南方医科大学学报2024，Vol.44Issue(5)：920-929,10.DOI:10.12122/j.issn.1673-4254.2024.05.14
基于硬皮病线粒体相关基因的人工神经网络模型的构建
An artificial neural network diagnostic model for scleroderma and immune cell infiltration analysis based on mitochondria-associated genes
摘要
Abstract
Objective To establish a diagnostic model for scleroderma by combining machine learning and artificial neural network based on mitochondria-related genes.Methods The GSE95065 and GSE59785 datasets of scleroderma from GEO database were used for analyzing expressions of mitochondria-related genes,and the differential genes were identified by Random forest,LASSO regression and SVM algorithms.Based on these differential genes,an artificial neural network model was constructed,and its diagnostic accuracy was evaluated by 10-fold crossover verification and ROC curve analysis using the verification dataset GSE76807.The mRNA expressions of the key genes were verified by RT-qPCR in a mouse model of scleroderma.The CIBERSORT algorithm was used to estimate the bioinformatic association between scleroderma and the screened biomarkers.Results A total of 24 differential genes were obtained,including 11 up-regulated and 13 down-regulated genes.Seven most relevant mitochondria-related genes(POLB,GSR,KRAS,NT5DC2,NOX4,IGF1,and TGM2)were screened using 3 machine learning algorithms,and the artificial neural network diagnostic model was constructed.The model showed an area under the ROC curves of 0.984 for scleroderma diagnosis(0.740 for the verification dataset and 0.980 for cross-over validation).RT-qPCR detected significant up-regulation of POLB,GSR,KRAS,NOX4,IGF1 and TGM2 mRNAs and significant down-regulation of NT5DC2 in the mouse models of scleroderma.Immune cell infiltration analysis showed that the differential genes in scleroderma were associated with follicular helper T cells,immature B cells,resting dendritic cells,memory activated CD4+T cells,M0 macrophages,monocytes,resting memory CD4+T cells and mast cell activation.Conclusion The artificial neural network diagnostic model for scleroderma established in this study provides a new perspective for exploring the pathogenesis of scleroderma.关键词
硬皮病/线粒体/人工神经网络/免疫细胞浸润/机器学习Key words
scleroderma/mitochondria/artificial neural network/immune cell infiltration/machine learning引用本文复制引用
左志威,孟庆良,崔家康,郭克磊,卞华..基于硬皮病线粒体相关基因的人工神经网络模型的构建[J].南方医科大学学报,2024,44(5):920-929,10.基金项目
国家自然科学基金(82074415) （82074415）
中原英才计划-中原科技创新领军人才项目(234200510006) （234200510006）
河南省科技计划项目(232102311201) Supported by National Natural Science Foundation of China(82074415). （232102311201）
