ReviewDiabetologia2022
Lessons from single-cell RNA sequencing of human islets.
Review in Diabetologia, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed, 32 citations in OpenAlex.
- Cell-specific DNA methylation in human alpha and beta cells regulates gene expression in type 2 diabetes.Nature metabolism · 2026Article
- Molecular diagnostics in pancreas transplantation: past, present, and future.Frontiers in molecular biosciences · 2026Review
- Single-cell virtual knockout network perturbation prioritizes candidate regulators of beta-cell functional failure in type 2 diabetes.Frontiers in endocrinology · 2026Article
- Network-based insights into miRNA regulation of β-cell insulin secretion in type 2 diabetes.iScience · 2025Article
- Single-cell mRNA-regulation analysis reveals cell type-specific mechanisms of type 2 diabetes.Nature communications · 2025Article
- Evaluating cell-specific gene expression using single-cell and single-nuclei RNA-sequencing data from human pancreatic islets of the same donors.Scientific reports · 2025Article
- Preclinical Diagnosis of Type 1 Diabetes: Reality or Utopia.Biomedicines · 2025Review
- Cell-type-specific cis-eQTLs in pancreatic cell types identify novel risk genes for type 2 diabetes.Briefings in bioinformatics · 2025Article
- Interpretable machine learning-guided single-cell mapping deciphers multi-lineage pancreatic dysregulation in type 2 diabetes.Cardiovascular diabetology · 2025Article
- Advancements in diabetes research and stem cell therapy: a concise review.Journal of diabetes and metabolic disorders · 2025Review
- Molecular correlates of glycine receptor activity in human β cells.Molecular metabolism · 2025Article
- Downregulation of NAD Kinase Expression in β-Cells Contributes to the Aging-Associated Decline in Glucose-Stimulated Insulin Secretion.Aging cell · 2025Article
- Transcriptomic heterogeneity of non-beta islet cells is associated with type 2 diabetes development in mouse models.Diabetologia · 2025Article
- Single-cell RNA sequencing in studies of type 1 diabetes mellitus: modern state-of-the-art and technical peculiarities.Frontiers in endocrinology · 2025Review
- Cycling alpha cells in regenerative drug-treated human pancreatic islets may serve as key beta cell progenitors.Cell reports. Medicine · 2024Article
- Article
- Integrating Mendelian randomization and single-cell RNA sequencing to identify therapeutic targets of baicalin for type 2 diabetes mellitus.Frontiers in pharmacology · 2024Article
- Single cell multiomic analysis reveals diabetes-associated β-cell heterogeneity driven by HNF1A.Nature communications · 2023Article
- Deficiency of WTAP in islet beta cells results in beta cell failure and diabetes in mice.Diabetologia · 2023Article
- Type 2 diabetes candidate genes, including PAX5, cause impaired insulin secretion in human pancreatic islets.The Journal of clinical investigation · 2023Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Islet dysfunction is central in type 2 diabetes and full-blown type 2 diabetes develops first when the beta cells lose their ability to secrete adequate amounts of insulin in response to raised plasma glucose. Several mechanisms behind beta cell dysfunction have been put forward but many important questions still remain. Furthermore, our understanding of the contribution of each islet cell type in type 2 diabetes pathophysiology has been limited by technical boundaries. Closing this knowledge gap will lead to a leap forward in our understanding of the islet as an organ and potentially lead to improved treatments. The development of single-cell RNA sequencing (scRNAseq) has led to a breakthrough for characterising the transcriptome of each islet cell type and several important observations on the regulation of cell-type-specific gene expression have been made. When it comes to identifying type 2 diabetes disease mechanisms, the outcome is still limited. Several studies have identified differentially expressed genes, although there is very limited consensus between the studies. As with all new techniques, scRNAseq has limitations; in addition to being extremely expensive, genes expressed at low levels may not be detected, noise may not be appropriately filtered and selection biases for certain cell types are at hand. Furthermore, recent advances suggest that commonly used computational tools may be suboptimal for analysis of scRNAseq data in small-scale studies. Fortunately, development of new computational tools holds promise for harnessing the full potential of scRNAseq data. Here we summarise how scRNAseq has contributed to increasing the understanding of various aspects of islet biology as well as type 2 diabetes disease mechanisms. We also focus on challenges that remain and propose steps to promote the utilisation of the full potential of scRNAseq in this area.
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