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已发表论文
链脲佐菌素诱导的 2 型糖尿病小鼠骨免疫微环境的改变：单细胞 RNA 测序分析
Authors Han K, Yan SG, Liu F , Li L , Zhou D, Li L, Liu N, Dong J
Received 17 June 2025
Accepted for publication 29 October 2025
Published 4 November 2025 Volume 2025:18 Pages 15309—15327
DOI https://doi.org/10.2147/JIR.S544316
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 3
Editor who approved publication: Dr Quan Zhang
Ke Han,1 Shuang G Yan,2 Fanxiao Liu,1 Lianxin Li,1 Dongsheng Zhou,1 Lin Li,3 Nan Liu,1 Jinlei Dong1
1Department of Orthopaedics, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, People’s Republic of China; 2Department of Orthopaedic Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, People’s Republic of China; 3Department of Orthopedic Surgery, Tengzhou Central People’s Hospital Affiliated to Jining Medical University, Tengzhou, Shandong, People’s Republic of China
Correspondence: Jinlei Dong, Department of Orthopaedics Shandong Provincial Hospital affiliated to Shandong First Medical University, Jinan, Shandong, People’s Republic of China, Email dongjinlei@163.com
Background: This study aimed to delineate the single-cell transcriptome of bone marrow (BM) cells from wild-type (WT) and type 2 diabetic (T2D) mice, revealing distinct immune microenvironment features.
Methods: Single high-throughput single-cell RNA sequencing dataset (GSE212726) from BM cells of WT and streptozotocin (STZ)-induced T2DM mice were analyzed. Uniform manifold approximation and projection (UMAP), pseudo-time analysis, gene enrichment studies, and CellphoneDB were employed to identify immune cell interactions within the osteoimmune microenvironment. Key gene expression was validated by quantitative real-time polymerase chain reaction (qRT-PCR).
Results: After filtering low-quality cells and doublets, 9,360 cells (WT) and 10,885 cells (T2DM) were retained and classified into 12 clusters. Proportional analysis revealed a significant decrease in BM-neutrophils (66.56% → 54.73%) and an increase in B cells (9.16% → 19.78%) in the DM group. The DM/WT ratio for BM-neutrophils/T cells, BM-neutrophils/DCs, and monocytes/T cells increased, while the ratio for BM-neutrophils/Naïve_B decreased. KEGG pathway analysis highlighted enrichment of neurodegeneration, protein processing in the endoplasmic reticulum, and amyotrophic lateral sclerosis pathways in BM-neutrophils. Intercellular communication analysis indicated reduced incoming and outgoing interaction strength for B cells and T cells, while the T2D group showed enhanced THBS, VISFATIN, CLEC, IL4, and IL6 signaling. Notably, CLEC was specific to outgoing signaling in T cells, and THBS was specific to both outgoing and incoming signaling in monocytes, MSCs, and BM-neutrophils.
Conclusion: Single-cell RNA sequencing provides a comprehensive profile of bone marrow immune cells in T2D mice and has highlighted their heterogeneity, population shifts, and intercellular interactions. These findings highlight critical alterations in immune cell functions that may contribute to T2D progression and suggest possible avenues for future therapeutic investigation. Future research should continue to leverage scRNA-seq technology to refine treatment strategies and enhance patient outcomes by addressing immune dysfunction and chronic inflammation.
Keywords: single-cell RNA sequencing, bone marrow, diabetes mellitus, osteoimmunology, lymphocyte
1Department of Orthopaedics, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, People’s Republic of China; 2Department of Orthopaedic Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, People’s Republic of China; 3Department of Orthopedic Surgery, Tengzhou Central People’s Hospital Affiliated to Jining Medical University, Tengzhou, Shandong, People’s Republic of China
Correspondence: Jinlei Dong, Department of Orthopaedics Shandong Provincial Hospital affiliated to Shandong First Medical University, Jinan, Shandong, People’s Republic of China, Email dongjinlei@163.com
Background: This study aimed to delineate the single-cell transcriptome of bone marrow (BM) cells from wild-type (WT) and type 2 diabetic (T2D) mice, revealing distinct immune microenvironment features.
Methods: Single high-throughput single-cell RNA sequencing dataset (GSE212726) from BM cells of WT and streptozotocin (STZ)-induced T2DM mice were analyzed. Uniform manifold approximation and projection (UMAP), pseudo-time analysis, gene enrichment studies, and CellphoneDB were employed to identify immune cell interactions within the osteoimmune microenvironment. Key gene expression was validated by quantitative real-time polymerase chain reaction (qRT-PCR).
Results: After filtering low-quality cells and doublets, 9,360 cells (WT) and 10,885 cells (T2DM) were retained and classified into 12 clusters. Proportional analysis revealed a significant decrease in BM-neutrophils (66.56% → 54.73%) and an increase in B cells (9.16% → 19.78%) in the DM group. The DM/WT ratio for BM-neutrophils/T cells, BM-neutrophils/DCs, and monocytes/T cells increased, while the ratio for BM-neutrophils/Naïve_B decreased. KEGG pathway analysis highlighted enrichment of neurodegeneration, protein processing in the endoplasmic reticulum, and amyotrophic lateral sclerosis pathways in BM-neutrophils. Intercellular communication analysis indicated reduced incoming and outgoing interaction strength for B cells and T cells, while the T2D group showed enhanced THBS, VISFATIN, CLEC, IL4, and IL6 signaling. Notably, CLEC was specific to outgoing signaling in T cells, and THBS was specific to both outgoing and incoming signaling in monocytes, MSCs, and BM-neutrophils.
Conclusion: Single-cell RNA sequencing provides a comprehensive profile of bone marrow immune cells in T2D mice and has highlighted their heterogeneity, population shifts, and intercellular interactions. These findings highlight critical alterations in immune cell functions that may contribute to T2D progression and suggest possible avenues for future therapeutic investigation. Future research should continue to leverage scRNA-seq technology to refine treatment strategies and enhance patient outcomes by addressing immune dysfunction and chronic inflammation.
Keywords: single-cell RNA sequencing, bone marrow, diabetes mellitus, osteoimmunology, lymphocyte