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1型糖尿病中与T细胞和自然杀伤细胞相关的免疫基因特征鉴定

Identification of Immune Gene Signature Associated with T Cells and Natural Killer Cells in Type 1 Diabetes.

作者信息

Wang Na, Wang Guofeng, Feng Xiuli, Yang Teng

机构信息

Department of Endocrinology, Lianyungang Clinical College of Nanjing Medical University, Lianyungang City, Jiangsu Province, 222000, People's Republic of China.

Department of Endocrinology, Jinzhou Medical University(The First People's Hospital of Lianyungang), Lianyungang City, Jiangsu Province, 222000, People's Republic of China.

出版信息

Diabetes Metab Syndr Obes. 2024 Aug 9;17:2983-2996. doi: 10.2147/DMSO.S470738. eCollection 2024.

Abstract

PURPOSE

This study aimed to investigate the abnormal infiltration of immune cells in type 1 diabetes mellitus (T1D) and elucidate their regulatory mechanisms.

METHODS

Public T1D-related gene expression data were obtained from the Gene Expression Omnibus database.The GSE123658 dataset analyzed whole blood RNA-seq data from type 1 diabetic patients and healthy volunteers. The GSE110914 dataset analyzed neutrophils purified from peripheral blood of patients with symptomatic and pre-symptomatic type 1 diabetes (T1D), at risk of T1D, and healthy controls. Immune cell infiltration analysis was performed to identify abnormally infiltrating immune cells. Differentially expressed immune genes (DEIGs) in T1D samples were identified, followed by the construction of an immune gene signature (IGS) using a protein-protein interaction (PPI) network and Least absolute shrinkage and selection operator Cox regression analyses (LASSO Cox regression analyses). The regulatory mechanisms underlying IGS were explored using gene set enrichment analysis. Furthermore, expression validation, diagnostic efficacy evaluation, and upstream miRNA prediction of hub signature genes were performed. We verified the miRNA expression of the key gene colony stimulating factor 1 (CSF1) and microRNA-326 (miR-326) by reverse transcription-quantitative PCR (RT‒qPCR).

RESULTS

The proportion of infiltrating T and natural killer (NK) cells differed between the T1D and control samples, and 207 immune genes (IGs) related to these immune cells were extracted. After differential expression, PPI, and LASSO Cox regression analyses, four signature DEIGs were identified for IGS construction: notch receptor 1 (NOTCH1), Janus kinase 3 (JAK3), tumor necrosis factor receptor superfamily member 4(TNFRSF4), and CSF1. Key pathways such as the Toll-like receptor signaling pathway were significantly activated in the high-risk group. Moreover, the upregulation of CSF1 in T1D samples was confirmed using a validation dataset, and CSF1 showed high diagnostic efficacy for T1D. Furthermore, CSF1 was targeted by miR-326.We used validated key genes in T1D patients, several of which were confirmed by RT‒qPCR.

CONCLUSION

In conclusion, the identified key IGs may play an important role in T1D. CSF1 can be developed as a novel diagnostic biomarker for T1D.

摘要

目的

本研究旨在探讨1型糖尿病(T1D)中免疫细胞的异常浸润情况,并阐明其调控机制。

方法

从基因表达综合数据库获取与T1D相关的公共基因表达数据。GSE123658数据集分析了1型糖尿病患者和健康志愿者的全血RNA测序数据。GSE110914数据集分析了从有症状和无症状1型糖尿病(T1D)患者、T1D风险人群以及健康对照者外周血中纯化的中性粒细胞。进行免疫细胞浸润分析以识别异常浸润的免疫细胞。鉴定T1D样本中差异表达的免疫基因(DEIGs),随后使用蛋白质-蛋白质相互作用(PPI)网络和最小绝对收缩和选择算子Cox回归分析(LASSO Cox回归分析)构建免疫基因特征(IGS)。使用基因集富集分析探索IGS潜在的调控机制。此外,对枢纽特征基因进行表达验证、诊断效能评估及上游miRNA预测。我们通过逆转录定量PCR(RT-qPCR)验证了关键基因集落刺激因子1(CSF1)和微小RNA-326(miR-326)的miRNA表达。

结果

T1D样本与对照样本中浸润的T细胞和自然杀伤(NK)细胞比例不同,共提取了207个与这些免疫细胞相关的免疫基因(IGs)。经过差异表达、PPI和LASSO Cox回归分析,确定了用于构建IGS的4个特征DEIGs:Notch受体1(NOTCH1)、Janus激酶3(JAK3)、肿瘤坏死因子受体超家族成员4(TNFRSF4)和CSF1。在高危组中,Toll样受体信号通路等关键通路被显著激活。此外,使用验证数据集证实了T1D样本中CSF1的上调,且CSF1对T1D具有较高的诊断效能。此外,CSF1是miR-326的靶标。我们在T1D患者中验证了关键基因,其中一些通过RT-qPCR得到了证实。

结论

总之,鉴定出的关键IGs可能在T1D中发挥重要作用。CSF1可开发为T1D的新型诊断生物标志物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcbb/11321349/f78002ea7f8f/DMSO-17-2983-g0001.jpg

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