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A New Mouse Model of Giant Axonal Neuropathy with Overt Phenotypes and Neurodegeneration Driven by Neurofilament Disorganization

2023· article· en· W4367840076 on OpenAlexafffund
Banshi Nath, Jean‐Pierre Julien

Bibliographic record

VenueJournal of Neuroscience · 2023
Typearticle
Languageen
FieldNeuroscience
TopicHereditary Neurological Disorders
Canadian institutionsUniversité LavalCentre Jeunesse de QuebecInstitut Universitaire en Santé Mentale de Québec
FundersCanadian Institutes of Health ResearchGovernment of Canada
KeywordsNeurodegenerationNeurofilamentNeuroinflammationNeuroscienceGenetically modified mousePeripherinKnockout mousePathogenesisBiologyAmyotrophic lateral sclerosisPhenotypeDiseaseTransgenePathologyMedicineImmunologyGeneGenetics

Abstract

fetched live from OpenAlex

Research on pathogenic mechanisms underlying giant axonal neuropathy (GAN), a disease caused by a deficiency of gigaxonin, has been hindered by the lack of appropriate animal models exhibiting substantial symptoms and large neurofilament (NF) swellings, a hallmark of the human disease. It is well established that intermediate filament (IF) proteins are substrates for gigaxonin-mediated degradation. However, it has remained unknown to what extent NF accumulations contribute to GAN pathogenesis. Here, we report the generation of a new mouse model of GAN that is based on crossing transgenic mice overexpressing peripherin (Prph) with mice knockout for Gan . The Gan −/− ;TgPer mice developed early onset sensory-motor deficits along with IF accumulations made up of NF proteins and of Prph, causing swelling of spinal neurons at a young age. Abundant inclusion bodies composed of disorganized IFs were also detected in the brain of Gan −/− ;TgPer mice. At 12 months of age, the Gan −/− ;TgPer mice exhibited cognitive deficits as well as severe sensory and motor defects. The disease was associated with neuroinflammation and substantial loss of cortical neurons and spinal neurons. Giant axons (≥160 μm 2 ) enlarged by disorganized IFs, a hallmark of GAN disease, were also detected in dorsal and ventral roots of the Gan −/− ;TgPer mice. These results, obtained with both sexes, support the view that the disorganization of IFs can drive some neurodegenerative changes caused by gigaxonin deficiency. This new mouse model should be useful to investigate the pathogenic changes associated with GAN disease and for drug testing. SIGNIFICANCE STATEMENT Research on pathogenic mechanism and treatment of GAN has been hampered by the lack of animal models exhibiting overt phenotypes and substantial neurofilament disorganization, a hallmark of the disease. Moreover, it remains unknown whether neurologic defects associated with gigaxonin deficiency in GAN are because of neurofilament disorganization as gigaxonin may also act on other protein substrates to mediate their degradation. This study reports the generation of a new mouse model of GAN based on overexpression of Prph in the context of targeted disruption of gigaxonin gene. The results support the view that neurofilament disorganization may contribute to neurodegenerative changes in GAN disease. The Gan −/− ;TgPer mice provide a unique animal model of GAN for drug testing.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.377
Threshold uncertainty score0.665

Codex and Gemma teacher scores by category

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

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 head0.028
GPT teacher head0.233
Teacher spread0.205 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations7
Published2023
Admission routes2
Has abstractyes

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