CD4+效应记忆T细胞在骨质疏松和衰老中的相关标记基因特征:来自单细胞分析和孟德尔随机化的见解。

IF 1.6 4区 医学 Q4 BIOCHEMICAL RESEARCH METHODS
Xiangwen Shi, Linmeng Tang, Mingjun Li, Yipeng Wu, Yongqing Xu
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引用次数: 0

摘要

目的:随着人口老龄化的加速,老龄化已成为骨质疏松症(OP)的主要危险因素。本研究旨在通过多种遗传学方法探讨OP与衰老的关系及共同的分子机制。方法:将骨质疏松症患者、老年人和健康对照者的外周血单细胞数据整合起来,分析细胞亚群的特征变化。然后在核心亚群中鉴定差异表达基因(DEGs),并采用孟德尔随机化(MR)分析来探索关键基因与OP之间的潜在因果关系。此外,在大鼠中建立OP模型,并使用RT-qPCR测量关键基因的mRNA水平。结果:通过对scRNA-seq数据的整合、筛选和分析,在OP和衰老样本中鉴定出CD4+效应记忆T (CD4+ TEM)细胞比例增加,将其标记为核心亚群。差异表达分析鉴定出49个DEGs,并通过孟德尔随机化(Mendelian Randomization, MR)进一步分析鉴定出与op显著相关的三个关键基因(KLRB1、NR4A2和S100A4)。值得注意的是,KLRB1和S100A4的上调可能会增强T细胞内以及与其他细胞亚群的相互作用。同时,NR4A2的下调可能会阻碍T细胞与其他细胞亚群之间的交流。RT-qPCR结果显示,OP组NR4A2明显下调。结论:本研究全面分析了OP与衰老之间的潜在联系,确定CD4+ TEM细胞是OP和衰老样本中的核心细胞亚群。进一步揭示了KLRB1、NR4A2和S100A4与OP发生的因果关系,KLRB1和S100A4的上调可能通过促进CD4+ TEM细胞与其他细胞亚群的相互作用参与OP发病,为OP的分子靶向和免疫治疗提供了新的思路。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
CD4+ Effector Memory T Cells Related Marker Gene Signatures in Osteoporosis and Aging: Insight From Single-Cell Analysis and Mendelian Randomization.

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.

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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.
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