GEO series

Imeglimin, unlike metformin, does not perturb differentiation of human induced pluripotent stem cells towards pancreatic β-like cells and rather enhances gain in β cell identity gene sets

GSE242776 Homo sapiens (human) RNA-seq (gene expression) 18 samples Submitted 2025/01/20 Platform GPL24676

At a glance

RNA-seq (gene expression) · human · 18 samples

What it is: RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism: Homo sapiens (human)
Samples: 18 samples: 6 conditions, mostly in triplicateGroups are read from the sample names, not from the paper. Check the list below.
Data you can get: A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Paper: Imeglimin, unlike metformin, does not perturb differentiation of human induced pluripotent stem cells towards pancreatic β-like cells and rather enhances gain in β cell identity gene setsJournal of diabetes investigation · 2025

Summary (written by the submitters)

Aims/Introduction: Metformin treatment for hyperglycemia in pregnancy (HIP) beneficially improves maternal glucose metabolism and reduces perinatal complications. However, metformin could impede pancreatic β cell development via impaired mitochondrial function. A new anti-diabetes drug imeglimin, developed based on metformin, improves mitochondrial function.

Read the full summary ↓

Here we examine the effect of imeglimin on β cell differentiation using human induced pluripotent stem cell (iPSC)-derived pancreatic islet-like spheroid (SC-islet) models. Materials and Methods: Human iPSCs are differentiated into SC-islets by three-dimensional culture with and without imeglimin or metformin. Differentiation efficiencies of SC-islets were analyzed by flow cytometry, immunostaining, quantitative PCR, and insulin secretion assay. RNA sequencing and oxygen consumption rate were obtained for further characterization of SC-islets. SC-islets were cultured with proinflammatory cytokines, in part mimicking the uterus environment in HIP. Results: Metformin perturbed SC-islet differentiation while imeglimin did not alter it. Furthermore, imeglimin enhanced the gene expressions of β cell lineage markers. Maintenance of mitochondrial function and optimization of TGF-β and Wnt signaling were considered potential mechanisms for augmented β cell maturation by imeglimin. In the presence of proinflammatory cytokines, imeglimin ameliorated β cell differentiation impaired by cytokines and metformin. Conclusions: Imeglimin does not perturb differentiation of SC-islet cells and rather enhances gain in β cell identity gene sets in contrast to metformin. This may lead to the improvement of in vitro β cell differentiation protocols.

Published in

Imeglimin, unlike metformin, does not perturb differentiation of human induced pluripotent stem cells towards pancreatic β-like cells and rather enhances gain in β cell identity gene sets

Imada T, Sasaki S, Yamaguchi H et al. · Journal of diabetes investigation 2025 · PMID 39829307 · doi:10.1111/jdi.14410

This dataset

Open GSE242776 in finder → Find more human RNA-seq datasets →

Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

Series matrix ↓

2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE242776_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓

3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

Raw reads on ENA ↗

What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1014490 and SRA study SRP459392. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39829307) ↗

Study design

6 conditions, mostly in triplicate

V ×3 M ×3 I ×3 C ×3 CM ×3 CI ×3

Supports a between-group comparison across 18 samples.

How we read this: 6 replicated groups read from 18 sample titles; they account for 18 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study

GSM7770360 V2 V
GSM7770361 V3 V
GSM7770362 V5 V
GSM7770363 M1 M
GSM7770364 M3 M
GSM7770365 M4 M
GSM7770366 I1 I
GSM7770367 I2 I
GSM7770368 I5 I
GSM7770369 C1 C
GSM7770370 C2 C
GSM7770371 C5 C
GSM7770372 CM2 CM
GSM7770373 CM3 CM
GSM7770374 CM5 CM
GSM7770375 CI2 CI
GSM7770376 CI4 CI
GSM7770377 CI5 CI

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