Diabesity: New Candidate Genes and Structural and Functional Effects of Non-Synonymous Single Nucleotide Polymorphisms Identified by Computational Biology.

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Tác giả: Riitvek Baddireddi, Lakshmiganesh Kadumbur Gopalshami, Naveenn Kumar, Baddireddi Subhadra Lakshmi, Karthiga Selvaraj, Kothai Thiruvengadam

Ngôn ngữ: eng

Ký hiệu phân loại: 620.37 Effects and countermeasures

Thông tin xuất bản: United States : Omics : a journal of integrative biology , 2025

Mô tả vật lý:

Bộ sưu tập: NCBI

ID: 12265

Diabesity is a comorbidity of type 2 diabetes mellitus and obesity. Diabesity is a major global epidemic and a veritable planetary health burden. With diabesity, several clinical signs are present such as excess accumulation of fat, altered lipid metabolism, chronic inflammation, insulin resistance, disordered pancreatic β-cell metabolism, and hyperglycemia. We report here new potential candidate genes for diabesity, and the structural and functional effects of non-synonymous single nucleotide polymorphisms (nsSNPs) in these genes using a computational biology approach. A protein-protein interaction (PPI) network was constructed using Human Integrated Protein-Protein Interaction rEference (HIPPIE') data for 186 diabesity-associated genes from the Disease Gene Network (DisGeNET). Subsequently, the top 2% of nine centrality-ranked genes were identified as hub genes. Gene ontology enrichment analysis was performed with the same gene list using the Gene Ontology enRIchment anaLysis and visuaLizAtion (GORILLA) tool, and importantly, 63 enriched hub genes with no prior disease association were selected and their differential expressions in adipose, skeletal, and hepatic tissues were analyzed using Gene Expression Omnibus (GEO) profiles. Finally, the nsSNPs in the top five prioritized genes (
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