In vivo rate-determining steps of tau seed accumulation in Alzheimer’s disease

Meisl, Georg; Hidari, Eric; Allinson, Kieren; Rittman, Timothy; DeVos, Sarah L.; Sanchez, Justin S.; Xu, Catherine K.; Duff, Karen; Johnson, Keith A.; Rowe, James B.; Hyman, Bradley T.; Knowles, Tuomas P. J.; Klenerman, David

doi:10.1126/sciadv.abh1448

Cited by 94 publications

(83 citation statements)

References 44 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Our findings support recent studies that suggest Alzheimer’s disease clinical symptomatology begins when tau aggregates exist in multiple brain regions; that is, inhibiting the initial stochastic sequence(s) that enhance neurodegeneration before propagation is likely to be an effective treatment and not preventing spread [ 32 ].…”

Section: Resultssupporting

confidence: 89%

Stochasticity, Entropy and Neurodegeneration

Panegyres

2022

Brain Sciences

View full text Add to dashboard Cite

We previously suggested that stochastic processes are fundamental in the development of sporadic adult onset neurodegenerative disorders. In this study, we develop a theoretical framework to explain stochastic processes at the protein, DNA and RNA levels. We propose that probability determines random sequencing changes, some of which favor neurodegeneration in particular anatomical spaces, and that more than one protein may be affected simultaneously. The stochastic protein changes happen in three-dimensional space and can be considered to be vectors in a space-time continuum, their trajectories and kinetics modified by physiological variables in the manifold of intra- and extra-cellular space. The molecular velocity of these degenerative proteins must obey the second law of thermodynamics, in which entropy is the driver of the inexorable progression of neurodegeneration in the context of the N-body problem of interacting proteins, time-space manifold of protein-protein interactions in phase space, and compounded by the intrinsic disorder of protein-protein networks. This model helps to elucidate the existence of multiple misfolded proteinopathies in adult sporadic neurodegenerative disorders.

show abstract

Section: Resultssupporting

confidence: 89%

Stochasticity, Entropy and Neurodegeneration

Panegyres

2022

Brain Sciences

View full text Add to dashboard Cite

show abstract

“…Thus, solutions that target senescent glia in LOAD will likely help managing or treating symptoms in these other diseases; co-morbid pathologies may also have independent mechanisms inducing glial senescence. Furthermore, data from tau PET studies indicated that tau seeding occurs locally from Braak stages III+ 132 . As this tau propagation is correlated with increased microglial activity 146 , this reinforces the idea of paracrine glial senescence via spreading hp-tau.…”

Section: Discussionmentioning

confidence: 99%

“…Senescent microglia are thus putatively accountable for neuritic plaque formation and indirect NFT formation, critical A, hp-tau, and pro-inflammatory cytokine pathology beyond threshold tolerance, among localized brain regions corresponding to Braak staging, and overall LOAD progression 1,8,61,62,82,83,94,132 . Furthermore, state "B" senescent microglia are predicted to respond to overwhelming A aggregation with an increased type I IFN response 23,[97][98][99] , leading to pro-inflammatory cytokine secretion and Kv1.3 expression exacerbating local inflammation 122,[133][134][135] .…”

Section: Senescent Microglia Are Predicted To Transform Morphology Dr...mentioning

confidence: 99%

“…Thus, it is predicted that senescent microglia actively accelerate hp-tau seeding and build-up of neuritic plaques that tip preclinical LOAD into clinical progression 130 . Furthermore, the exacerbated, resulting localized concentration and gradual accumulation of A and neurofibrillary pathology determines clinical LOAD progression 132 , increasing synaptic loss, pro-inflammatory glial responses, and overall glial and paracrine senescence (Fig. 2).…”

