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Record W4312086833 · doi:10.1002/alz.068080

Identification TDP‐43 fragments specific for frontotemporal lobar degeneration with TDP‐43 inclusions

2022· article· en· W4312086833 on OpenAlexaff
Lauren M. Forgrave, Yun Li, Kyung‐Mee Moon, Ian R. Mackenzie, Leonard J. Foster, Mari L. DeMarco

Bibliographic record

VenueAlzheimer s & Dementia · 2022
Typearticle
Languageen
FieldMedicine
TopicAmyotrophic Lateral Sclerosis Research
Canadian institutionsSt. Paul's HospitalProvidence Health CareUniversity of British Columbia
Fundersnot available
KeywordsFrontotemporal lobar degenerationPathologyHigh resolutionBiologyMedicinePsychologyFrontotemporal dementiaDiseaseDementia

Abstract

fetched live from OpenAlex

Abstract Background Ante‐mortem biomarkers specific for TDP‐43 pathology are highly desired given the challenge in distinguishing frontotemporal lobar degeneration with TDP‐43 pathology (FTLD‐TDP) from phenotypically related disorders. TDP‐43 post‐translational modifications, like C‐terminal fragments, are regarded as disease‐specific TDP‐43 proteoforms; however, the exact structure of these proteoforms remains unclear. This lack of clarity is due in part to the use of instrumentation and techniques with low structural resolution and the study of small sample sizes. With this in mind, we performed high resolution mass spectrometry (HRMS) analysis of brain tissue from cases with and without TDP‐43 proteinopathy to identify TDP‐43 proteoforms unique to FTLD‐TDP. Method HRMS was used to determine TDP‐43 proteoform composition in insoluble frontal lobe brain tissue from immunohistochemically‐confirmed FTLD‐TDP (n=13), related dementias (i.e., Alzheimer’s disease and FTLD‐tau without TDP‐43 deposits; n=10) and neuropathologically‐unaffected controls (n=3). Brain tissue was fractioned by gel electrophoresis, with HRMS analysis performed on molecular weight regions corresponding to <28 kDa (low molecular weight TDP; L‐TDP), 28‐38 kDa (mid molecular weight TDP; M‐TDP), and 38‐55 kDa (intact TDP; I‐TDP). Result In all samples tested, the greatest TDP‐43 sequence coverage was observed for I‐TDP, followed by L‐TDP and then M‐TDP. TDP‐43 peptides from L‐TDP were more frequently detected in the FTLD‐TDP cases compared to both sets of controls, whereas no frequency differences were observed for I‐TDP and M‐TDP. Quantitative analysis revealed peptide concentrations from M‐ and L‐TDP were significantly increased in FTLD‐TDP cases compared to controls. The L‐TDP peptides concentrations differentiated FTLD‐TDP cases from related dementias and unaffected controls with 78% sensitivity and 100% specificity. Further, three in vivo cleavage sites of TDP‐43 were identified, which were unique to FTLD‐TDP cases. Conclusion This is the largest reported proteomics study to date of histology‐confirmed FTLD‐TDP. This is also the first study to include a large number and range of control tissues, and to provide supporting evidence for in vivo cleavage sites including corroboration of the proteolytic fragment recently found in TDP‐43 fibrils. Clarity and consensus on the sequence of TDP‐43 disease‐specific proteoforms will be helpful in advancing biomarker and drug discovery efforts for TDP‐43 proteopathies.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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

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 head0.307
Teacher spread0.258 · 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 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

Citations1
Published2022
Admission routes1
Has abstractyes

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