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Ⅰ型糖尿病T细胞和自然杀伤细胞相关免疫基因特征的鉴定
Authors Wang N, Wang G, Feng X, Yang T
Received 23 May 2024
Accepted for publication 23 July 2024
Published 9 August 2024 Volume 2024:17 Pages 2983—2996
DOI https://doi.org/10.2147/DMSO.S470738
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Prof. Dr. Juei-Tang Cheng
Na Wang,1,2 Guofeng Wang,2 Xiuli Feng,2 Teng Yang2
1Department of Endocrinology, Lianyungang Clinical College of Nanjing Medical University, Lianyungang City, Jiangsu Province, 222000, People’s Republic of China; 2Department of Endocrinology, Jinzhou Medical University(The First People’s Hospital of Lianyungang), Lianyungang City, Jiangsu Province, 222000, People’s Republic of China
Correspondence: Guofeng Wang, Department of Endocrinology, Lianyungang Clinical College of Nanjing Medical University (The First People’s hospital of Lianyungang), No. 6 Zhenhua East Road, Haizhou District, Lianyungang City, Jiangsu Province, 222000, People’s Republic of China, Email wangguofengo@21cn.com
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.
Keywords: Type 1 diabetes, immune cell infiltration, immune gene signature, diagnosis, CSF1