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Record W4380883706 · doi:10.1002/alz.065537

Alzheimer’s Disease as an Autoimmune Disease

2023· article· en· W4380883706 on OpenAlexaff
Donald F. Weaver, Autumn Meek, Mark A. Reed, Christopher Barden

Bibliographic record

VenueAlzheimer s & Dementia · 2023
Typearticle
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsKrembil Foundation
Fundersnot available
KeywordsNeuroscienceInnate immune systemMechanism (biology)DiseaseAmyloid (mycology)In vivoBiologyComputational biologyImmune systemChemistryImmunologyMedicinePhysicsPathology

Abstract

fetched live from OpenAlex

Abstract Background The identification of new exploitable molecular pathogeneses (beyond the conventional amyloid hypothesis) for Alzheimer’s disease (AD) is a continuing neurotherapeutic priority, and has yielded a range of mechanistic proposals including immunopathy, gliopathy, mitochondriopathy, synaptopathy. However, as these new hypotheses emerge, they are often regarded as mutually exclusive and even in competition. Rather than unconditionally rejecting the role of amyloid‐β (Aβ) (or any other proposed mechanism), the need for a broadly‐encompassing model of AD, which harmonizes multiple divergent theories into a single unified explanation emerges as a much‐needed goal. Method We performed a comprehensive series of in silico, in vitro and in vivo studies explicitly evaluating the atomistic‐molecular mechanisms of cytokine‐mediated and Aβ‐mediated neurotoxicities in AD. Next, new chemical entities were synthesized to probe the pathways identified by these molecular mechanism studies and to provide prototypic starting points in the development of small molecule therapeutics. Result In response to various stimuli (e.g. infection, trauma, ischemia, air pollution, depression), Aβ is released as an early responder immunopeptide triggering an innate immunity cascade in which Aβ exhibits both immunomodulatory and antimicrobial properties (whether bacteria are present, or not), resulting in a misdirected attack upon ‘self’ neurons, arising from analogous electronegative surface topologies between neurons and bacteria, and rendering them similarly susceptible to membrane‐penetrating attack by antimicrobial peptides (AMPs) such as Aβ. Following this self‐attack, the resulting necrotic (but not apoptotic) neuronal breakdown products diffuse to adjacent neurons eliciting further release of Aβ, leading to a chronic self‐perpetuating autoimmune cycle. AD thus emerges as a brain‐centric autoimmune disorder of innate immunity. Based upon the hypothesis that autoimmune processes are susceptible to endogenous regulatory processes, a subsequent comprehensive screening program of small molecules normally present in human brain identified tryptophan metabolism as a regulator of brain innate immunity and a source of potential endogenous anti‐Alzheimer’s molecules capable of chemical modification into multi‐site therapeutic modulators targeting AD’s complex immunopathic‐proteopathic pathogenesis. Conclusion Conceptualizing AD as a brain‐centric autoimmune disease of innate immunity (with Aβ as an immunopeptide), and identifying endogenous regulators of this autoimmunity, represents a novel comprehensive conceptualization approach to AD with therapeutic implications.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.049
GPT teacher head0.344
Teacher spread0.295 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2023
Admission routes1
Has abstractyes

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