Key result
Integrated bioinformatics analysis of NGS data identified 872 differentially expressed genes and 10 hub genes as potential diagnostic and prognostic biomarkers for diabetes and obesity.
Why the study?
Diabetes and obesity represent metabolic disorders, and the study aimed to elucidate potential biomarkers and prognostic targets in affected subjects.
Integrated bioinformatics analysis identified ten hub genes that could serve as potential diagnostic and prognostic biomarkers for subjects with diabetes and obesity.
Bioinformatics analysis nominates candidate biomarkers in diabetic obesity; leaves open clinical utility pending prospective validation.
Background and Objectives: A subject with diabetes and obesity is a class of the metabolic disorder. The current investigation aimed to elucidate the potential biomarker and prognostic targets in subjects with diabetes and obesity. Materials and Methods: The next-generation sequencing (NGS) data of GSE132831 was downloaded from Gene Expression Omnibus (GEO) database. Functional enrichment analysis of DEGs was conducted with ToppGene. The protein–protein interactions network, module analysis, target gene–miRNA regulatory network and target gene–TF regulatory network were constructed and analyzed. Furthermore, hub genes were validated by receiver operating characteristic (ROC) analysis. A total of 872 DEGs, including 439 up-regulated genes and 433 down-regulated genes were observed. Results: Second, functional enrichment analysis showed that these DEGs are mainly involved in the axon guidance, neutrophil degranulation, plasma membrane bounded cell projection organization and cell activation. The top ten hub genes (MYH9, FLNA, DCTN1, CLTC, ERBB2, TCF4, VIM, LRRK2, IFI16 and CAV1) could be utilized as potential diagnostic indicators for subjects with diabetes and obesity. The hub genes were validated in subjects with diabetes and obesity. Conclusion: This investigation found effective and reliable molecular biomarkers for diagnosis and prognosis by integrated bioinformatics analysis, suggesting new and key therapeutic targets for subjects with diabetes and obesity.
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Ganekal et al. (2023) studied Diabetes and obesity. Next-generation sequencing data analysis was evaluated on Differentially expressed genes (DEGs) and hub genes. Integrated bioinformatics analysis of NGS data identified 872 differentially expressed genes and 10 hub genes as potential diagnostic and prognostic biomarkers for diabetes and obesity.
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