Immune mechanisms of type 1 diabetes revealed by single-cell transcriptomics, bulk transcriptomics, and experimental validation
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Background:
Type 1 diabetes (T1D) is an autoimmune disorder characterized by the destruction of insulin-producing pancreatic β cells. Understanding the immune mechanisms underlying T1D is crucial for developing effective diagnostic and therapeutic strategies. This study aimed to elucidate the immune mechanisms of T1D by integrating single-cell RNA sequencing (scRNA-seq), bulk RNA-seq, and experimental validation.
Methods:
scRNA-seq data (GSE200695) and bulk RNA-seq data (GSE9006) were obtained from the Gene Expression Omnibus (GEO) database. After data preprocessing, principal component analysis (PCA), and clustering, cell subtypes were annotated using ImmGenData as a reference. Receptor-ligand interactions were analyzed to identify key cell subtypes. Least absolute shrinkage and selection operator (LASSO) regression was performed to identify characteristic genes and construct a diagnostic model. Key genes were further validated using the training and validation sets. Functional enrichment and immune infiltration analyses were conducted for the key genes. In vitro experiments were performed to validate the findings using a high-glucose model in the monocytic cell line THP-1. siRNA-mediated knockdown of TRIB1 was performed to investigate its role in regulating monocyte activation and immune-related pathways under high-glucose conditions. Monocyte activation markers, inflammatory cytokines, apoptosis, and the expression of key genes and immune-related genes were assessed using immunofluorescence staining, ELISA, flow cytometry, qPCR, and Western blot.
Results:
Monocytes were identified as the key cell subtype with the most interactions with other cell subtypes. Eleven characteristic genes were selected to construct a diagnostic model, which demonstrated high validation efficiency (AUC > 0.8). Three key genes (ACTG1, REL, and TRIB1) showed consistent expression trends in the training and validation sets. Functional analyses revealed that these genes were involved in immune regulation and PI3K/AKT/mTOR signaling. In vitro experiments confirmed that high glucose induced monocyte activation, as evidenced by increased expression of activation markers (CD86) and pro-inflammatory cytokines (IL-8 and TNF-α). High glucose also increased monocyte apoptosis and altered the expression of key genes (ACTG1, REL, and TRIB1) and immune-related genes (CXCL16, TGFBR1, CTLA4, CD48, TMIGD2, and HLA-DPB1). Knockdown of TRIB1 attenuated high glucose-induced monocyte activation, as demonstrated by decreased expression of activation markers and pro-inflammatory cytokines. TRIB1 knockdown also modulated the expression of immune-related genes and PI3K/AKT/mTOR signaling under high-glucose conditions.
Conclusions:
This study integrates scRNA-seq, bulk RNA-seq, and experimental validation to unravel the immune mechanisms of T1D. Key genes (ACTG1, REL, and TRIB1) and monocytes were identified as crucial players in T1D pathogenesis. The constructed diagnostic model showed high validation efficiency. In vitro experiments confirmed the role of TRIB1 in regulating monocyte activation and immune-related pathways in a high-glucose model. These findings provide novel insights into the immune mechanisms of T1D and potential diagnostic and therapeutic targets.