Bioinformatics Analysis of Next Generation Sequencing Data Identifies Molecular Biomarkers Associated With Type 2 Diabetes Mellitus.

IF 2.7 Q3 ENDOCRINOLOGY & METABOLISM Clinical Medicine Insights-Endocrinology and Diabetes Pub Date : 2023-02-20 eCollection Date: 2023-01-01 DOI:10.1177/11795514231155635

Varun Alur, Varshita Raju, Basavaraj Vastrad, Chanabasayya Vastrad, Satish Kavatagimath, Shivakumar Kotturshetti

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Abstract

Background: Type 2 diabetes mellitus (T2DM) is the most common metabolic disorder. The aim of the present investigation was to identify gene signature specific to T2DM.

Methods: The next generation sequencing (NGS) dataset GSE81608 was retrieved from the gene expression omnibus (GEO) database and analyzed to identify the differentially expressed genes (DEGs) between T2DM and normal controls. Then, Gene Ontology (GO) and pathway enrichment analysis, protein-protein interaction (PPI) network, modules, miRNA (micro RNA)-hub gene regulatory network construction and TF (transcription factor)-hub gene regulatory network construction, and topological analysis were performed. Receiver operating characteristic curve (ROC) analysis was also performed to verify the prognostic value of hub genes.

Results: A total of 927 DEGs (461 were up regulated and 466 down regulated genes) were identified in T2DM. GO and REACTOME results showed that DEGs mainly enriched in protein metabolic process, establishment of localization, metabolism of proteins, and metabolism. The top centrality hub genes APP, MYH9, TCTN2, USP7, SYNPO, GRB2, HSP90AB1, UBC, HSPA5, and SQSTM1 were screened out as the critical genes. ROC analysis provides prognostic value of hub genes.

Conclusion: The potential crucial genes, especially APP, MYH9, TCTN2, USP7, SYNPO, GRB2, HSP90AB1, UBC, HSPA5, and SQSTM1, might be linked with risk of T2DM. Our study provided novel insights of T2DM into genetics, molecular pathogenesis, and novel therapeutic targets.

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下一代测序数据的生物信息学分析确定了与 2 型糖尿病相关的分子生物标记物。

背景：2 型糖尿病（T2DM）是最常见的代谢性疾病。本研究旨在确定 T2DM 的特异性基因特征：方法：从基因表达总括（GEO）数据库中检索并分析了新一代测序（NGS）数据集 GSE81608，以确定 T2DM 和正常对照之间的差异表达基因（DEGs）。然后进行了基因本体（GO）和通路富集分析、蛋白-蛋白相互作用（PPI）网络、模块、miRNA（微 RNA）-中枢基因调控网络构建、TF（转录因子）-中枢基因调控网络构建和拓扑分析。同时还进行了接收者操作特征曲线（ROC）分析，以验证枢纽基因的预后价值：结果：在 T2DM 中总共发现了 927 个 DEGs（461 个上调基因和 466 个下调基因）。GO和REACTOME结果显示，DEGs主要富集于蛋白质代谢过程、定位的建立、蛋白质的代谢和新陈代谢。其中，APP、MYH9、TCTN2、USP7、SYNPO、GRB2、HSP90AB1、UBC、HSPA5和SQSTM1被筛选为关键基因。ROC分析提供了枢纽基因的预后价值：结论：潜在的关键基因，尤其是 APP、MYH9、TCTN2、USP7、SYNPO、GRB2、HSP90AB1、UBC、HSPA5 和 SQSTM1，可能与 T2DM 风险有关。我们的研究为 T2DM 的遗传学、分子发病机制和新的治疗靶点提供了新的见解。

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