Integrative Machine Learning Approach to Explore Glycosylation Signatures and Immune Landscape in Moyamoya Disease.

IF 2.4 Q3 BIOCHEMICAL RESEARCH METHODS
Bioinformatics and Biology Insights Pub Date : 2025-05-24 eCollection Date: 2025-01-01 DOI:10.1177/11779322251342412
Cunxin Tan, Jing Wang, Yanru Wang, Shaoqi Xu, Zhenyu Zhou, Junze Zhang, Shihao He, Ran Duan
{"title":"Integrative Machine Learning Approach to Explore Glycosylation Signatures and Immune Landscape in Moyamoya Disease.","authors":"Cunxin Tan, Jing Wang, Yanru Wang, Shaoqi Xu, Zhenyu Zhou, Junze Zhang, Shihao He, Ran Duan","doi":"10.1177/11779322251342412","DOIUrl":null,"url":null,"abstract":"<p><p>Moyamoya disease (MMD) is a rare, chronic cerebrovascular disorder of uncertain etiology. Although abnormal glucose metabolism has been implicated, the contribution of glycosylation-related genes in MMD remains elusive. In this study, we analyzed 2 transcriptome data sets (GSE189993 and GSE131293) from the Gene Expression Omnibus (GEO) database to identify 723 differentially expressed genes (DEGs) between MMD patients and controls. Intersection genes with known glycosylation-related genes underwent Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. We utilized machine learning to select key hub genes, followed by immune cell infiltration and correlation analyses. In-depth immune cell analysis indicated that both CFP and MGAT5B were closely tied to various immune components, suggesting potential crosstalk between glycosylation pathways and immune regulation. Notably, CFP was positively associated with pDCs, HLA, and CCR, whereas MGAT5B correlated with B-cells, check-points, and T helper cells but showed a negative relationship with Tregs, hinting at an immunoregulatory mechanism influencing MMD progression. Motif-TF annotation highlighted csibp_M2095 as the motif with the highest normalized enrichment score (NES: 6.57). Reverse microRNA (miRNA)-gene prediction identified 75 miRNAs regulating these focus genes, along with 126 miRNA-miRNA interconnections. Connectivity Map (Cmap) analysis revealed that Chenodeoxycholic acid, MRS-1220, Phenytoin, and Piceid were strongly negatively correlated with MMD expression profiles, suggesting potential therapeutic candidates. Enzyme-linked immunosorbent assays confirmed elevated CFP and MGAT5B and reduced PTPN11 in MMD, aligning with our bioinformatic findings. Moreover, PTPN11 knockdown in human brain microvascular endothelial cells (HBMECs) significantly enhanced tube formation, indicating a role in vascular remodeling. Collectively, these results emphasize the importance of glycosylation-related genes and immune dysregulation in MMD pathogenesis. These findings broaden our understanding of MMD's underlying mechanisms and underscore the necessity of continued research into glycosylation-driven pathways for improved disease management.</p>","PeriodicalId":9065,"journal":{"name":"Bioinformatics and Biology Insights","volume":"19 ","pages":"11779322251342412"},"PeriodicalIF":2.4000,"publicationDate":"2025-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12103670/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Bioinformatics and Biology Insights","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/11779322251342412","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q3","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 0

