Targeting macrophages and ion homeostasis in T2D: new genes and therapeutic pathways identified
IntroductionType 2 diabetes (T2D) is characterized by insulin resistance and chronic inflammation, with macrophages playing a crucial role in pancreatic islet dysfunction. This study explored the intersection of macrophage-specific gene expression and abnormal blood monovalent inorganic cation conce...
Saved in:
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2025-08-01
|
| Series: | Frontiers in Immunology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fimmu.2025.1514243/full |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849770819442442240 |
|---|---|
| author | Lisha Mou Lisha Mou Tony Bowei Wang Ying Lu Ying Lu Zijing Wu Zijing Wu Yuxian Chen Ziqi Luo Xinyu Wang Zuhui Pu Zuhui Pu |
| author_facet | Lisha Mou Lisha Mou Tony Bowei Wang Ying Lu Ying Lu Zijing Wu Zijing Wu Yuxian Chen Ziqi Luo Xinyu Wang Zuhui Pu Zuhui Pu |
| author_sort | Lisha Mou |
| collection | DOAJ |
| description | IntroductionType 2 diabetes (T2D) is characterized by insulin resistance and chronic inflammation, with macrophages playing a crucial role in pancreatic islet dysfunction. This study explored the intersection of macrophage-specific gene expression and abnormal blood monovalent inorganic cation concentration-related genes (ABRGs) in T2D patients via single-cell RNA sequencing (scRNA-seq) and machine learning to identify key genes and potential therapeutic targets.MethodsScRNA-seq data from the pancreatic islet cells of 27 nondiabetic (ND) patients and 17 T2D patients were analyzed to identify differentially expressed genes (DEGs) in macrophages. These DEGs were intersected with ABRGs to identify hub genes. Machine learning models were developed to predict T2D, and structural predictions of the hub proteins were performed. PPI networks and regulatory networks involving transcription factors (TFs) and miRNAs were also analyzed. Correlations between hub ABRGs and immune cell infiltration, as well as cytokine responses, were examined via ssGSEA and immune response enrichment analysis (IREA).ResultsSixteen overlapping hub ABRGs, including ATP1A1, CACNA1D, and CLDN10, were identified. The GBM model demonstrated high predictive accuracy, with an AUC of 0.988. Correlation analysis revealed significant relationships between the hub genes and the infiltration of immune cells, particularly macrophages. Cytokine enrichment analysis revealed that macrophages in T2D exhibit a distinct signature of cytokines, including IL15, IFNα1, IFNβ, and IL17F. PPI networks highlighted significant interactions among the hub genes. Regulatory network analysis revealed that STAT3 is a central TF and that miRNAs such as hsa-mir-1-3p are critical regulators.DiscussionThis study highlights the central roles of macrophages and ABRGs in T2D, identifying novel genes and regulatory networks that contribute to disease progression. The integration of scRNA-seq and machine learning provides valuable insights and potential therapeutic targets for T2D. |
| format | Article |
| id | doaj-art-7341e0168f4843b7b679c53faf0a2721 |
| institution | DOAJ |
| issn | 1664-3224 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Immunology |
| spelling | doaj-art-7341e0168f4843b7b679c53faf0a27212025-08-20T03:02:52ZengFrontiers Media S.A.Frontiers in Immunology1664-32242025-08-011610.3389/fimmu.2025.15142431514243Targeting macrophages and ion homeostasis in T2D: new genes and therapeutic pathways identifiedLisha Mou0Lisha Mou1Tony Bowei Wang2Ying Lu3Ying Lu4Zijing Wu5Zijing Wu6Yuxian Chen7Ziqi Luo8Xinyu Wang9Zuhui Pu10Zuhui Pu11Institute of Translational Medicine, Health Science Center, The First Affiliated Hospital of Shenzhen University, Shenzhen Second People’s Hospital, Shenzhen, Guangdong, ChinaMetaLife Center, Shenzhen Institute of Translational Medicine, Shenzhen, Guangdong, ChinaBiology Department, Skidmore College, Saratoga Springs, NY, United StatesInstitute of Translational Medicine, Health Science Center, The First Affiliated Hospital of Shenzhen University, Shenzhen Second People’s Hospital, Shenzhen, Guangdong, ChinaMetaLife Center, Shenzhen Institute of Translational Medicine, Shenzhen, Guangdong, ChinaInstitute of Translational Medicine, Health Science Center, The First Affiliated Hospital of Shenzhen University, Shenzhen Second People’s Hospital, Shenzhen, Guangdong, ChinaMetaLife Center, Shenzhen Institute of Translational Medicine, Shenzhen, Guangdong, ChinaDepartment of Endocrinology, The First Affiliated Hospital of Shenzhen University, Shenzhen Second People’s Hospital, Shenzhen, Guangdong, ChinaDepartment of Endocrinology, The First Affiliated Hospital of Shenzhen University, Shenzhen Second People’s Hospital, Shenzhen, Guangdong, ChinaDepartment of Endocrinology, The First Affiliated Hospital of Shenzhen University, Shenzhen