基于机器学习的强直性脊柱炎免疫相关基因鉴定

周若舟; 胡昕; 范瑜; 房佐忠; 田健; 邓国兵

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湖南师范大学学报医学版 ›› 2023, Vol. 20 ›› Issue (2) : 54-62.

临床医学

基于机器学习的强直性脊柱炎免疫相关基因鉴定

周若舟¹, 胡昕¹, 范瑜¹, 房佐忠¹, 田健², 邓国兵¹

作者信息 +

Identification of immune related genes in ankylosing spondylitis based on machine learning

ZHOU Ruozhou¹, HU Xin¹, FAN Yu¹, FANG Zuozhong¹, TIAN Jian², DENG Guobing¹

Author information +

文章历史 +

摘要

目的：探索免疫相关的特征基因在强直性脊柱（ankylosing spondylitis,AS）的诊断价值及其分子机制。方法：从GEO数据库下载GSE73756和GSE25101数据集,联合加权基因过表达网络（WGCNA）与最小绝对值收敛选择算子（LASSO）和支持向量机-递归特征消除（SVM - RFE）筛选特征基因,并评估其在AS中的诊断价值,并进行功能及通路富集分析等生物信息学分析。结果：共鉴定出5个关键免疫相关基因：CD81、IL2RB、CSF3R、IL8、CCL3L3。5个基因联合构建的诊断模型在训练集和测试集中都具有较高的诊断价值。结论：CD81、IL2RB、CSF3R、IL8、CCL3L3可能成为AS的诊断生物学标志及潜在治疗靶点。

Abstract

Objective To explore the diagnostic value and molecular mechanism of immune related characteristic genes in ankylosing spondylitis (AS). Methods Download the GSE73756 and GSE25101 datasets from the Gene Expression Omnibus (GEO) database. Combined the weighted gene overexpression network (WGCNA) and the Least absolute shrinkage and selection operator, LASSO) and the Support Vector Machine-recursive feature elimination (SVM-RFE) to screen characteristic genes and evaluate their diagnostic value in AS. Bioinformatics analysis such as functional and pathway enrichment analysis was performed. Results Finally, a total of 5 key immune related genes were identified: CD81, IL2RB, CSF3R, IL8, and CCL3L3. The diagnostic model constructed by the combination of five genes has high diagnostic value in both the training set and the test set. Conclusion CD81, IL2RB, CSF3R, IL8 and CCL3L3 may be the diagnostic biomarkers and potential therapeutic targets of AS.

导出引用

周若舟, 胡昕, 范瑜, 房佐忠, 田健, 邓国兵. 基于机器学习的强直性脊柱炎免疫相关基因鉴定[J]. 湖南师范大学学报医学版. 2023, 20(2): 54-62

ZHOU Ruozhou, HU Xin, FAN Yu, FANG Zuozhong, TIAN Jian, DENG Guobing. Identification of immune related genes in ankylosing spondylitis based on machine learning[J]. Journal of Hunan Normal University(Medical Science). 2023, 20(2): 54-62

中图分类号： R681.5

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