Abstract

Moyamoya disease (MMD) is a rare, chronic cerebrovascular disorder of uncertain etiology. Although abnormal glucose metabolism has been implicated, the contribution of glycosylation-related genes in MMD remains elusive. In this study, we analyzed 2 transcriptome data sets (GSE189993 and GSE131293) from the Gene Expression Omnibus (GEO) database to identify 723 differentially expressed genes (DEGs) between MMD patients and controls. Intersection genes with known glycosylation-related genes underwent Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. We utilized machine learning to select key hub genes, followed by immune cell infiltration and correlation analyses. In-depth immune cell analysis indicated that both CFP and MGAT5B were closely tied to various immune components, suggesting potential crosstalk between glycosylation pathways and immune regulation. Notably, CFP was positively associated with pDCs, HLA, and CCR, whereas MGAT5B correlated with B-cells, check-points, and T helper cells but showed a negative relationship with Tregs, hinting at an immunoregulatory mechanism influencing MMD progression. Motif-TF annotation highlighted csibp_M2095 as the motif with the highest normalized enrichment score (NES: 6.57). Reverse microRNA (miRNA)-gene prediction identified 75 miRNAs regulating these focus genes, along with 126 miRNA-miRNA interconnections. Connectivity Map (Cmap) analysis revealed that Chenodeoxycholic acid, MRS-1220, Phenytoin, and Piceid were strongly negatively correlated with MMD expression profiles, suggesting potential therapeutic candidates. Enzyme-linked immunosorbent assays confirmed elevated CFP and MGAT5B and reduced PTPN11 in MMD, aligning with our bioinformatic findings. Moreover, PTPN11 knockdown in human brain microvascular endothelial cells (HBMECs) significantly enhanced tube formation, indicating a role in vascular remodeling. Collectively, these results emphasize the importance of glycosylation-related genes and immune dysregulation in MMD pathogenesis. These findings broaden our understanding of MMD's underlying mechanisms and underscore the necessity of continued research into glycosylation-driven pathways for improved disease management.

综合机器学习方法探索烟雾病的糖基化特征和免疫景观。
烟雾病是一种罕见的慢性脑血管疾病,病因不明。尽管异常的糖代谢已经牵涉其中,糖基化相关基因在烟雾病中的作用仍然难以捉摸。在这项研究中,我们分析了基因表达Omnibus (GEO)数据库中的2个转录组数据集(GSE189993和GSE131293),以确定烟雾病患者与对照组之间的723个差异表达基因(DEGs)。与已知糖基化相关基因的交叉基因进行基因本体(GO)和京都基因与基因组百科全书(KEGG)富集分析。我们利用机器学习选择关键枢纽基因,然后进行免疫细胞浸润和相关性分析。深入的免疫细胞分析表明,CFP和MGAT5B都与多种免疫成分密切相关,表明糖基化途径与免疫调节之间存在潜在的串导。值得注意的是,CFP与pDCs、HLA和CCR呈正相关,而MGAT5B与b细胞、检查点和T辅助细胞相关,但与Tregs呈负相关,暗示了影响烟雾病进展的免疫调节机制。motif - tf注释显示csibp_M2095是归一化富集分数最高的motif (NES: 6.57)。反向microRNA (miRNA)-基因预测鉴定了75个调节这些焦点基因的miRNA,以及126个miRNA-miRNA互连。连接图(Cmap)分析显示,Chenodeoxycholic acid、MRS-1220、Phenytoin和Piceid与烟雾病表达谱呈强烈负相关,提示潜在的治疗候选药物。酶联免疫吸附试验证实MMD中CFP和MGAT5B升高,PTPN11降低,与我们的生物信息学发现一致。此外,PTPN11在人脑微血管内皮细胞(HBMECs)中的敲低显著增强了管的形成,表明其在血管重塑中起作用。总之,这些结果强调了糖基化相关基因和免疫失调在烟雾病发病机制中的重要性。这些发现拓宽了我们对烟雾病潜在机制的理解,并强调了继续研究糖基化驱动途径以改善疾病管理的必要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Bioinformatics and Biology Insights
Bioinformatics and Biology Insights BIOCHEMICAL RESEARCH METHODS-
CiteScore
6.80
自引率
1.70%
发文量
36
审稿时长
8 weeks
期刊介绍: Bioinformatics and Biology Insights is an open access, peer-reviewed journal that considers articles on bioinformatics methods and their applications which must pertain to biological insights. All papers should be easily amenable to biologists and as such help bridge the gap between theories and applications.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信