% IMPORTANT: The following is UTF-8 encoded. This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.
@ARTICLE{Murray:282475,
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},
title = {{A}ccelerating biomedical discoveries in brain health
through transformative neuropathology of aging and
neurodegeneration.},
journal = {Neuron},
volume = {113},
number = {22},
issn = {0896-6273},
address = {[Cambridge, Mass.]},
publisher = {Cell Press},
reportid = {DZNE-2025-01298},
pages = {3703 - 3721},
year = {2025},
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 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.},
subtyp = {Review Article},
keywords = {Humans / Brain: pathology / Brain: diagnostic imaging /
Aging: pathology / Neurodegenerative Diseases: pathology /
Neuropathology: methods / Neuropathology: trends /
Neuroimaging: methods / Biomedical Research / biomarkers
(Other) / digital pathology (Other) / machine learning
(Other) / neuropathology (Other) / pathomics (Other) /
spatial biology (Other)},
cin = {AG Gokce},
ddc = {610},
cid = {I:(DE-2719)1013041},
pnm = {351 - Brain Function (POF4-351)},
pid = {G:(DE-HGF)POF4-351},
typ = {PUB:(DE-HGF)16},
pubmed = {pmid:40683248},
pmc = {pmc:PMC12313173},
doi = {10.1016/j.neuron.2025.06.014},
url = {https://pub.dzne.de/record/282475},
}