{"title":"A Complex Network of Obesity-Risk Genes Revealed by Systematic Bioinformatics and Single-Cell Transcriptomic Analyses.","authors":"Yuenan Liu, Haolin Yuan, Junhui Hu, Xu Xu, Shankai Yin, Yiming Hu, Feng Liu","doi":"10.1155/jobe/7821115","DOIUrl":null,"url":null,"abstract":"<p><p>The development of obesity is closely linked to genetic factors. Despite the identification of numerous genes associated with an increased risk of obesity in humans, a comprehensive understanding of their biological roles has not been achieved. In our extensive bioinformatics study, we identified 802 core genes implicated in obesity. Our protein-protein interaction (PPI) network analysis revealed that these genes form a tightly connected functional network primarily involved in neurological and metabolic regulatory processes. Moreover, our in-depth analysis of single-cell transcriptomic datasets from the human hypothalamus, pancreatic islets, adipose tissue, and liver has shed light on the distinct expression profiles of these obesity-linked genes across various tissue and cell types. This analysis also highlighted the biological processes they influence and the upstream transcriptional regulatory networks involved. Our study not only uncovers the complicated regulatory role of genetic factors in the pathogenesis and progression of obesity but also establishes a close link between the expression patterns and functional roles of these obesity-associated genes. This study provides crucial insights for advancing our understanding of the genetic mechanisms underlying obesity.</p>","PeriodicalId":16628,"journal":{"name":"Journal of Obesity","volume":"2025 ","pages":"7821115"},"PeriodicalIF":3.8000,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11976034/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Obesity","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1155/jobe/7821115","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"ENDOCRINOLOGY & METABOLISM","Score":null,"Total":0}
引用次数: 0
Abstract
The development of obesity is closely linked to genetic factors. Despite the identification of numerous genes associated with an increased risk of obesity in humans, a comprehensive understanding of their biological roles has not been achieved. In our extensive bioinformatics study, we identified 802 core genes implicated in obesity. Our protein-protein interaction (PPI) network analysis revealed that these genes form a tightly connected functional network primarily involved in neurological and metabolic regulatory processes. Moreover, our in-depth analysis of single-cell transcriptomic datasets from the human hypothalamus, pancreatic islets, adipose tissue, and liver has shed light on the distinct expression profiles of these obesity-linked genes across various tissue and cell types. This analysis also highlighted the biological processes they influence and the upstream transcriptional regulatory networks involved. Our study not only uncovers the complicated regulatory role of genetic factors in the pathogenesis and progression of obesity but also establishes a close link between the expression patterns and functional roles of these obesity-associated genes. This study provides crucial insights for advancing our understanding of the genetic mechanisms underlying obesity.
期刊介绍:
Journal of Obesity is a peer-reviewed, Open Access journal that provides a multidisciplinary forum for basic and clinical research as well as applied studies in the areas of adipocyte biology & physiology, lipid metabolism, metabolic syndrome, diabetes, paediatric obesity, genetics, behavioural epidemiology, nutrition & eating disorders, exercise & human physiology, weight control and health risks associated with obesity.