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.
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GROUP CONDITION SAMPLES
human islets
GSM5494795 GSM5494796 GSM5494797
GSM5494798 GSM5494799 GSM5494800
Description

Submission Date: Aug 02, 2021

Summary: Currently, no oral medications are available for individuals suffering from type 1 diabetes (T1D). Our randomized placebo-controlled phase 2 trial recently revealed that oral verapamil has short- term beneficial effects in subjects with new-onset type 1 diabetes (T1D) 1. However, what exact biological changes verapamil elicits in humans with T1D, how long they may last, and how to best monitor any associated therapeutic success has remained elusive. We therefore now conducted extended analyses of the effects of continuous verapamil use over a 2-year period, performed unbiased proteomics analysis of serum samples and assessed changes in proinflammatory T-cell markers in subjects receiving verapamil or just standard insulin therapy. In addition, we determined the verapamil-induced changes in human islets using RNA sequencing. Our present results reveal that verapamil regulates the thioredoxin system and promotes an anti-oxidative and anti-apoptotic gene expression profile in human islets, reverses T1D-induced elevations in circulating proinflammatory T-follicular-helper cells and interleukin-21 and normalizes serum levels of chromogranin A (CHGA), a recently identified T1D autoantigen 2,3. In fact, proteomics identified CHGA as the top serum protein altered by verapamil and as a potential therapeutic marker. Moreover, continuous use of oral verapamil delayed T1D progression, promoted endogenous beta cell function and lowered insulin requirements and serum CHGA levels for at least 2 years and these benefits were lost upon discontinuation. Thus, the current studies provide crucial mechanistic and clinical insight into the beneficial effects of verapamil in T1D.

GEO Accession ID: GSE181328

PMID: 35241690

Description

Submission Date: Aug 02, 2021

Summary: Currently, no oral medications are available for individuals suffering from type 1 diabetes (T1D). Our randomized placebo-controlled phase 2 trial recently revealed that oral verapamil has short- term beneficial effects in subjects with new-onset type 1 diabetes (T1D) 1. However, what exact biological changes verapamil elicits in humans with T1D, how long they may last, and how to best monitor any associated therapeutic success has remained elusive. We therefore now conducted extended analyses of the effects of continuous verapamil use over a 2-year period, performed unbiased proteomics analysis of serum samples and assessed changes in proinflammatory T-cell markers in subjects receiving verapamil or just standard insulin therapy. In addition, we determined the verapamil-induced changes in human islets using RNA sequencing. Our present results reveal that verapamil regulates the thioredoxin system and promotes an anti-oxidative and anti-apoptotic gene expression profile in human islets, reverses T1D-induced elevations in circulating proinflammatory T-follicular-helper cells and interleukin-21 and normalizes serum levels of chromogranin A (CHGA), a recently identified T1D autoantigen 2,3. In fact, proteomics identified CHGA as the top serum protein altered by verapamil and as a potential therapeutic marker. Moreover, continuous use of oral verapamil delayed T1D progression, promoted endogenous beta cell function and lowered insulin requirements and serum CHGA levels for at least 2 years and these benefits were lost upon discontinuation. Thus, the current studies provide crucial mechanistic and clinical insight into the beneficial effects of verapamil in T1D.

GEO Accession ID: GSE181328

PMID: 35241690

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:

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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.
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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.