CD4+ Effector Memory T Cells Related Marker Gene Signatures in Osteoporosis and Aging: Insight From Single-Cell Analysis and Mendelian Randomization.

IF 1.6 4区 医学 Q4 BIOCHEMICAL RESEARCH METHODS
Xiangwen Shi, Linmeng Tang, Mingjun Li, Yipeng Wu, Yongqing Xu
{"title":"CD4+ Effector Memory T Cells Related Marker Gene Signatures in Osteoporosis and Aging: Insight From Single-Cell Analysis and Mendelian Randomization.","authors":"Xiangwen Shi, Linmeng Tang, Mingjun Li, Yipeng Wu, Yongqing Xu","doi":"10.2174/0113862073353509241205065221","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>With the accelerated aging of the population, aging has emerged as a major risk factor for osteoporosis (OP). This study aims to investigate the relationship and shared molecular mechanisms between OP and aging through various genetic approaches.</p><p><strong>Methods: </strong>Single-cell data from the peripheral blood of osteoporosis patients, aging individuals, and healthy controls were integrated to analyze characteristic changes in cell subpopulations. Differentially expressed genes (DEGs) were then identified within core subpopulations, and Mendelian Randomization (MR) analysis was employed to explore potential causal links between key genes and OP. Additionally, an OP model was established in rats, and mRNA levels of key genes were measured using RT-qPCR.</p><p><strong>Results: </strong>Through the integration, filtering, and analysis of scRNA-seq data, an increased proportion of CD4+ effector memory T (CD4+ TEM) cells were identified in OP and aging samples, marking them as a core subpopulation. Differential expression analysis identified 49 DEGs, and further analysis through Mendelian Randomization (MR) identified three key genes (KLRB1, NR4A2, and S100A4) significantly associated with OP. Notably, the upregulation of KLRB1 and S100A4 may enhance the interactions within T cells and with other cell subgroups. At the same time, the downregulation of NR4A2 could impede communication between T cells and other cell subpopulations. The RT-qPCR results indicated that NR4A2 was significantly downregulated in the OP group.</p><p><strong>Conclusion: </strong>This study conducted a comprehensive analysis of the potential link between OP and aging, identifying CD4+ TEM cells as the core cell subgroup in OP and aging samples. It further revealed the causal relationship between KLRB1, NR4A2, and S100A4 and the occurrence of OP. The upregulation of KLRB1 and S100A4 may contribute to OP pathogenesis by promoting interactions between CD4+ TEM cells and other cell subgroups, providing new insights for molecular targeting and immunotherapy of OP.</p>","PeriodicalId":10491,"journal":{"name":"Combinatorial chemistry & high throughput screening","volume":" ","pages":""},"PeriodicalIF":1.6000,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Combinatorial chemistry & high throughput screening","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.2174/0113862073353509241205065221","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 0

Abstract

Objective: With the accelerated aging of the population, aging has emerged as a major risk factor for osteoporosis (OP). This study aims to investigate the relationship and shared molecular mechanisms between OP and aging through various genetic approaches.

Methods: Single-cell data from the peripheral blood of osteoporosis patients, aging individuals, and healthy controls were integrated to analyze characteristic changes in cell subpopulations. Differentially expressed genes (DEGs) were then identified within core subpopulations, and Mendelian Randomization (MR) analysis was employed to explore potential causal links between key genes and OP. Additionally, an OP model was established in rats, and mRNA levels of key genes were measured using RT-qPCR.

Results: Through the integration, filtering, and analysis of scRNA-seq data, an increased proportion of CD4+ effector memory T (CD4+ TEM) cells were identified in OP and aging samples, marking them as a core subpopulation. Differential expression analysis identified 49 DEGs, and further analysis through Mendelian Randomization (MR) identified three key genes (KLRB1, NR4A2, and S100A4) significantly associated with OP. Notably, the upregulation of KLRB1 and S100A4 may enhance the interactions within T cells and with other cell subgroups. At the same time, the downregulation of NR4A2 could impede communication between T cells and other cell subpopulations. The RT-qPCR results indicated that NR4A2 was significantly downregulated in the OP group.

Conclusion: This study conducted a comprehensive analysis of the potential link between OP and aging, identifying CD4+ TEM cells as the core cell subgroup in OP and aging samples. It further revealed the causal relationship between KLRB1, NR4A2, and S100A4 and the occurrence of OP. The upregulation of KLRB1 and S100A4 may contribute to OP pathogenesis by promoting interactions between CD4+ TEM cells and other cell subgroups, providing new insights for molecular targeting and immunotherapy of OP.

求助全文
约1分钟内获得全文 求助全文
来源期刊
CiteScore
3.10
自引率
5.60%
发文量
327
审稿时长
7.5 months
期刊介绍: Combinatorial Chemistry & High Throughput Screening (CCHTS) publishes full length original research articles and reviews/mini-reviews dealing with various topics related to chemical biology (High Throughput Screening, Combinatorial Chemistry, Chemoinformatics, Laboratory Automation and Compound management) in advancing drug discovery research. Original research articles and reviews in the following areas are of special interest to the readers of this journal: Target identification and validation Assay design, development, miniaturization and comparison High throughput/high content/in silico screening and associated technologies Label-free detection technologies and applications Stem cell technologies Biomarkers ADMET/PK/PD methodologies and screening Probe discovery and development, hit to lead optimization Combinatorial chemistry (e.g. small molecules, peptide, nucleic acid or phage display libraries) Chemical library design and chemical diversity Chemo/bio-informatics, data mining Compound management Pharmacognosy Natural Products Research (Chemistry, Biology and Pharmacology of Natural Products) Natural Product Analytical Studies Bipharmaceutical studies of Natural products Drug repurposing Data management and statistical analysis Laboratory automation, robotics, microfluidics, signal detection technologies Current & Future Institutional Research Profile Technology transfer, legal and licensing issues Patents.
×
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:481959085
Book学术官方微信