Evidence map›Paper›PMID 38512414›Full record

ArticleDiabetologia2024

Differential CpG methylation at Nnat in the early establishment of beta cell heterogeneity.

Vanessa Yu, Fiona Yong, Angellica Marta, Sanjay Khadayate, Adrien Osakwe, Supriyo Bhattacharya, Sneha S Varghese, Pauline Chabosseau, Sayed M Tabibi, Keran Chen and 26 more

Open access · hybridAbstract read
In one paragraph

Article in Diabetologia, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
9.2field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 16 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

36 authors at 9 institutions in 5 countries.

Vanessa Yu *Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, UK.
Fiona Yong *Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, UK.
Angellica Marta *Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, UK.
Sanjay KhadayateMRC Laboratory of Medical Sciences, London, UK.
Adrien OsakweQuantitative Life Sciences Program, McGill University, Montréal, QC, Canada.
Supriyo BhattacharyaDepartment of Computational and Quantitative Medicine, Beckman Research Institute, City of Hope, Duarte, CA, USA.
Sneha S VargheseDepartment of Translational Research and Cellular Therapeutics, Arthur Riggs Diabetes and Metabolism Research Institute, City of Hope, Duarte, CA, USA.
Pauline ChabosseauDepartment of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, UK.
Sayed M TabibiDepartment of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, UK.
Keran ChenDepartment of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, UK.
Eleni GeorgiadouDepartment of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, UK.
Nazia ParveenDepartment of Translational Research and Cellular Therapeutics, Arthur Riggs Diabetes and Metabolism Research Institute, City of Hope, Duarte, CA, USA.
Mara SuleimanDepartment of Clinical and Experimental Medicine, and AOUP Cisanello University Hospital, University of Pisa, Pisa, Italy.
Zoe StamoulisDepartment of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, UK.
Lorella MarselliDepartment of Clinical and Experimental Medicine, and AOUP Cisanello University Hospital, University of Pisa, Pisa, Italy.
Carmela De LucaDepartment of Clinical and Experimental Medicine, and AOUP Cisanello University Hospital, University of Pisa, Pisa, Italy.
Marta TesiDepartment of Clinical and Experimental Medicine, and AOUP Cisanello University Hospital, University of Pisa, Pisa, Italy.
Giada OstinelliCHUM Research Center and Faculty of Medicine, University of Montréal, Montréal, QC, Canada.
Luis Delgadillo-SilvaCHUM Research Center and Faculty of Medicine, University of Montréal, Montréal, QC, Canada.
Xiwei WuDepartment of Computational and Quantitative Medicine, Beckman Research Institute, City of Hope, Duarte, CA, USA.
Yuki HatanakaMRC Laboratory of Medical Sciences, London, UK.
Alex MontoyaMRC Laboratory of Medical Sciences, London, UK.
James ElliottMRC Laboratory of Medical Sciences, London, UK.
Bhavik PatelMRC Laboratory of Medical Sciences, London, UK.
Nikita DemchenkoMRC Laboratory of Medical Sciences, London, UK.
Chad WhildingMRC Laboratory of Medical Sciences, London, UK.
Petra HajkovaMRC Laboratory of Medical Sciences, London, UK.
Pavel ShliahaMRC Laboratory of Medical Sciences, London, UK.
Holger KramerMRC Laboratory of Medical Sciences, London, UK.
Yusuf AliNutrition, Metabolism and Health Programme & Centre for Microbiome Medicine, Lee Kong Chian School of Medicine, Nanyang Technological University Singapore, Singapore, Republic of Singapore.ORCID http://orcid.org/0000-0002-0681-1125
Piero MarchettiDepartment of Clinical and Experimental Medicine, and AOUP Cisanello University Hospital, University of Pisa, Pisa, Italy.
Robert SladekQuantitative Life Sciences Program, McGill University, Montréal, QC, Canada.
Sangeeta DhawanDepartment of Translational Research and Cellular Therapeutics, Arthur Riggs Diabetes and Metabolism Research Institute, City of Hope, Duarte, CA, USA.
Dominic J WithersMRC Laboratory of Medical Sciences, London, UK.
Guy A RutterDepartment of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, UK. g.rutter@imperial.ac.uk.ORCID http://orcid.org/0000-0001-6360-0343
Steven J MillershipDepartment of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, UK. s.millership@imperial.ac.uk.ORCID http://orcid.org/0000-0001-6947-7059
Imperial College London · GBCity of Hope · USUniversity of Pisa · ITNanyang Technological University · SGMcGill University · CAUniversité de Montréal · CASt George's, University of London · GBUniversity of East Anglia · GBUniversity of Oxford · GB

Funding

Control of insulin secretion by mitochondrial fusionR01DK135268 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Brett A Kaufman, Scott Soleimanpour · 2023 to 2026
$2.4M
Regulation of beta-cell homeostasis by DNA methylation and hydroxymethylation.R01DK120523 · NIDDK · BECKMAN RESEARCH INSTITUTE/CITY OF HOPE · PI DHAWAN, SANGEETA · 2019 to 2023
$2.2M
Medical Research Council MC-A654-5QB40Medical Research Council MR/R010676/1Medical Research Council MR/R022259/1NIDDK NIH HHS R01 DK120523NIDDK NIH HHS R01 DK135268NIH HHS R01DK120523Wellcome TrustWellcome Trust 093082/Z/10/ZWellcome Trust 204834/Z/16/ZWellcome Trust WT212625/Z/18/Z
6 · The paper itself

Abstract

aims/hypothesisBeta cells within the pancreatic islet represent a heterogenous population wherein individual sub-groups of cells make distinct contributions to the overall control of insulin secretion. These include a subpopulation of highly connected 'hub' cells, important for the propagation of intercellular Ca

methodsSingle-cell RNA-seq datasets were examined using Seurat 4.0 and ClusterProfiler running under R. Transgenic mice expressing enhanced GFP under the control of the Nnat enhancer/promoter regions were generated for FACS of beta cells and downstream analysis of CpG methylation by bisulphite sequencing and RNA-seq, respectively. Animals deleted for the de novo methyltransferase DNA methyltransferase 3 alpha (DNMT3A) from the pancreatic progenitor stage were used to explore control of promoter methylation. Proteomics was performed using affinity purification mass spectrometry and Ca

resultsNnat mRNA was differentially expressed in a discrete beta cell population in a developmental stage- and DNA methylation (DNMT3A)-dependent manner. Thus, pseudo-time analysis of embryonic datasets demonstrated the early establishment of Nnat-positive and -negative subpopulations during embryogenesis. NNAT expression is also restricted to a subset of beta cells across the human islet that is maintained throughout adult life. NNAT CONCLUSIONS/

interpretationThese findings demonstrate that differential DNA methylation at Nnat represents a novel means through which beta cell heterogeneity is established during development. We therefore hypothesise that changes in methylation at this locus may contribute to a loss of beta cell hierarchy and connectivity, potentially contributing to defective insulin secretion in some forms of diabetes. DATA AVAILABILITY: The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD048465.

Indexed as

CpG IslandsDNA MethylationInsulin-Secreting CellsAnimalsDNA Methyltransferase 3AHumansInsulinInsulin SecretionMembrane ProteinsMiceMice, TransgenicNerve Tissue ProteinsDNA Methyltransferase 3ADnmt3a protein, mouseInsulinMembrane ProteinsNerve Tissue ProteinsBeta cell developmentCa2+ConnectivityCpG methylationHeterogeneityIdentityImprinted genesInsulinIsletNeuronatinType 2 diabetes

Identifiers

PMID38512414
PMCPMC11058053
OpenAlexW4393052939

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.