Identification and validation of key genes related to innate immune cell barrier in type 2 diabetes mellitus: transcriptome and single-cell combined analysis

Type 2 diabetes mellitus (T2DM) constitutes a significant global public health issue, characterized by insulin resistance and progressive functional decline of pancreatic β-cells. The regulatory role of innate immune cell barrier (ICB)-related genes (ICBRGs) in the progression of T2DM remains unclear. This study aims to identify the key ICBRGs associated with T2DM, elucidate their regulatory mechanisms and clinical significance, and provide molecular targets for precise therapeutic interventions. Initially, T2DM-related transcriptome datasets were downloaded from public databases, with GSE15932 serving as the training set and GSE26168 as the validation set, along with the single-cell dataset GSE268210. Candidate genes were obtained by screening the intersection with ICBRGs through differential expression analysis. Subsequent identification of key genes was conducted using various machine learning algorithms, such as XGBoost and Random Forest (RF). In-depth exploration of gene functions involved immune infiltration analysis, gene set enrichment analysis (GSEA), and single-cell RNA sequencing (scRNA-seq) analysis, encompassing aspects such as cell communication and pseudotemporal analysis. Finally, reverse transcription quantitative polymerase chain reaction (RT-qPCR) was employed to validate the expression of the identified key genes. Three key genes were successfully identified: CEBPA, ELANE, and TGFB1. Immune infiltration analysis revealed significant correlations of these genes with immune cells, particularly monocytes and CD4 + memory T cells. GSEA results indicated co-enrichment of these genes in critical metabolic pathways, including the insulin signaling pathway. Single-cell analysis confirmed that monocytes play a pivotal role in T2DM, exhibiting the highest communication probability with B cells. Pseudotime analysis demonstrated dynamic expression patterns of the key genes during the differentiation of monocytes. RT-qPCR validation indicated significant upregulation of CEBPA and ELANE in T2DM blood samples, while TGFB1 exhibited an increasing trend that did not reach statistical significance. CEBPA, ELANE, and TGFB1 may contribute to the pathogenesis of T2DM through monocyte-related immune regulation. CEBPA and ELANE demonstrated consistent experimental validation, while TGFB1 is proposed as a candidate biomarker that warrants further confirmation in larger clinical cohorts.

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Journal
Scientific Reports
Published
2026-10-26
DOI
https://doi.org/10.1038/s41598-026-77211-3
Primary Topic
Adipokines, Inflammation, and Metabolic Diseases
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article
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article

Identification and validation of key genes related to innate immune cell barrier in type 2 diabetes mellitus: transcriptome and single-cell combined analysis

Feng Wu, Guiling Zheng
Scientific Reports
Adipokines, Inflammation, and Metabolic Diseases
article

Identification and validation of key genes related to innate immune cell barrier in type 2 diabetes mellitus: transcriptome and single-cell combined analysis

Feng Wu, Guiling Zheng
article en

Abstract

Type 2 diabetes mellitus (T2DM) constitutes a significant global public health issue, characterized by insulin resistance and progressive functional decline of pancreatic β-cells. The regulatory role of innate immune cell barrier (ICB)-related genes (ICBRGs) in the progression of T2DM remains unclear. This study aims to identify the key ICBRGs associated with T2DM, elucidate their regulatory mechanisms and clinical significance, and provide molecular targets for precise therapeutic interventions. Initially, T2DM-related transcriptome datasets were downloaded from public databases, with GSE15932 serving as the training set and GSE26168 as the validation set, along with the single-cell dataset GSE268210. Candidate genes were obtained by screening the intersection with ICBRGs through differential expression analysis. Subsequent identification of key genes was conducted using various machine learning algorithms, such as XGBoost and Random Forest (RF). In-depth exploration of gene functions involved immune infiltration analysis, gene set enrichment analysis (GSEA), and single-cell RNA sequencing (scRNA-seq) analysis, encompassing aspects such as cell communication and pseudotemporal analysis. Finally, reverse transcription quantitative polymerase chain reaction (RT-qPCR) was employed to validate the expression of the identified key genes. Three key genes were successfully identified: CEBPA, ELANE, and TGFB1. Immune infiltration analysis revealed significant correlations of these genes with immune cells, particularly monocytes and CD4 + memory T cells. GSEA results indicated co-enrichment of these genes in critical metabolic pathways, including the insulin signaling pathway. Single-cell analysis confirmed that monocytes play a pivotal role in T2DM, exhibiting the highest communication probability with B cells. Pseudotime analysis demonstrated dynamic expression patterns of the key genes during the differentiation of monocytes. RT-qPCR validation indicated significant upregulation of CEBPA and ELANE in T2DM blood samples, while TGFB1 exhibited an increasing trend that did not reach statistical significance. CEBPA, ELANE, and TGFB1 may contribute to the pathogenesis of T2DM through monocyte-related immune regulation. CEBPA and ELANE demonstrated consistent experimental validation, while TGFB1 is proposed as a candidate biomarker that warrants further confirmation in larger clinical cohorts.

Scientific Reports
Chinese People's Liberation Army (CN)
Openalex Percentile: Top 12%
Adipokines, Inflammation, and Metabolic Diseases
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