ArticleNature communications2025
Single-cell mRNA-regulation analysis reveals cell type-specific mechanisms of type 2 diabetes.
Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Cross-ancestry analysis of gestational diabetes mellitus identifies novel loci, drug targets and biological pathways.Frontiers in endocrinology · 2026Pooled it
- Mitochondrial Dysfunction: From Molecular Mechanisms to Modern Approaches for Basic and Clinical Research.Biomedicines · 2026Review
- Pancreatic β-cell aging in physiology and diabetes: emerging roles of m6A mRNA methylation.Journal of molecular endocrinology · 2026Review
- Cell-specific DNA methylation in human alpha and beta cells regulates gene expression in type 2 diabetes.Nature metabolism · 2026Article
- Identifying patterns differing between high-dimensional datasets with generalized contrastive PCA.PLoS computational biology · 2025Article
- Identifying patterns differing between high-dimensional datasets with generalized contrastive PCA.bioRxiv : the preprint server for biology · 2024Article
- Article
Corrections and comments
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Authors and funding
25 authors.
Funding
Abstract
Perturbed secretion of insulin and other pancreatic islet hormones is the main cause of type 2 diabetes (T2D). The islets harbor five cell types that are potentially altered differently by T2D. Whole-islet transcriptomics and single-cell RNA-sequencing (scRNAseq) studies have revealed differentially expressed genes without reaching consensus. Here, we demonstrate that further insights into T2D disease mechanisms can be obtained by network-based analysis of scRNAseq data from individual cell types. We developed differential gene coordination network analysis (dGCNA) and analyzed islet SmartSeq2 scRNAseq data from 16 T2D and 16 non-T2D individuals. dGCNA reveals T2D-induced cell type-specific networks of dysregulated genes with remarkable ontological specificity, thus allowing for a comprehensive and unbiased functional classification of genes involved in T2D. In beta cells eleven networks of genes are detected, revealing that mitochondrial electron transport chain, glycolysis, cytoskeleton organization, cell proliferation, unfolded protein response and three networks of beta cell transcription factors are perturbed, whereas exocytosis, lysosomal regulation and insulin translation programs are instead enhanced in T2D. Furthermore, we validated the ability of dGCNA to reveal disease mechanisms and predict the functional context of genes by showing that TMEM176A/B regulates beta cell microfilament organization and that CEPBG is an important regulator of the unfolded protein response. In addition, when comparing beta- and alpha cells, we found substantial differences, reproduced across independent datasets, confirming cell type-specific alterations in T2D. We conclude that analysis of networks of differentially coordinated genes provides detailed insight into cell type-specific gene function and T2D pathophysiology.
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Registered trials
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.