华西口腔医学杂志2024，Vol.42Issue(6)：735-747,13.DOI:10.7518/hxkq.2024.2024214
基于机器学习和生物信息学分析的脂肪酸代谢相关基因在牙周炎中的作用研究
Role of fatty acid metabolism-related genes in periodontitis based on machine learning and bioinformatics analysis
摘要
Abstract
Objective This study aims to investigate the role of genes related to fatty acid metabolism in periodon-titis through machine learning and bioinformatics methods.Methods Periodontitis datasets GSE10334 and GSE-16134 were downloaded from the GEO database,and the fatty acid metabolism-related gene sets were obtained from the GeneCards database.Differentially expressed fatty acid metabolism-related genes(DEFAMRGs)in periodontitis were screened using the"limma"R package.Functional enrichment and pathway analyses were conducted.Recursive Feature Elimination,Least Absolute Shrinkage and Selection Operator,and Boruta algorithm were used to determine hub DEFAMRGs and construct diagnostic models with internal and external validation.Subtypes of periodontitis relat-ed to hub DEFAMRGs were constructed using consis-tency clustering analysis.CIBERSORT was used to ana-lyze immune cell infiltration in gingival tissues and ex-plore the correlation between hub DEFAMRGs and im-mune cells.Results A total of 113 periodontitis DE-FAMRGs were screened out as a result.The enrichment analysis results indicate that DEFAMRGs are mainly associat-ed with immune inflammatory responses and immune cell chemotaxis.Finally,8 hub DEFAMRGs(BTG2,CXCL12,FABP4,CLDN10,PPBP,RGS1,LGALSL,and RIF1)were identified and a diagnostic model(AUC=0.967)was con-structed,based on which periodontitis was divided into two subtypes.In addition,there is a significant correlation be-tween hub DEFAMRGs and different immune cell populations,with mast cells and dendritic cells showing higher cor-relation.Conclusion This study provides new insights and ideas for the occurrence and development mechanism of periodontitis and proposes a diagnostic model based on hub DEFAMRGs to provide new directions for diagnosis and treatment.关键词
牙周炎/脂肪酸代谢/生物信息学/机器学习/免疫浸润Key words
periodontitis/fatty acid metabolism/bioinformatics/machine learning/immune infiltration分类
医药卫生引用本文复制引用
陈宇翔,赵安娜,杨浩然,杨霞,程婷婷,饶先琦,李自良..基于机器学习和生物信息学分析的脂肪酸代谢相关基因在牙周炎中的作用研究[J].华西口腔医学杂志,2024,42(6):735-747,13.基金项目
National Natural Science Foundation of China(82360185) 国家自然科学基金(82360185) （82360185）
