| 引用本文: | 肖剑伟,蔡旭,郭粉莲,陈新鹏,洪易炜,叶志中.基于机器学习识别干燥综合征发病相关长链非编码RNA[J].生物信息学,2023,21(2):146-154. |
| XIAO Jianwei,CAI Xu,GUO Fenlian,CHEN Xinpeng,HONG Yiwei,YE Zhizhong.Identifying long non-coding RNAs related to the onset of Sjogren’s syndrome based on machine learning[J].Chinese Journal of Bioinformatics,2023,21(2):146-154. |
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| 摘要: |
| 通过机器学习筛选干燥综合征(SS)患者唇腺组织及全血中潜在发病相关长链非编码RNA(Long non-coding RNA, lncRNA)以及lncRNA与唇腺组织中免疫细胞浸润的相关性。通过GEO数据库获取SS唇腺组织及全血的表达数据,将唇腺组织表达数据归一化处理后,差异分析得到lncRNA表达谱,通过2种机器学习方法筛选并取交集得到共同的lncRNA。基于CIBER-SORT软件计算唇腺组织中22种免疫细胞浸润情况并分析关键lncRNA与免疫细胞浸润的相关性；分析全血中关键lncRNA与临床性状的相关性并绘制ROC曲线；分析关键lncRNA共表达编码蛋白基因,并进行KEGG信号通路分析。共筛选出SS关键lncRNA 1个(HCP5),在唇腺组织及全血中HCP5表达上调。免疫浸润分析显示,在SS唇腺组织中,γδT细胞、巨噬细胞、CD4+ 记忆T细胞比例明显升高,而浆细胞的比例在SS唇腺组织中比例减少。HCP5的表达与γ/δ T 细胞、CD4+ 记忆T细胞在唇腺中的浸润程度呈正相关。在全血中,HCP5与ANA、IgG、抗SSA抗体、抗SSB抗体、ESSDAI具有明显相关性。不同数据集中ROC诊断曲线结果显示HCP5的AUC为0.833和0.877；KEGG信号通路分析显示,唇腺与HCP5共表达的蛋白功能集中于抗原加工和呈递、B细胞受体信号通路等信号通路,全血中与HCP5共表达的蛋白功能集中于代谢途径细胞、凋亡等信号通路。HCP5可能通过影响SS患者唇腺组织免疫细胞的浸润从而影响SS疾病的发病与进展,为SS潜在的诊断及治疗靶点。 |
| 关键词: 干燥综合征 HCP5 免疫浸润 机器学习 长链非编码RNA |
| DOI：10.12113/202203018 |
| 分类号:Q344+.11 |
| 文献标识码:A |
| 基金项目:广东省中医药管理局中医药科研项目(No.20221342);深圳市福田区卫生公益性科研项目(No.FTWS2021026,FTWS2021063,FTWS2021064). |
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| Identifying long non-coding RNAs related to the onset of Sjogren’s syndrome based on machine learning |
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XIAO Jianwei, CAI Xu, GUO Fenlian, CHEN Xinpeng, HONG Yiwei, YE Zhizhong
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(Shenzhen Futian Hospital for Rheumatic Diseases, Shenzhen 518000,Guangdong, China)
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| Abstract: |
| Machine learning was used for idenfifying possible pathogenesis-related long non-coding RNAs (lncRNAs) in labial gland tissue and whole blood of Sjogrens syndrome (SS) patients, and investigating the correlation between the lncRNA with immune cell infiltration in labial gland tissue. The expression data of SS labial gland tissue and whole blood were obtained from the GEO database, and the data were normalized and processed for differential analysis to obtain lncRNA expression profiles. Common lncRNAs were screened and intersected by two machine learning methods. Based on CIBER-SORT software, 22 immune cell infiltration situations in labial gland tissues were calculated,and the correlation between key lncRNAs and immune cell infiltration was analyzed. The correlation between key lncRNAs and clinical traits in whole blood was analyzed and ROC curves were plotted. Key lncRNA co-expression encoding protein genes were analyzed and KEGG signaling pathway analysis was performed. One SS key lncRNA (HCP5) was identified, and HCP5 was upregulated in labial gland tissue and whole blood. Immuno-infiltration analysis showed that the proportion of γδ T cells, macrophages, and CD4+ memory T cells increased in SS labial gland tissue, while the proportion of plasma cells decreased in SS labial gland tissue. The expression of HCP5 was positively correlated with the infiltration of γ/δ T cells and CD4+ memory T cells. In whole blood, HCP5 significantly correlated with ANA, IgG, anti-SSA antibodies, anti-SSB antibodies, and ESSDAI. The ROC diagnostic curve results in different datasets showed that the AUCs of HCP5 were 0.833 and 0.877. KEGG analysis showed that the function of proteins co-expressed with HCP5 in the labial gland was focused on signaling pathways such as antigen processing and presentation and B cell receptor signaling pathway, while the proteins co-expressed with HCP5 in whole blood functioned in signaling pathways such as metabolic pathways and apoptosis. HCP5 may affect the pathogenesis and progression of the disease by regulating the infiltration of immune cells in the labial gland tissue, and may be a potential diagnostic and therapeutic target for SS. |
| Key words: Sjogrens syndrome HCP5 Immune infiltration Machine learning Long non-coding RNA |
