Evidence map›Paper›PMID 31615329›Full record

ArticleJournal of the Royal Society, Interface2019

Prion-like spreading of Alzheimer's disease within the brain's connectome.

Sveva Fornari, Amelie Schäfer, Mathias Jucker, Alain Goriely, Ellen Kuhl

Open access · hybridAbstract read
In one paragraph

Article in Journal of the Royal Society, Interface, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers.

0numbers the graph read from it
0cells of the map it votes in
62citing papers in PubMed
4.3field-weighted citation impact, top 5% of its field
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

62 citing papers in PubMed, 143 citations in OpenAlex.

  1. Article
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  7. Structure-function coupling in the human brainstem.bioRxiv : the preprint server for biology · 2026
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  9. Network Diffusion Modeling in Computational Neuroscience.Advances in experimental medicine and biology · 2026
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  18. A network-level transport model of tau progression in the Alzheimer's brain.Mathematical medicine and biology : a journal of the IMA · 2025
    Article
  19. Article
  20. Review

2 more citing papers are in PubMed but not listed here.

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 at 3 institutions in 3 countries.

Sveva FornariLiving Matter Laboratory, Stanford University, Stanford, CA, USA.
Amelie SchäferLiving Matter Laboratory, Stanford University, Stanford, CA, USA.
Mathias JuckerHertie-Institute for Clinical Brain Research/German Center for Neurodegenerative Diseases, Tübingen, Germany.
Alain GorielyMathematical Institute, University of Oxford, Oxford, UK.
Ellen KuhlLiving Matter Laboratory, Stanford University, Stanford, CA, USA.
Stanford University · USGerman Center for Neurodegenerative Diseases · DEUniversity of Oxford · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The prion hypothesis states that misfolded proteins can act as infectious agents that template the misfolding and aggregation of healthy proteins to transmit a disease. Increasing evidence suggests that pathological proteins in neurodegenerative diseases adopt prion-like mechanisms and spread across the brain along anatomically connected networks. Local kinetic models of protein misfolding and global network models of protein spreading provide valuable insight into several aspects of prion-like diseases. Yet, to date, these models have not been combined to simulate how pathological proteins multiply and spread across the human brain. Here, we create an efficient and robust tool to simulate the spreading of misfolded protein using three classes of kinetic models, the Fisher-Kolmogorov model, the Heterodimer model and the Smoluchowski model. We discretize their governing equations using a human brain network model, which we represent as a weighted Laplacian graph generated from 418 brains from the Human Connectome Project. Its nodes represent the anatomic regions of interest and its edges are weighted by the mean fibre number divided by the mean fibre length between any two regions. We demonstrate that our brain network model can predict the histopathological patterns of Alzheimer's disease and capture the key characteristic features of finite-element brain models at a fraction of their computational cost: simulating the spatio-temporal evolution of aggregate size distributions across the human brain throughout a period of 40 years takes less than 7 s on a standard laptop computer. Our model has the potential to predict biomarker curves, aggregate size distributions, infection times, and the effects of therapeutic strategies including reduced production and increased clearance of misfolded protein.

Indexed as

BrainConnectomeModels, NeurologicalNerve NetAlzheimer DiseaseFemaleHumansMalePrionsPrionsAlzheimer’s diseaseconnectomegraph Laplaciannetworkneurodegenerationprion

Identifiers

PMID31615329
PMCPMC6833337
OpenAlexW2980552311

What OpenQuestion 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 OpenQuestion graph.