Evidence map›Paper›PMID 40585245›Full record

ArticleResearch square2025

Back to the Future: Predicting Individual Tau Progression in Alzheimer's Disease.

Robin Sandell, Justin Torok, Kamalini G Ranasinghe, Srikantan S Nagarajan, Ashish Raj

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in Research square, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Robin SandellDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA.ORCID https://orcid.org/0009-0006-1586-1278
Justin TorokDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA.
Kamalini G RanasingheMemory and Aging Center, University of California, San Francisco, CA, USA.
Srikantan S NagarajanDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA.
Ashish RajDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA.

Funding

Understanding disorder-specific neural pathophysiology in laryngeal dystonia and voice tremorP50DC019900 · NIDCD · MASSACHUSETTS EYE AND EAR INFIRMARY · PI Kristina Simonyan · 2021 to 2026
$11.9M
Understanding the dynamic interactions between tau pathology and microgliamediated inflammation in Alzheimer's DiseaseR01AG072753 · NIA · WEILL MEDICAL COLL OF CORNELL UNIV · PI BUTLER, TRACY A., GUPTA, AJAY · 2021 to 2025
$5.3M
The role of the cerebellum in speechR01DC017091 · NIDCD · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI John Francis Houde, RICHARD IVRY · 2019 to 2026
$4.5M
Predictive model of spread of Parkinson's pathology using network diffusionR01NS092802 · NINDS · WEILL MEDICAL COLL OF CORNELL UNIV · PI GUPTA, AJAY, RAJ, ASHISH · 2016 to 2020
$2.8M
Electrophysiological and molecular imaging of early AD progressionR01AG088398 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Kamalini Gayathree Ranasinghe · 2024 to 2026
$2.4M
Dynamic Brain Imaging of Speech in Primary Progressive AphasiaRF1NS100440 · NINDS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI GORNO TEMPINI, MARIA LUISA, HOUDE, JOHN FRANCIS · 2023 to 2023
$2.4M
Multimodal imaging measures to assess synaptic dysfunction in Alzheimer's diseaseR21AG077498 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI RANASINGHE, KAMALINI GAYATHREE · 2022 to 2022
$484k
NIA NIH HHS R01 AG072753NIA NIH HHS R01 AG088398NIA NIH HHS R21 AG077498NIDCD NIH HHS P50 DC019900NIDCD NIH HHS R01 DC017091NINDS NIH HHS R01 NS092802NINDS NIH HHS RF1 NS100440
6 · The paper itself

Abstract

Alzheimer's Disease (AD) is characterized by the spread of tau neurofibrillary tangles along the brain's structural network. The marked variability in pathology spread patterns across individuals necessitates a precision medicine approach. Here we introduce Stage-based Network Diffusion (StaND), a novel algorithm that combines statistical staging with biophysical modeling to predict patient-specific tau progression. Using data from 650 subjects in the Alzheimer's Disease Neuroimaging Initiative, StaND first estimates each subject's disease stage and then infers their individual tau seeding pattern, agglomeration rate, and transmission rate. The model is applied forward in time to predict regional tau distributions cross-sectionally and longitudinally. StaND outperforms benchmark models in both instances. Inferred tau seed patterns capture spatial heterogeneity, while rate parameters explain temporal and cognitive variability. Despite diverse initial seeding patterns, tau distributions converge across subjects over time. We also identify two distinct tau seeding archetypes with distinct clinical and demographic profiles. StaND offers a powerful new approach for understanding and forecasting the spatiotemporal dynamics of AD and is widely applicable to other neurodegenerative diseases.

Indexed as

Alzheimer’s DiseaseBiophysical ModelingPrecision MedicineStatistic Modeling

Identifiers

PMID40585245
PMCPMC12204357

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.