valuable roadmap for streamlining innovations. In this perspective, we outline actionable solutions for leveraging existing resources and strengthening collaboration -where we envision future opportunities to drive translational discoveries stemming from transformative neuropathology.
(Less)
- author
- organization
- publishing date
- 2025-11-19
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- biomarkers, digital pathology, machine learning, neuropathology, pathomics, spatial biology
- in
- Neuron
- volume
- 113
- issue
- 22
- pages
- 19 pages
- publisher
- Cell Press
- external identifiers
-
- pmid:40683248
- scopus:105011042202
- ISSN
- 0896-6273
- DOI
- 10.1016/j.neuron.2025.06.014
- language
- English
- LU publication?
- yes
- additional info
- Publisher Copyright: © 2025 The Author(s).
- id
- f65dbfc6-8337-49c1-b19e-b9f1f34766ab
- date added to LUP
- 2026-01-27 13:58:49
- date last changed
- 2026-01-28 03:00:07
@article{f65dbfc6-8337-49c1-b19e-b9f1f34766ab,
abstract = {{<p>Transformative neuropathology is redefining human brain research by integrating foundational descriptive pathology with advanced methodologies. These approaches, spanning multi-omics studies and machine learning applications, will drive discovery for the identification of biomarkers, therapeutic targets, and complex disease patterns through comprehensive analyses of postmortem human brain tissue. Yet critical challenges remain, including the sustainability of brain banks, expanding donor participation, strengthening training pipelines, enabling rapid autopsies, supporting collaborative platforms, and integrating data across modalities. Innovations in digital pathology, tissue quality enhancement, harmonization of data standards, and machine learning integration offer opportunities to accelerate tissue-level “pathomics” research in brain health through cross-disciplinary collaborations. Lessons from neuroimaging, particularly in establishing common data frameworks and multi-site collaborations, offer a valuable roadmap for streamlining innovations. In this perspective, we outline actionable solutions for leveraging existing resources and strengthening collaboration -where we envision future opportunities to drive translational discoveries stemming from transformative neuropathology.</p>}},
author = {{Murray, Melissa E. and Smith, Colin and Menon, Vilas and Keene, C. Dirk and Lein, Ed and Hawrylycz, Michael and Aguzzi, Adriano and Benedetti, Brett and Brose, Katja and Caetano-Anolles, Kelsey and Sillero, Maria Inmaculada Cobos and Crary, John F. and De Jager, Philip L. and Faustin, Arline and Flanagan, Margaret E. and Gokce, Ozgun and Grant, Seth G.N. and Grinberg, Lea T. and Gutman, David A. and Hillman, Elizabeth M.C. and Huang, Zhi and Irwin, David J. and Jones, David T. and Kapasi, Alifiya and Karch, Celeste M. and Kukull, Walter T. and Lashley, Tammaryn and Lee, Edward B. and Lehner, Thomas and Parkkinen, Laura and Pedersen, Maria and Pritchett, Dominique and Rutledge, Matthew H. and Schneider, Julie A. and Seeley, William W. and Shepherd, Claire E. and Spires-Jones, Tara L. and Steen, Judith A. and Sutherland, Margaret and Vickovic, Sanja and Zhang, Bin and Stewart, David J. and Keiser, Michael J. and Vogel, Jacob W. and Dugger, Brittany N. and Phatnani, Hemali}},
issn = {{0896-6273}},
keywords = {{biomarkers; digital pathology; machine learning; neuropathology; pathomics; spatial biology}},
language = {{eng}},
month = {{11}},
number = {{22}},
pages = {{3703--3721}},
publisher = {{Cell Press}},
series = {{Neuron}},
title = {{Accelerating biomedical discoveries in brain health through transformative neuropathology of aging and neurodegeneration}},
url = {{http://dx.doi.org/10.1016/j.neuron.2025.06.014}},
doi = {{10.1016/j.neuron.2025.06.014}},
volume = {{113}},
year = {{2025}},
}