MétaCan
Menu
Back to cohort
Record W4413418357 · doi:10.1016/j.nbd.2025.107054

Nutrient sensing receptor GPRC6A regulates mTORC1 signaling and Tau biology

2025· article· en· W4413418357 on OpenAlexaff
Chao Ma, Kelsey Campbell, Andrii Kovalenko, Leslie A. Sandusky‐Beltran, Huimin Liang, Jerry B. Hunt, John Calahatian, Mani Kallupurackal, Shalini Pandey, Muskan Vasisht, Mallory Watler, Zainuddin Quadri, Camilla Michalski, Margaret Fahnestock, Athanasios Papangelis, Daniel Sejer Pedersen, Trond Ulven, Kevin Nash, Maj‐Linda B. Selenica, Dave Morgan, Paula C. Bickford, Daniel C. Lee

Bibliographic record

VenueNeurobiology of Disease · 2025
Typearticle
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsMcMaster University
FundersNational Institute on AgingNational Institutes of HealthEdward N. and Della L. Thome Memorial FoundationFlorida Department of HealthBrightFocus FoundationAlzheimer's Association
KeywordsmTORC1Cell biologyBiologySignal transductionReceptorNeurosciencePI3K/AKT/mTOR pathwayBiochemistry

Abstract

fetched live from OpenAlex

Tauopathies, including Alzheimer's disease (AD), comprise microtubule-associated protein tau aggregates that cause neuronal cell death and clinical cognitive decline. Reducing overall tau abundance remains a central strategy for therapeutics; however, no disease-modifying treatment exists to date. One principal pathway for balancing cellular proteostasis includes the mechanistic target of rapamycin complex 1 (mTORC1) signaling. Recently, arginine emerged as one of the primary amino acids to activate mTORC1 through several intracellular arginine sensors and an extracellular arginine receptor, namely the G protein-coupled receptor (GPCR) family C, group 6, member A (GPRC6A). Human AD brains were previously reported with elevated mTORC1 signaling; however, it is unclear whether arginine sensing and signaling to mTORC1 plays a role in tauopathies. Herein, we examined arginine sensing associated with mTORC1 signaling in the human AD and animal models of tauopathy. We found that human AD brains maintained elevated levels of arginine sensors with potential uncoupling of arginine sensing pathways. Furthermore, we observed increased GPRC6A and arginine in the brain, accompanied by increased mTORC1 signaling and decreased autophagy in a mouse model of tauopathy (Tau PS19). We also discovered that both supplementing arginine and overexpressing GPRC6A in cell culture models could independently activate mTORC1 and promote tau accumulation. In addition, we found that suppressing GPRC6A signaling by either genetic reduction or pharmacological antagonism reduced tau accumulation, phosphorylation, and oligomerization. Overall, these findings uncover the crucial role of arginine sensing pathways in deregulating mTORC1 signaling in tauopathies and identify GPRC6A as a promising target for future therapeutics in tauopathies and other proteinopathies. SIGNIFICANCE STATEMENT: Tauopathies, including Alzheimer's disease (AD), accumulate pathogenic tau protein inclusions that potentially contribute to the hyperactive mechanistic target of rapamycin complex 1 (mTORC1) signaling and eventually cause neuronal cell death. Here, we presented novel findings that AD and animal models of tauopathy maintained increased expression of arginine sensors and uncoupling of arginine sensing associated with mTORC1 signaling. We investigated the role of a putative extracellular arginine and basic L-amino acid sensing G protein-coupled receptor (GPCR) family C, group 6, member A (GPRC6A) in activating mTORC1 and accelerating pathogenic tau phenotypes in several cell models. Additionally, we showed that genetic repression or antagonism of GPRC6A signaling provides a novel therapeutic target for tauopathies and other proteinopathies.

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 score0.001
Threshold uncertainty score0.003

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.008
GPT teacher head0.250
Teacher spread0.242 · 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
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueNeurobiology of DiseaseSame topicDiabetes Treatment and ManagementFrench-language works237,207