Transcriptomic analysis in diabetes patients

Project description: This study focused on generating a transcriptome dataset of omental and subcutaneous adipose tissues collected from patients with gestational diabetes mellitus (GDM) and control subjects. Gestational diabetes is a form of diabetes that occurs during pregnancy and can lead to various health complications for both the mother and the baby. Adipose tissue plays a significant role in the development and progression of GDM due to its involvement in insulin resistance, inflammation, and metabolic dysregulation..

1. Approach

Omental and subcutaneous adipose tissue samples were collected from 32 pregnant women, including 16 GDM patients and 16 matched control subjects. They performed RNA sequencing on the samples and generated a comprehensive transcriptome dataset for both types of adipose tissues in GDM patients and control subjects.

2. Brief summary of results

The dataset provided in the study contains raw sequencing data, gene expression data, and metadata. These data can be used to identify differentially expressed genes (DEGs) and pathways associated with GDM, offering valuable insights into the molecular mechanisms underlying the pathogenesis of GDM in adipose tissues. Additionally, the dataset can be utilized in comparative studies, gene co-expression network analysis, and the identification of potential therapeutic targets for GDM.

3. Brief conclusion

This transcriptome dataset of omental and subcutaneous adipose tissues in gestational diabetes patients represents a valuable resource for researchers studying the molecular basis of GDM and may contribute to the development of new diagnostic and therapeutic approaches for the disease.

For more details see Nature Scientific Data publication.