| Issue |
BIO Web Conf.
Volume 172, 2025
International Conference on Nurturing Innovative Technological Trends in Engineering – BIOscience (NITTE-BIO 2025)
|
|
|---|---|---|
| Article Number | 04002 | |
| Number of page(s) | 9 | |
| Section | Pharmaceutical Biotechnology | |
| DOI | https://doi.org/10.1051/bioconf/202517204002 | |
| Published online | 10 April 2025 | |
Comparative analysis of gene expression in Diabetic vs Non-Diabetic Obese individuals
Department of Biotechnology, K. S. Rangasamy College of Technology, Tiruchengode, Tamil Nadu, India.
* Corresponding author: durgamurugan433@gmail.com
Diabetes and obesity are closely interconnected epidemics with shared and distinct molecular mechanisms. In this analysis, a comparative gene expression study was carried out among diabetic and non-diabetic obese patients using Gene Expression Omnibus dataset (GSE132831), containing 104 diabetic and 120 non-diabetic obese Patients. Differential Expressed Genes were identified, which results of 509 upregulated genes and 33,885 downregulated genes. Further Gene Ontology terms, such as Biological Process, Cellular Component and Molecular Function were analysed. Visualization of Differential Expressed Genes and pathway enrichment analysis indicated significant associations with metabolic and immune signaling pathways, and fold enrichment Analyses highlighted critical differences in gene activity between the two groups. Protein-Protein Interaction Network is generated, which showed highly connected clusters. These clusters identified the target genes Transmembrane Immune Signaling Adapter Protein (TYROBP) and Receptor for Activated C Kinase (RACK1) with their respective networks. These were considered potential targets for treatment because of the central Positions they occupy in metabolic and immune regulatory pathways associated with diabetic obesity.
Key words: Gene Expression Omnibus / Diabetes / Obesity / Differential Expressed Genes / Protein-Protein Interaction / Gene Ontology / Clusters
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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