Dataset Information

Deciphering the Transcriptomic Landscape of Type 2 Diabetes: Insights from Bulk RNA Sequencing and Single-Cell Analysis [RNA-seq]

ABSTRACT: 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.

ORGANISM(S): Homo sapiens

PROVIDER: GSE280402 | GEO | 2024/10/30

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description: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.

Project description:Physical inactivity and western diet are the main factors leading to skeletal muscle (and whole-body) insulin resistance – a defect in insulin-mediated glucose uptake and metabolism – and associated metabolic diseases, such as obesity and type 2 diabetes mellitus (T2D). The study of the response to a mixed meal (normalized for body mass and/or basal metabolic rate) is of particular interest, as it simulates the physiological response to a typical (daily) single meal that depends on both the secretory function of the beta cells (insulin response) and the sensitivity of skeletal muscle signaling to insulin – variables, which markedly changing during development of insulin resistance and T2D. We aimed to compare the early transcriptomic response to a mixed meal normalized to body mass in skeletal muscle of healthy subjects and obese patients without (Ob) and with T2D (Ob+T2D). To investigate the early transcriptomic response we took biopsy samples from the vastus lateralis muscle prior to and 1 h after a meal. In the Ob+T2D group the average level and increase in C-peptide and insulin in the blood were comparable with healthy subjects that, apparently, is explained by dysfunction of the beta-cells induced by chronic T2D. At the same time, the Ob+T2D group demonstrated dysregulation of mixed meal-induced gene expression in skeletal muscle: morу than two times lower number of DEGs and a small overlapping with the gene response in the control group. On the contrary, the postprandial level of C-peptide and insulin in the Ob group was significantly greater than in healthy control that is related to insulin oversecretion associated with insulin resistance. Despite this, the gene response in skeletal muscle was also significantly dysregulated; moreover, it differed from the response in the Ob+T2D group. It means that defect in regulation of insulin-induced gene expression (insulin resistance in terms of gene expression) appears at the first stage of the development of metabolic disorders.

Dataset Information

Deciphering the Transcriptomic Landscape of Type 2 Diabetes: Insights from Bulk RNA Sequencing and Single-Cell Analysis [RNA-seq]

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets