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[1]王晓楠,杜玮,郁春艳,等.儿童系统性红斑狼疮关键生物标志物的鉴定[J].天津医科大学学报,2025,31(01):10-18.[doi:10.20135/j.issn.1006-8147.2025.01.0010]
　WANG Xiaonan,DU Wei,YU Chunyan,et al.Identification of key biomarkers for childhood systemic lupus erythematosus[J].Journal of Tianjin Medical University,2025,31(01):10-18.[doi:10.20135/j.issn.1006-8147.2025.01.0010]
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儿童系统性红斑狼疮关键生物标志物的鉴定(PDF)
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《天津医科大学学报》[ISSN:1006-8147/CN:12-1259/R]

卷:
31卷
期数:
2025年01期
页码:
10-18
栏目:
生物信息学及网络药理学专题
出版日期:
2025-01-20

文章信息/Info

Title:
Identification of key biomarkers for childhood systemic lupus erythematosus
文章编号:
1006-8147(2025)01-0010-09
作者:
王晓楠1; 2; 杜玮1; 郁春艳1; 邓为民1
（1.天津医科大学基础医学院免疫学系，国家教育部免疫微环境与疾病重点实验室，天津300070；2.天津市儿童医院检验科，天津300134）
Author(s):
WANG Xiaonan1; 2;  DU Wei1;  YU Chunyan1;  DENG Weimin1
（1.Department of Immunology，School of Basic Medical Sciences，Tianjin Medical University，Key Laboratory of Diseases and Microenvironment of Ministry of Education of China，Tianjin 300070，China；2.Department of Clinical Laboratory， Tianjin Children′s Hospital， Tianjin 300134，China）
关键词:
儿童系统性红斑狼疮; 风险评分模型; TNFAIP6; 细胞凋亡; 细胞周期
Keywords:
childhood systemic lupus erythematosus;  risk score model;  TNFAIP6;  apoptosis;  cell cycle
分类号:
Q939.91
DOI:
10.20135/j.issn.1006-8147.2025.01.0010
文献标志码:
A
摘要:
目的：基于生物信息数据库进行数据挖掘，探究儿童系统性红斑狼疮（cSLE）发生的关键基因并构建风险评分模型。方法：从基因数据库中提取cSLE数据，通过多种机器学习识别与cSLE发病相关的基因并构建风险评分模型。通过ELISA验证基因表达，并利用流式细胞术分析TNFAIP6对细胞凋亡和周期的影响。结果：TNFAIP6、B4GALT5、HLX、ANXA3和DYSF与cSLE发病相关，且对cSLE具有较强的诊断价值，其曲线下面积分别为：TNFAIP6：0.866、B4GALT5：0.891、HLX：0.914、ANXA3：0.878、DYSF：0.929。利用TNFAIP6和DYSF构建的风险评分模型能够有效诊断cSLE（曲线下面积：0.969）。与低风险组相比，中性粒细胞在高风险组中显著增加（t=268.5，P=0.009）。实验结果表明TNFAIP6在cSLE患者血清中高表达，且沉默其表达能够促进THP-1细胞凋亡和阻滞细胞周期。结论：利用TNFAIP6和DYSF构建的cSLE风险评分模型可有效识别cSLE；TNFAIP6可能是cSLE潜在的生物标志物。
Abstract:
Objective： To conduct data mining based on bioinformatics databases to explore key genes related to the occurrence of childhood systemic lupus erythematosus（cSLEs） and build a risk score model. Methods： cSLE-related data were obtained from the Gene Expression Comprehensive Database. Genes related to the onset of cSLE were identified through various machine learning methods and a risk score model was constructed. TNFAIP6 expression was verified by ELISA， and the effect of TNFAIP6 on cell apoptosis and cell cycle was analyzed by flow cytometry. Results： TNFAIP6， B4GALT5， HLX， ANXA3 and DYSF were related to the onset of cSLE and had strong diagnostic value for cSLE.Their areas under the curve were TNFAIP6： 0.866， B4GALT5： 0.891， HLX： 0.914， ANXA3： 0.878， DYSF： 0.929. The risk score model constructed using TNFAIP6 and DYSF could effectively diagnose cSLE（areas under the curve was 0.969）. Neutrophil levels were significantly elevated in the high-risk group compared to the low-risk group（t=268.5， P=0.009）. Experimental results showed that TNFAIP6 was highly expressed in the serum of cSLE patients， and its silencing might promote THP-1 cell apoptosis and arrest the cell cycle. Conclusion： The cSLE risk score model constructed using TNFAIP6 and DYSF can effectively identify cSLE； TNFAIP6 may be a potential biomarker for cSLE.

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备注/Memo

备注/Memo:
基金项目：国家重点研发计划（2021YFC2009300）
作者简介：王晓楠（1988-），女，技师，硕士，研究方向：免疫学；通信作者：邓为民，E-mail：dengweimin@tmu.edu.cn。
更新日期/Last Update: 2025-02-10