Section: Senescent Microglia Are Predicted To Transform Morphology Dr...mentioning

confidence: 99%

See 1 more Smart Citation

The Glial Aging & Senescence Hypothesis of Late-onset Alzheimer’s

Lau¹,

Ramer²,

Tremblay³

2022

Preprint

View full text Add to dashboard Cite

Alzheimer’s disease (AD) predominantly occurs as a late-onset form (LOAD), involving neurodegeneration and cognitive decline with progressive memory loss. Over time, risk factors and aging promote accumulation of well-known AD pathologies in oxidative stress, amyloid-beta and tau protein pathology, as well as inflammation. Homeostatic glial functions regulate and suppress these AD pathologies; however, other glial states involve increased pro-inflammatory cytokine release and further pathology accumulation. Different stresses can additionally induce cellular senescence, or an irreversible differentiation process resulting in decreased supportive functions and increased, pro-inflammatory cytokine release. While these pathophysiological underpinnings all contribute to LOAD, they require temporal and mechanistic integration. This perspective hypothesizes that when individuals have threshold senescent glia accumulation, they transition from healthy cognition into mild cognitive impairment and LOAD diagnosis. Particularly, senescent microglia are predicted to represent a final threshold required for the tau pathology burden and spreading that corresponds to sustained neurodegeneration and dementia severity. We first explore age-related decline in glia that promote increases in AD pathologies, and then discuss emerging evidence linking oxidative stress, neurons containing tau pathology, and amyloid-beta to microglia, oligodendrocyte progenitor cell, and astrocyte senescence. Our hypothesis proposes that senescent astrocytes and oligodendrocyte progenitors pressure microglia to phagocytose neurons containing tau pathology. The resulting senescent microglia would form neuritic plaques and induce paracrine senescence transitioning into a progressive clinical dementia presentation. This predictive hypothesis can potentially account for why medications used to treat LOAD fail, as previous treatments have not reduced senescent glial burden. It is also coherent with the predominant hypotheses surrounding LOAD, generates testable hypotheses about LOAD, and increases rationale in testing senolytics as targeted treatments for LOAD arrest and reversal.

show abstract

“…Each of the proteins follows the dynamics of a modified heterodimer model with local and nonlocal interactions and a coupling parameter between two proteins 20,[27][28][29][30] . Motivated by Meisl et al 31 , we replace exponential growth with logistic growth in both the proteins Aβ and τP. Due to toxic variants of these proteins present in the brain cell, neuronal damage occurs in the brain.…”

Section: Introductionmentioning

confidence: 99%

Nonlocal Models in the Analysis of Brain Neurodegenerative Protein Dynamics with Application to Alzheimer's Disease

Pal¹,

Melnik²

2021

Preprint

View full text Add to dashboard Cite

It is well known that today nearly one in six of the world's population has to deal with neurodegenerative disorders. While a number of medical devices have been developed for the detection, prevention, and treatments of such disorders, some fundamentals of the progression of associated diseases are in urgent need of further clarification. In this paper, we focus on Alzheimer's disease, where it is believed that the concentration changes in amyloid-beta and tau proteins play a central role in its onset and development. A multiscale model is proposed to analyze the propagation of these concentrations in the brain connectome. In particular, we consider a modified heterodimer model for the protein-protein interactions. Higher toxic concentrations of amyloid-beta and tau proteins destroy the brain cell. We have studied these propagations for the primary and secondary and their mixed tauopathy. We model the damage of a brain cell by the nonlocal contributions of these toxic loads present in the brain cells. With the help of rigorous analysis, we check the stability behaviour of the stationary points corresponding to the homogeneous system. After integrating the brain connectome data into the developed model, we see that the spreading patterns of the toxic concentrations for the whole brain are the same, but their concentrations are different in different regions. Also, the time to propagate the damage in each region of the brain connectome is different.

show abstract

In vivo rate-determining steps of tau seed accumulation in Alzheimer’s disease

Abstract: Local replication doubles the number of tau aggregate in Alzheimer’s disease only once every 5 years, limiting the overall rate.

Cited by 94 publications

References 44 publications

Stochasticity, Entropy and Neurodegeneration

Stochasticity, Entropy and Neurodegeneration

The Glial Aging & Senescence Hypothesis of Late-onset Alzheimer’s

Nonlocal Models in the Analysis of Brain Neurodegenerative Protein Dynamics with Application to Alzheimer's Disease

Contact Info

Product

Resources

About