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Identification of key regions mediating human melatonin type 1 receptor biased signaling revealed by natural variants

2018· article· en· W3168946679 on OpenAlexafffundabout
Alan Hégron, Bianca Plouffe, Amélie Bonnefond, Wenwen Gao, Philippe Froguel, Christian Le Gouill, Ralf Jockers, Michel Bouvier

Bibliographic record

VenueThe FASEB Journal · 2018
Typearticle
Languageen
FieldNeuroscience
TopicCircadian rhythm and melatonin
Canadian institutionsUniversité de Montréal
FundersCanadian Institutes of Health ResearchDefense Advanced Research Projects AgencyFondation pour la Recherche MédicaleNational Science FoundationNational Institutes of HealthAgence Nationale de la Recherche
KeywordsMelatoninMelatonin receptorReceptorBiologySignal transductionG protein-coupled receptorEndocrinologyInternal medicineCell biologyPineal glandGeneticsMedicine

Abstract

fetched live from OpenAlex

Background Melatonin is a circulating neurohormone mainly released from the pineal gland in a circadian manner regulating many physiological functions, such as glycemia homeostasis. A misregulation of the glycemia could lead to Type 2 Diabetes (T2D). Recently, a genetic variant (rs2119882) found on melatonin type 1 receptor (MT1) promoter has been associated to higher risks to develop T2D. Hypothesis Variants on the MT1 coding region could modify receptor signalling and consequently modulate incidence to develop T2D. Methods we performed a genome‐wide association studies with both normoglycemic individuals and T2D patients and 32 non synonymous polymorphisms of MT1 were identified. Our primary aim was to functionally characterize these variants to further verify if there is an association between specific impaired signaling pathways and higher risks to develop T2D. Affinity for melatonin (Kd) and cell surface expression of variants were measured using 125 I‐melatonin binding assays and enzyme‐linked immunosorbent assay (ELISA) respectively to be sure that all receptors were expressed at the cell surface. Melatonin dose‐response curves were performed at equivalent cell surface expression to determine MT1s efficacy and potency to activate each G protein using a bioluminescence resonance energy transfer (BRET) assay monitoring proximity between G alpha and G gamma proteins as activation indicator. Finally, b‐arrestin 2 recruitment to cytoplasmic membrane upon MT1s stimulated with melatonin was measured by monitoring BRET between RlucII‐fused b‐arrestin and the cytoplasmic membrane targeted sensor (rGFP‐fused to CAAX box of KRas). Results Results obtained by the functional characterization indicate several types of signaling signatures. Indeed, some mutations show a biased signaling between G protein activation and b‐arrestin recruitment, while others show G protein isoform selectivity. Conclusion Association studies between patients having MT1 mutations and these signaling signatures will help us to understand in a better way the relationship between melatonin and insulin and represent an opportunity to identify new potential genetic markers of higher risks to develop T2D. Support or Funding Information This work was supported by a grant from CIHR to MB, from FRM, ANR and Université Paris 5 Descartes to RJ and from NIH, NSF and DARPA to OL. PhD student fellowship from Université de Montréal to AH, postdoctoral fellowships from CIHR and from Diabetes Canada to BP and from FRM to AK also funded this work. This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

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)0.0020.000

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 head0.033
GPT teacher head0.282
Teacher spread0.248 · 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 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".

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Citations0
Published2018
Admission routes3
Has abstractyes

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