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Record W4281785770 · doi:10.1101/2022.06.04.494826

Loss of RREB1 in pancreatic beta cells reduces cellular insulin content and affects endocrine cell gene expression

2022· preprint· en· W4281785770 on OpenAlexaff
Katia K. Mattis, Nicole A. J. Krentz, Christoph Metzendorf, Fernando Abaitua, Aliya F Spigelman, Han Sun, Antje K. Rottner, Austin Bautista, Eugenia Mazzaferro, Marta Perez‐Alcantara, Jocelyn E. Manning Fox, Jason Torres, Agata Weslowska-Andersen, Grace Z. Yu, Anubha Mahajan, Anders Larsson, Patrick E. MacDonald, Ben Davies, Marcel den Hoed, Anna L. Gloyn

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2022
Typepreprint
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsUniversity of Alberta
FundersUniversity of OxfordWellcome Trust
KeywordsBiologyGene knockdownZebrafishTranscription factorCell biologyIsletBeta cellCell growthInsulinInternal medicineEndocrinologyGeneGenetics

Abstract

fetched live from OpenAlex

Abstract Aims/hypothesis Genome-wide studies have uncovered multiple independent signals at the RREB1 locus associated with altered type 2 diabetes risk and related glycemic traits. However, little is known about the function of the zinc finger transcription factor RREB1 in glucose homeostasis or how changes in its expression and/or function influence diabetes risk. Methods A zebrafish model lacking rreb1a and rreb1b was used to study the effect of RREB1 loss in vivo . Using transcriptomic and cellular phenotyping of a human beta cell model (EndoC-βH1) and human induced pluripotent stem cell (hiPSC)-derived beta-like cells, we investigated how loss of RREB1 expression and activity affects pancreatic endocrine cell development and function. Ex vivo measurements of human islet function were performed in donor islets from carriers of RREB1 T2D-risk alleles. Results CRISPR-Cas9-mediated loss of rreb1a and rreb1b function in zebrafish supports an in vivo role for the transcription factor in beta cell mass, beta cell insulin expression, and glucose levels. Loss of RREB1 reduced insulin gene expression and cellular insulin content in EndoC-βH1 cells, and impaired insulin secretion under prolonged stimulation. Transcriptomic analysis of RREB1 knockdown and knockout EndoC-βH1 cells supports RREB1 as a novel regulator of genes involved in insulin secretion. In vitro differentiation of RREB1 KO/KO hiPSCs revealed a dysregulation of pro-endocrine cell genes, including RFX family members, suggesting that RREB1 also regulates genes involved in endocrine cell development. Human donor islets from carriers of T2D-risk alleles in RREB1 have altered glucose-stimulated insulin secretion ex vivo , consistent with RREB1 regulating islet cell function. Conclusions/interpretation Together, our results indicate that RREB1 regulates beta cell function by transcriptionally regulating the expression of genes involved in beta cell development and function. Research in context What is already known about this subject? Human genetic variation in RREB1 is associated with altered diabetes risk, variation in glycemic, and anthropometric traits RREB1 is a transcription factor that binds to Ras-responsive elements and is expressed in multiple diabetes relevant tissues, including pancreatic islets What is the key question? How does altered expression or function of RREB1 influence diabetes risk? What are the new findings? Knockdown and knockout of RREB1 in mature human EndoC-βH1 cells reduces expression of insulin transcript and cellular content, as well as insulin secretion under prolonged stress Carriers of the T2D-risk RREB1 coding allele trend towards reduced insulin content, but have improved glucose-stimulated insulin secretion A loss-of-function zebrafish model suggests that RREB1 is required for insulin expression How might this impact on clinical practice in the foreseeable future? RREB1 controls beta cell function and whole-body glucose homeostasis by transcriptionally regulating the development and function of pancreatic beta cells

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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.018
GPT teacher head0.219
Teacher spread0.201 · 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

Citations3
Published2022
Admission routes1
Has abstractyes

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