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Record W2924415036 · doi:10.1186/s40478-018-0654-6

Optic nerve thinning and neurosensory retinal degeneration in the rTg4510 mouse model of frontotemporal dementia

2019· article· en· W2924415036 on OpenAlexafffund
Ian F. Harrison, Rozalind Whitaker, Pietro Maria Bertelli, James M. O’Callaghan, Lajos Csincsik, Martina Bocchetta, Da Ma, Alice Fisher, Zeshan Ahmed, Tracey K. Murray, Michael J. O’Neill, Jonathan D. Rohrer, Mark F. Lythgoe, Imre Lengyel

Bibliographic record

VenueActa Neuropathologica Communications · 2019
Typearticle
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsSimon Fraser University
FundersMedical Research CouncilBiotechnology and Biological Sciences Research CouncilUK Regenerative Medicine PlatformMoorfields Eye Hospital NHS Foundation TrustQueen's UniversitySimon Fraser UniversityBrain Research TrustWolfson FoundationAlzheimer's SocietyNational Institute for Health and Care ResearchQueen's University BelfastUniversity College LondonEngineering and Physical Sciences Research CouncilAstraZenecaEli Lilly and Company
KeywordsRetinaFrontotemporal dementiaPathologyRetinalOptic nerveInner plexiform layerInner nuclear layerMedicineRetinal ganglion cellNeuroscienceDementiaOphthalmologyPsychology

Abstract

fetched live from OpenAlex

Visual impairments, such as difficulties in reading and finding objects, perceiving depth and structure from motion, and impaired stereopsis, have been reported in tauopathy disorders, such as frontotemporal dementia (FTD). These impairments however have been previously attributed to cortical pathologies rather than changes in the neurosensory retina or the optic nerve. Here, we examined tau pathology in the neurosensory retina of the rTg(tauP301L)4510 mouse model of FTD. Optic nerve pathology in mice was also assessed using MRI, and corresponding measurements taken in a cohort of five FTD sufferers and five healthy controls. rTg(tauP301L)4510 mice were imaged (T2-weighted MRI) prior to being terminally anesthetized and eyes and brains removed for immunohistochemical and histological analysis. Central and peripheral retinal labelling of tau and phosphorylated tau (pTau) was quantified and retinal layer thicknesses and cell numbers assessed. MR volumetric changes of specific brain regions and the optic nerve were compared to tau accumulation and cell loss in the visual pathway. In addition, the optic nerves of a cohort of healthy controls and behavioural variant FTD patients, were segmented from T1- and T2-weighted images for volumetric study. Accumulation of tau and pTau were observed in both the central and peripheral retinal ganglion cell (RGC), inner plexiform and inner nuclear layers of the neurosensory retina of rTg(tauP301L)4510 mice. This pathology was associated with reduced nuclear density (- 24.9 ± 3.4%) of the central RGC layer, and a reduced volume (- 19.3 ± 4.6%) and elevated T2 signal (+ 27.1 ± 1.8%) in the optic nerve of the transgenic mice. Significant atrophy of the cortex (containing the visual cortex) was observed but not in other area associated with visual processing, e.g. the lateral geniculate nucleus or superior colliculus. Atrophic changes in optic nerve volume were similarly observed in FTD patients (- 36.6 ± 2.6%). The association between tau-induced changes in the neurosensory retina and reduced optic nerve volume in mice, combined with the observation of optic nerve atrophy in clinical FTD suggests that ophthalmic tau pathology may also exist in the eyes of FTD patients. If tau pathology and neurodegeneration in the retina were to reflect the degree of cortical tau burden, then cost-effective and non-invasive imaging of the neurosensory retina could provide valuable biomarkers in tauopathy. Further work should aim to validate whether these observations are fully translatable to a clinical scenario, which would recommend follow-up retinal and optic nerve examination in FTD.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.228
Threshold uncertainty score0.310

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.080
GPT teacher head0.321
Teacher spread0.241 · 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 designObservational
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

Citations45
Published2019
Admission routes2
Has abstractyes

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