GSE197850: Glucagon-like Peptide-1 (GLP-1) Rescue Diabetic Cardiac Dysfuntions in Human iPSC-Derived Cardiomyocytes

Gene Expression Data Explorer
Info Gene counts are sourced from ARCHS4, which provides uniform alignment of GEO samples. You can learn more about ARCHS4 and its pipeline here.
Enter gene symbol:

Select conditions below to toggle them from the plot:

GROUP CONDITION SAMPLES
induced pluripotent stem cells-derived cardiomyocytes (iPSC-CMs)
GSM5931373 GSM5931374 GSM5931375 GSM5931376
GSM5931369 GSM5931370 GSM5931371 GSM5931372
GSM5931377 GSM5931378 GSM5931379 GSM5931380
GSM5931365 GSM5931366 GSM5931367 GSM5931368
Description

Submission Date: Mar 03, 2022

Summary: We investigate the effects of GLP-1 on diabetic cardiomyocytes (DCMs) model established by human induced pluripotent stem cells-derived cardiomyocytes (iPSC-CMs). Two subtypes of GLP-1, GLP-17-36 and GLP-19-36, were evaluated for their efficacy on hypertrophic phenotype, impaired calcium homeostasis and electrophysiological properties. RNA-seq was performed to reveal the underlying molecular mechanism of GLP-1. Our results demonstrated that GLP-17-36 and GLP-19-36 were able to ameliorate high glucose-induced hypertrophy phenotype and cardiac dysfunctions in DCM model based on iPSC-CMs. Our study provides a novel platform to unveil the cellular mechanisms of diabetic cardiomyopathy, which sheds light on discovering better targets for novel therapeutic interventions.

GEO Accession ID: GSE197850

PMID: No Pubmed ID

Description

Submission Date: Mar 03, 2022

Summary: We investigate the effects of GLP-1 on diabetic cardiomyocytes (DCMs) model established by human induced pluripotent stem cells-derived cardiomyocytes (iPSC-CMs). Two subtypes of GLP-1, GLP-17-36 and GLP-19-36, were evaluated for their efficacy on hypertrophic phenotype, impaired calcium homeostasis and electrophysiological properties. RNA-seq was performed to reveal the underlying molecular mechanism of GLP-1. Our results demonstrated that GLP-17-36 and GLP-19-36 were able to ameliorate high glucose-induced hypertrophy phenotype and cardiac dysfunctions in DCM model based on iPSC-CMs. Our study provides a novel platform to unveil the cellular mechanisms of diabetic cardiomyopathy, which sheds light on discovering better targets for novel therapeutic interventions.

GEO Accession ID: GSE197850

PMID: No Pubmed ID

Visualize Samples

Info Visualizations are precomputed using the Python package scanpy on the top 5000 most variable genes.

Precomputed Differential Gene Expression

Info Differential expression signatures are automatically computed using the limma R package. More options for differential expression are available to compute below.

Signatures:

Select conditions:

Control Condition

Perturbation Condition

Only conditions with at least 1 replicate are available to select

Differential Gene Expression Analysis
Info Differential expression signatures can be computed using DESeq2 or characteristic direction.
Select differential expression analysis method:
Bulk RNA-seq Appyter

This pipeline enables you to analyze and visualize your bulk RNA sequencing datasets with an array of downstream analysis and visualization tools. The pipeline includes: PCA analysis, Clustergrammer interactive heatmap, library size analysis, differential gene expression analysis, enrichment analysis, and L1000 small molecule search.