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Record W2410639191 · doi:10.1503/jpn.150131

Progranulin deficiency induces overactivation of <i>WNT5A</i> expression via TNF-α/NF-κB pathway in peripheral cells from frontotemporal dementia-linked granulin mutation carriers

2016· article· en· W2410639191 on OpenAlexvenueno aff
Carolina Alquézar, Ana de la Encarnación, Fermín Moreno, Adolfo López de Munaín, Ángeles Martín‐Requero

Bibliographic record

VenueJournal of Psychiatry and Neuroscience · 2016
Typearticle
Languageen
FieldMedicine
TopicAmyotrophic Lateral Sclerosis Research
Canadian institutionsnot available
Fundersnot available
KeywordsFrontotemporal lobar degenerationBiologyMutationMolecular biologyCancer researchFrontotemporal dementiaInternal medicineMedicineGeneticsGeneDementia

Abstract

fetched live from OpenAlex

BACKGROUND: Loss-of-function progranulin gene (GRN) mutations have been identified as the major cause of frontotemporal lobar degeneration with transactive response (TAR) DNA-binding protein 43 (TDP-43) pathology (frontotemporal lobar degeneration [FTLD]-TDP); however, little is known about the association between progranulin (PGRN) deficiency and neuronal loss in individuals with FTLD-TDP. Previously we reported enhanced proliferative activity associated with the activation of WNT5A/CDK6/pRb signalling in PGRN-deficient cells. The objective of this work was to elucidate the association between PGRN deficiency, WNT5A signalling and cell proliferation in immortalized lymphoblasts from carriers of the c.709-1G > A GRN mutation (asymptomatic and FTLD-TDP). METHODS: We assessed cell proliferation in carriers of the c.709-1G > A GRN gene mutation and controls without GRN mutation and without sign of neurologic degeneration by cell counting or using an MTT assay. We used a luciferase assay to measure the nuclear factor-κ (NF-κ) activity. We evaluated messenger RNA levels using quantitative real-time polymerase chain reaction and protein levels by immunoblotting. Co-immunoprecipitation was used to analyze the interaction between PGRN and its receptors. RESULTS: We enrolled 19 carriers of the GRN gene mutation and 10 controls in this study. The PGRN-deficient cells showed increased expression of WNT5A due to NF-κB signalling overactivation. We observed a competition between PGRN and tumour necrosis factor-α (TNF-α) for binding both TNF receptors (TNFR) I and II. Blocking NF-κB signalling using wedelolactone or specific antibodies against TNFRs inhibited WNT5A overexpression and proliferation of PGRN-deficient cells. Conversely, the activation of NF-κB signalling by TNF-α increased WNT5A-dependent proliferation of control cells. LIMITATIONS: All cell lines were derived from individuals harboring the same splicing GRN mutation. Nevertheless, most of the known GRN mutations lead to haploinsufficiency of the protein. CONCLUSION: Our results revealed an important role of NF-κB signalling in PGRN-associated FTLD-TDP and confirm that PGRN can bind to TNF-α receptors regulating the expression of WNT5A, suggesting novel targets for treatment of FTLD-TDP linked to GRN mutations.

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 score0.005

Distilled classifier scores by category (both heads)

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)0.0020.001

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 head0.021
GPT teacher head0.279
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

Citations36
Published2016
Admission routes1
Has abstractyes

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