结合生物信息学和机器学习识别骨关节炎支链氨基酸相关基因的生物标志物。

IF 2.2 3区 医学 Q2 ORTHOPEDICS
Xiao-Zhi ZhaYang, Yan-Xiong Chen, Wen-Da Hua, Zheng-Lin Bai, Yun-Peng Jin, Xing-Wen Zhao, Quan-Fu Liu, Zeng-Dong Meng
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引用次数: 0

摘要

背景:支链氨基酸(BCAA)代谢与骨关节炎(OA)有显著相关性,但BCAA相关基因(BCAA- rgs)在OA中的具体作用机制尚不清楚。因此,本研究旨在确定BCAA-RGs在OA组织中的潜在生物标志物和作用机制。方法:从基因表达综合数据库(Gene Expression Omnibus, GEO)中获取差异基因,与BCAA-RGs交叉鉴定候选基因。利用基因本体(GO)和京都基因与基因组百科全书(KEGG)揭示了其潜在机制。随后,通过结合三种机器学习算法来识别OA特征高度相关的基因。此外,我们还创建了诊断图谱和受试者Receiver operating characteristic curves (roc)来评估这些特征基因诊断OA的能力,并预测它们在分子调控网络轴和分子信号通路中的可能作用。结果:通过4178个deg和14个BCAA-RGs交叉获得8个候选基因。随后获得5个候选生物标志物,分别为SLC3A2、SLC7A5、SLC43A2、SLC43A1和SLC7A7。重要的是,SLC3A2和SLC7A5通过验证集和qRT-PCR进行了验证。此外,由SLC3A2和SLC7A5构建的nomogram预测OA的发生率具有很好的准确性。富集结果表明,SLC3A2和SLC7A5在核糖体、胰岛素信号通路、嗅觉转导等方面显著富集。同时,我们还发现XIST通过hsa-miR-30e-5p调控SLC7A5,通过hsa-miR-7-5p调控SLC3A2。OIP5-AS1通过hsa-miR-7-5p调控SLC7A5和SLC3A2。通过这种方法,我们发现了150种药物,包括对乙酰氨基酚和丙烯酰胺,它们同时靶向这两种生物标志物。结论:基于生物信息学,SLC3A2和SLC7A5被鉴定为OA中与BCAA相关的生物标志物,可为OA患者的治疗和诊断提供新的参考。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Integrating bioinformatics and machine learning to identify biomarkers of branched chain amino acid related genes in osteoarthritis.

Background: Branched-chain amino acids (BCAA) metabolism is significantly associated with osteoarthritis (OA), but the specific mechanism of BCAA related genes (BCAA-RGs) in OA is still unclear. Therefore, this research intended to identify potential biomarkers and mechanisms of action of BCAA-RGs in OA tissues.

Methods: Differential genes were obtained from the Gene Expression Omnibus (GEO) database and intersections were taken with BCAA-RGs to identify candidate genes. The underlying mechanisms were revealed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Subsequently, by combining three machine learning algorithms to identify genes with highly correlated OA features. In addition, created diagnostic maps and subject Receiver operating characteristic curves (ROCs) to assess the ability of the signature genes to diagnose OA and to predict their possible roles in molecular regulatory network axes and molecular signaling pathways.

Results: Eight candidate genes were acquired by intersecting 4,178 DEGs and 14 BCAA-RGs. Subsequently, five candidate biomarkers were obtained, namely SLC3A2, SLC7A5, SLC43A2, SLC43A1, and SLC7A7. Importantly, SLC3A2 and SLC7A5 were validated by validation set and qRT-PCR. Furthermore, the nomogram constructed by SLC3A2 and SLC7A5 exhibited excellent accuracy in predicting the incidence of OA. The enrichment results demonstrated that SLC3A2 and SLC7A5 were significantly enriched in ribosome, insulin signaling pathway, olfactory transduction, etc. Meanwhile, we also found XIST regulated SLC7A5 through hsa-miR-30e-5p, and regulated SLC3A2 through hsa-miR-7-5p.OIP5-AS1 regulated SLC7A5 and SLC3A2 through hsa-miR-7-5p. By the way, 150 drugs were identified, including Acetaminophen and Acrylamide, which exhibited simultaneous targeting of these two biomarkers.

Conclusion: Based on bioinformatics, SLC3A2 and SLC7A5 were identified as biomarkers related to BCAA in OA, which may provide a new reference for the treatment and diagnosis of OA patients.

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来源期刊
BMC Musculoskeletal Disorders
BMC Musculoskeletal Disorders 医学-风湿病学
CiteScore
3.80
自引率
8.70%
发文量
1017
审稿时长
3-6 weeks
期刊介绍: BMC Musculoskeletal Disorders is an open access, peer-reviewed journal that considers articles on all aspects of the prevention, diagnosis and management of musculoskeletal disorders, as well as related molecular genetics, pathophysiology, and epidemiology. The scope of the Journal covers research into rheumatic diseases where the primary focus relates specifically to a component(s) of the musculoskeletal system.
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