Second People’s Hospital, Shenzhen, Guangdong, ChinaMetaLife Center, Shenzhen Institute of Translational Medicine, Shenzhen, Guangdong, ChinaImaging Department, The First Affiliated Hospital of Shenzhen University, Shenzhen Second People’s Hospital, Shenzhen, Guangdong, ChinaIntroductionType 2 diabetes (T2D) is characterized by insulin resistance and chronic inflammation, with macrophages playing a crucial role in pancreatic islet dysfunction. This study explored the intersection of macrophage-specific gene expression and abnormal blood monovalent inorganic cation concentration-related genes (ABRGs) in T2D patients via single-cell RNA sequencing (scRNA-seq) and machine learning to identify key genes and potential therapeutic targets.MethodsScRNA-seq data from the pancreatic islet cells of 27 nondiabetic (ND) patients and 17 T2D patients were analyzed to identify differentially expressed genes (DEGs) in macrophages. These DEGs were intersected with ABRGs to identify hub genes. Machine learning models were developed to predict T2D, and structural predictions of the hub proteins were performed. PPI networks and regulatory networks involving transcription factors (TFs) and miRNAs were also analyzed. Correlations between hub ABRGs and immune cell infiltration, as well as cytokine responses, were examined via ssGSEA and immune response enrichment analysis (IREA).ResultsSixteen overlapping hub ABRGs, including ATP1A1, CACNA1D, and CLDN10, were identified. The GBM model demonstrated high predictive accuracy, with an AUC of 0.988. Correlation analysis revealed significant relationships between the hub genes and the infiltration of immune cells, particularly macrophages. Cytokine enrichment analysis revealed that macrophages in T2D exhibit a distinct signature of cytokines, including IL15, IFNα1, IFNβ, and IL17F. PPI networks highlighted significant interactions among the hub genes. Regulatory network analysis revealed that STAT3 is a central TF and that miRNAs such as hsa-mir-1-3p are critical regulators.DiscussionThis study highlights the central roles of macrophages and ABRGs in T2D, identifying novel genes and regulatory networks that contribute to disease progression. The integration of scRNA-seq and machine learning provides valuable insights and potential therapeutic targets for T2D.https://www.frontiersin.org/articles/10.3389/fimmu.2025.1514243/fulltype 2 diabetes (T2D)macrophagesion homeostasisimmune infiltrationScRNA-seqmachine learning |
| spellingShingle | Lisha Mou Lisha Mou Tony Bowei Wang Ying Lu Ying Lu Zijing Wu Zijing Wu Yuxian Chen Ziqi Luo Xinyu Wang Zuhui Pu Zuhui Pu Targeting macrophages and ion homeostasis in T2D: new genes and therapeutic pathways identified Frontiers in Immunology type 2 diabetes (T2D) macrophages ion homeostasis immune infiltration ScRNA-seq machine learning |
| title | Targeting macrophages and ion homeostasis in T2D: new genes and therapeutic pathways identified |
| title_full | Targeting macrophages and ion homeostasis in T2D: new genes and therapeutic pathways identified |
| title_fullStr | Targeting macrophages and ion homeostasis in T2D: new genes and therapeutic pathways identified |
| title_full_unstemmed | Targeting macrophages and ion homeostasis in T2D: new genes and therapeutic pathways identified |
| title_short | Targeting macrophages and ion homeostasis in T2D: new genes and therapeutic pathways identified |
| title_sort | targeting macrophages and ion homeostasis in t2d new genes and therapeutic pathways identified |
| topic | type 2 diabetes (T2D) macrophages ion homeostasis immune infiltration ScRNA-seq machine learning |
| url | https://www.frontiersin.org/articles/10.3389/fimmu.2025.1514243/full |
| work_keys_str_mv | AT lishamou targetingmacrophagesandionhomeostasisint2dnewgenesandtherapeuticpathwaysidentified AT lishamou targetingmacrophagesandionhomeostasisint2dnewgenesandtherapeuticpathwaysidentified AT tonyboweiwang targetingmacrophagesandionhomeostasisint2dnewgenesandtherapeuticpathwaysidentified AT yinglu targetingmacrophagesandionhomeostasisint2dnewgenesandtherapeuticpathwaysidentified AT yinglu targetingmacrophagesandionhomeostasisint2dnewgenesandtherapeuticpathwaysidentified AT zijingwu targetingmacrophagesandionhomeostasisint2dnewgenesandtherapeuticpathwaysidentified AT zijingwu targetingmacrophagesandionhomeostasisint2dnewgenesandtherapeuticpathwaysidentified AT yuxianchen targetingmacrophagesandionhomeostasisint2dnewgenesandtherapeuticpathwaysidentified AT ziqiluo targetingmacrophagesandionhomeostasisint2dnewgenesandtherapeuticpathwaysidentified AT xinyuwang targetingmacrophagesandionhomeostasisint2dnewgenesandtherapeuticpathwaysidentified AT zuhuipu targetingmacrophagesandionhomeostasisint2dnewgenesandtherapeuticpathwaysidentified AT zuhuipu targetingmacrophagesandionhomeostasisint2dnewgenesandtherapeuticpathwaysidentified |