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Record W4380987902 · doi:10.3389/fendo.2023.1171933

Impact of an SLC30A8 loss-of-function variant on the pancreatic distribution of zinc and manganese: laser ablation-ICP-MS and positron emission tomography studies in mice

2023· article· en· W4380987902 on OpenAlexaff
George Firth, Eleni Georgiadou, Alex Griffiths, Maral Amrahli, Jana Kim, Zilin Yu, Ming Hu, Theodora J. Stewart, Isabelle Leclerc, Haruka Okamoto, Daniel R. Gomez, Philip J. Blower, Guy A. Rutter

Bibliographic record

VenueFrontiers in Endocrinology · 2023
Typearticle
Languageen
FieldNursing
TopicTrace Elements in Health
Canadian institutionsCentre Hospitalier de l’Université de Montréal
FundersCentre For Medical Engineering, King’s College LondonMedical Research CouncilEPSRC Centre for Doctoral Training in Medical ImagingKing's College LondonDiabetes UKEngineering and Physical Sciences Research CouncilNational Institute for Health and Care ResearchImperial College LondonKing's College Hospital NHS Foundation TrustWellcome Trust
KeywordsPancreasIsletZincChemistryInternal medicineEndocrinologyKnockout mousePancreatic isletsBiologyMolecular biologyDiabetes mellitusGeneMedicineBiochemistry

Abstract

fetched live from OpenAlex

Introduction Common variants in the SLC30A8 gene, encoding the secretory granule zinc transporter ZnT8 (expressed largely in pancreatic islet alpha and beta cells), are associated with altered risk of type 2 diabetes. Unexpectedly, rare loss-of-function (LoF) variants in the gene, described in heterozygous individuals only, are protective against the disease, even though knockout of the homologous SLC30A8 gene in mice leads to unchanged or impaired glucose tolerance. Here, we aimed to determine how one or two copies of the mutant R138X allele in the mouse SLC30A8 gene impacts the homeostasis of zinc at a whole-body (using non-invasive 62Zn PET imaging to assess the acute dynamics of zinc handling) and tissue/cell level [using laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) to map the long-term distribution of zinc and manganese in the pancreas]. Methods Following intravenous administration of [62Zn]Zn-citrate (~7 MBq, 150 μl) in wild-type (WT), heterozygous (R138X+/−), and homozygous (R138X+/+) mutant mice (14–15 weeks old, n = 4 per genotype), zinc dynamics were measured over 60 min using PET. Histological, islet hormone immunohistochemistry, and elemental analysis with LA-ICP-MS (Zn, Mn, P) were performed on sequential pancreas sections. Bulk Zn and Mn concentration in the pancreas was determined by solution ICP-MS. Results Our findings reveal that whereas uptake into organs, assessed using PET imaging of 62Zn, is largely unaffected by the R138X variant, mice homozygous of the mutant allele show a substantial lowering (to 40% of WT) of total islet zinc, as anticipated. In contrast, mice heterozygous for this allele, thus mimicking human carriers of LoF alleles, show markedly increased endocrine and exocrine zinc content (1.6-fold increase for both compared to WT), as measured by LA-ICP-MS. Both endocrine and exocrine manganese contents were also sharply increased in R138X+/− mice, with smaller increases observed in R138X+/+ mice. Discussion These data challenge the view that zinc depletion from the beta cell is the likely underlying driver for protection from type 2 diabetes development in carriers of LoF alleles. Instead, they suggest that heterozygous LoF may paradoxically increase pancreatic β-cell zinc and manganese content and impact the levels of these metals in the exocrine pancreas to improve insulin secretion.

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 score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.023
GPT teacher head0.323
Teacher spread0.300 · 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".

Quick stats

Citations6
Published2023
Admission routes1
Has abstractyes

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