ArticlePhenomics (Cham, Switzerland)2021
Pseudotime Ordering Single-Cell Transcriptomic of β Cells Pancreatic Islets in Health and Type 2 Diabetes.
Article in Phenomics (Cham, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 9 citations in OpenAlex.
- Multi-omics analyses related to unfolded protein response in prostate cancer implicate pro-tumor role of IFRD1.Frontiers in immunology · 2026Article
- Stress-driven remodeling of antigen presentation and chemokine signaling in pancreatic β-cells: implications for type 1 diabetes.Frontiers in immunology · 2026Review
- Multi-Omics Exploration of Obesity Biomarkers in Sedentary and Weight Loss Cohorts.Phenomics (Cham, Switzerland) · 2025Article
- Trajectory Inference for Single Cell Omics.ArXiv · 2025Article
- snRNA-seq of human ovaries reveals heat shock proteins are associated with obesity related cancer risk.Journal of translational medicine · 2024Article
- New Insights and Potential Therapeutic Interventions in Metabolic Diseases.International journal of molecular sciences · 2023Review
- Plasma Metabolomics Reveals β-Glucan Improves Muscle Strength and Exercise Capacity in Athletes.Metabolites · 2022Article
- Article
- Increased DNA Polymerase Epsilon Catalytic Subunit Expression Predicts Tumor Progression and Modulates Tumor Microenvironment of Hepatocellular Carcinoma.Journal of Cancer · 2022Article
Corrections and comments
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Authors and funding
7 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
β cells are defined by the ability to produce and secret insulin. Recent studies have evaluated that human pancreatic β cells are heterogeneous and demonstrated the transcript alterations of β cell subpopulation in diabetes. Single-cell RNA sequence (scRNA-seq) analysis helps us to refine the cell types signatures and understand the role of the β cells during metabolic challenges and diseases. Here, we construct the pseudotime trajectory of β cells from publicly available scRNA-seq data in health and type 2 diabetes (T2D) based on highly dispersed and highly expressed genes using Monocle2. We identified three major states including 1) Normal branch, 2) Obesity-like branch and 3) T2D-like branch based on biomarker genes and genes that give rise to bifurcation in the trajectory. β cell function-maintain-related genes, insulin expression-related genes, and T2D-related genes enriched in three branches, respectively. Continuous pseudotime spectrum might suggest that β cells transition among different states. The application of pseudotime analysis is conducted to clarify the different cell states, providing novel insights into the pathology of β cells in T2D. Supplementary Information: The online version contains supplementary material is available at 10.1007/s43657-021-00024-z.
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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 OpenQuestion graph.