GEO series
Deciphering the Transcriptomic Landscape of Type 2 Diabetes: Insights from Bulk RNA Sequencing and Single-Cell Analysis [RNA-seq]
GSE280402
Homo sapiens
Expression profiling by high throughput sequencing
16 samples
2024/10/30
GPL16791
Summary
Type 2 diabetes (T2D) is a chronic metabolic disorder characterized by insulin resistance and relative insulin deficiency. It is a significant public health concern worldwide, with an estimated prevalence of over 422 million individuals affected globally. This number is projected to rise, making diabetes one of the leading causes of morbidity and mortality. It is associated with numerous severe microvascular and macrovascular complications, including retinopathy, nephropathy, cardiovascular diseases, and neuropathy, which substantially impact patients' quality of life and healthcare systems. The global prevalence of T2D necessitates a deeper understanding of its underlying mechanisms to develop more effective prevention and treatment strategies. Recent advancements in transcriptomics and single-cell technologies have revolutionized our ability to investigate the cellular and molecular landscapes of T2DM. Transcriptomic analysis provides insights into gene expression patterns in T2D, revealing pathways involved in insulin signaling, metabolic regulation, and inflammation. The importance of inflammation driven by immune cells in the pathogenesis of T2D has been repeatedly demonstrated. This makes research focused on the analysis of gene expression in whole blood cells especially relevant. Transcriptomic markers of T2D have been investigated in studies utilizing expression arrays and RNA-seq. While expression arrays allow for the analysis of a gene set limited by the design of microarrays, RNA-seq allows investigating the entire transcriptome. A study focused on the analysis of transcriptomic markers of T2D in whole blood using RNA-seq demonstrated differential expression of genes associated with inflammation, insulin resistance, and mitochondrial dysfunction. However, the heterogeneity of immune cell populations poses significant challenges in understanding the disease's complexity. Single-cell RNA sequencing (scRNA-seq) enables researchers to dissect this cellular diversity, allowing for the identification of distinct cell types and their specific contributions to T2DM progression. By integrating transcriptomic data with single-cell analyses, we can elucidate the dynamic interactions between various cell types and their roles in T2DM. In this study, we aimed to analyze transcriptomic markers of T2D in whole blood cells and conduct single-cell sequencing on isolated PBMCs from T2D patients and healthy controls in order to advance our understanding of the processes involved in the pathogenesis of T2D and to highlight the significance of transcriptomic and single-cell research in T2D studies.
Download
NCBI GEO page ↗
Paper (PMID 41465472) ↗
{# Names what the click gives you. "Open in finder" meant nothing to a
visitor who arrived from a search engine and has never seen the tool. #}
Find more
human RNA-seq datasets →
Similar datasets
- GSE328275 Single-cell RNA sequencing of CD45+ immune cells across primary tumor, sentinel tumor-draining lymph node, and axillary lymph node in treatment-naive triple-negative breast cancer 28 samples
- GSE341753 Cohesin loading at regulatory elements shapes 3D genome folding during erythropoiesis [RNA-Seq] 12 samples
- GSE319969 Spatial and Bulk Transcriptomic Profiling Defines the Molecular Evolution of Cutaneous Squamous Cell Carcinoma and Reveals Stage-Specific Biomarkers of Clinical Relevance [RNA-Seq] 24 samples
- GSE342462 Integrated transcriptomic and bioelectrical profiling of stem-like cellular states in a colorectal cancer using SdFFF and UHF-DEP 12 samples
- GSE313035 METIMMOX: Colorectal Cancer METastasis - Shaping Anti-tumor IMMunity by OXaliplatin 67 samples
- GSE341139 A conserved HAND2-BMP5-SMAD1/5/9 axis drives hepatic stellate cell activation and extracellular matrix overproduction in multiple fibrotic etiologies 10 samples
- GSE274275 Effect of depletion of NSUN4 on gene expression of NCI-H226 cells [RNA-seq] 6 samples
- GSE339456 Integrated bulk and spatial transcriptomic analysis identifies progression-associated molecular signatures in biopsy-proven hypertensive nephropathy [RNA-seq] 35 samples
Share this dataset
Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.