Endocrine Division, Hospital de Clínicas de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil; Postgraduation Program in Medical Sciences: Endocrinology, Faculdade de Medicina, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil.
Endocrine Division, Hospital de Clínicas de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil; Postgraduation Program in Medical Sciences: Endocrinology, Faculdade de Medicina, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil.
Gene. 2022 Jul 1;830:146512. doi: 10.1016/j.gene.2022.146512. Epub 2022 Apr 18.
Childhood obesity is triggered by a complex interplay of environmental, genetic, and epigenetic factors; however, the molecular mechanisms behind this disease are not completely elucidated. Thus, the aim of this study was to investigate molecular mechanisms involved in childhood obesity by implementing a systems biology approach.
Experimentally validated and computationally predicted genes related to childhood obesity were downloaded from DisGeNET database. A protein-protein interaction (PPI) network was constructed using the STRING database and analyzed at Cytoscape web-tool. Hub-bottleneck genes and functional clusters were identified through CytoHubba and MCODE plugins, respectively. Functional enrichment analyses were performed based on Gene Ontology terms and KEGG Pathways.
The DisGeNET search retrieved 191 childhood obesity-related genes. The resulting PPI network contained 12 hub-bottleneck genes (INS, LEP, STAT3, POMC, ALB, TNF, BDNF, CAT, GCG, PPARG, VEGFA, and ADIPOQ) and 4 functional clusters, with cluster 1 showing the highest interaction score. Genes at this cluster were enriched at inflammation, carbohydrate, and lipid metabolism pathways. With exception of POMC, all hub-bottleneck genes were found in cluster 1, which contains highly connected genes that possibly play key roles in obesity-related pathways.
Our systems biology approach revealed a set of highly interconnected genes associated with childhood obesity, providing comprehensive information regarding genetic and molecular factors involved in the pathogenesis of this disease.
儿童肥胖是由环境、遗传和表观遗传因素复杂相互作用引发的；然而，这种疾病的分子机制尚未完全阐明。因此，本研究旨在通过实施系统生物学方法来研究儿童肥胖相关的分子机制。
从 DisGeNET 数据库中下载了与儿童肥胖相关的经过实验验证和计算预测的基因。使用 STRING 数据库构建蛋白质-蛋白质相互作用（PPI）网络，并在 Cytoscape 网络工具中进行分析。使用 CytoHubba 和 MCODE 插件分别识别枢纽-瓶颈基因和功能簇。基于基因本体论术语和 KEGG 通路进行功能富集分析。
DisGeNET 搜索检索到 191 个与儿童肥胖相关的基因。生成的 PPI 网络包含 12 个枢纽-瓶颈基因（INS、LEP、STAT3、POMC、ALB、TNF、BDNF、CAT、GCG、PPARG、VEGFA 和 ADIPOQ）和 4 个功能簇，其中簇 1 的相互作用得分最高。该簇中的基因富集在炎症、碳水化合物和脂质代谢途径中。除了 POMC 之外，所有的枢纽-瓶颈基因都存在于簇 1 中，簇 1 包含高度连接的基因，这些基因可能在肥胖相关途径中发挥关键作用。
我们的系统生物学方法揭示了一组与儿童肥胖相关的高度相互关联的基因，为该疾病发病机制中涉及的遗传和分子因素提供了全面的信息。
