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Myint O, Sakunrangsit N, Pholtaisong J, Toejing P, Pho-on P, Leelahavanichkul A, Sridurongrit S, Aporntewan C, Greenblatt MB, Lotinun S. Differential Gene Expression Involved in Bone Turnover of Mice Expressing Constitutively Active TGFβ Receptor Type I. Int J Mol Sci 2024; 25:5829. [PMID: 38892016 PMCID: PMC11173332 DOI: 10.3390/ijms25115829] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2024] [Revised: 05/17/2024] [Accepted: 05/23/2024] [Indexed: 06/21/2024] Open
Abstract
Transforming growth factor beta (TGF-β) is ubiquitously found in bone and plays a key role in bone turnover. Mice expressing constitutively active TGF-β receptor type I (Mx1;TβRICA mice) are osteopenic. Here, we identified the candidate genes involved in bone turnover in Mx1;TβRICA mice using RNA sequencing analysis. A total of 285 genes, including 87 upregulated and 198 downregulated genes, were differentially expressed. According to the KEGG analysis, some genes were involved in osteoclast differentiation (Fcgr4, Lilrb4a), B cell receptor signaling (Cd72, Lilrb4a), and neutrophil extracellular trap formation (Hdac7, Padi4). Lilrb4 is related to osteoclast inhibition protein, whereas Hdac7 is a Runx2 corepressor that regulates osteoblast differentiation. Silencing Lilrb4 increased the number of osteoclasts and osteoclast marker genes. The knocking down of Hdac7 increased alkaline phosphatase activity, mineralization, and osteoblast marker genes. Therefore, our present study may provide an innovative idea for potential therapeutic targets and pathways in TβRI-associated bone loss.
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Affiliation(s)
- Ohnmar Myint
- Center of Excellence in Skeletal Disorders and Enzyme Reaction Mechanism, Department of Physiology, Faculty of Dentistry, Chulalongkorn University, Bangkok 10330, Thailand; (O.M.); (N.S.); (J.P.); (P.T.); (P.P.-o.)
| | - Nithidol Sakunrangsit
- Center of Excellence in Skeletal Disorders and Enzyme Reaction Mechanism, Department of Physiology, Faculty of Dentistry, Chulalongkorn University, Bangkok 10330, Thailand; (O.M.); (N.S.); (J.P.); (P.T.); (P.P.-o.)
| | - Jatuphol Pholtaisong
- Center of Excellence in Skeletal Disorders and Enzyme Reaction Mechanism, Department of Physiology, Faculty of Dentistry, Chulalongkorn University, Bangkok 10330, Thailand; (O.M.); (N.S.); (J.P.); (P.T.); (P.P.-o.)
| | - Parichart Toejing
- Center of Excellence in Skeletal Disorders and Enzyme Reaction Mechanism, Department of Physiology, Faculty of Dentistry, Chulalongkorn University, Bangkok 10330, Thailand; (O.M.); (N.S.); (J.P.); (P.T.); (P.P.-o.)
| | - Pinyada Pho-on
- Center of Excellence in Skeletal Disorders and Enzyme Reaction Mechanism, Department of Physiology, Faculty of Dentistry, Chulalongkorn University, Bangkok 10330, Thailand; (O.M.); (N.S.); (J.P.); (P.T.); (P.P.-o.)
| | - Asada Leelahavanichkul
- Division of Immunology, Department of Microbiology, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand;
| | - Somyoth Sridurongrit
- Department of Anatomy, Faculty of Science, Mahidol University, Bangkok 10400, Thailand;
| | - Chatchawit Aporntewan
- Department of Mathematics and Computer Science, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand;
| | - Matthew B. Greenblatt
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY 10065, USA;
- Research Division, Hospital for Special Surgery, New York, NY 10065, USA
| | - Sutada Lotinun
- Center of Excellence in Skeletal Disorders and Enzyme Reaction Mechanism, Department of Physiology, Faculty of Dentistry, Chulalongkorn University, Bangkok 10330, Thailand; (O.M.); (N.S.); (J.P.); (P.T.); (P.P.-o.)
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Sun R, Duan D, Li R. Transcriptome Sequencing Identifies Abnormal lncRNAs and mRNAs and Reveals Potentially Hub Immune-Related mRNA in Osteoporosis with Vertebral Fracture. Clin Interv Aging 2024; 19:203-217. [PMID: 38352274 PMCID: PMC10863500 DOI: 10.2147/cia.s441251] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Accepted: 01/17/2024] [Indexed: 02/16/2024] Open
Abstract
Background Recent studies have put forward the viewpoint of "bone immunology", which holds that the immune system and immune factors play an important regulatory role in the occurrence and development of osteoporosis. This study was intended to identify genetic characteristics of differentially expressed immune-related mRNA and lncRNA in patients combined with osteoporosis and vertebral fracture. Methods The peripheral blood samples were obtained from 3 groups of subjects: healthy control (HC), osteoporosis patients without vertebral fracture (OWF), and osteoporosis patients combined with vertebral fracture (OVF). The data were integrated to obtain differentially expressed mRNAs (DEmRNAs) and differentially expressed lncRNAs (DElncRNAs). Subsequently, the protein-protein interaction (PPI) networks were constructed. Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) enrichment analyses were performed. Cytoscape-cytoHubba plug-in was used to identify key DEmRNAs. Furthermore, lncRNA-miRNA-mRNA, mRNA-lncRNA co-expression and transcription factors (TFs) networks were constructed. In addition, real-time PCR verification was performed. Results Totally of 3378 lncRNA-mRNA pairs were obtained, and the lncRNA co-expressed mRNA was mainly enriched in immune-related pathways, especially in GO-biological process (GO-BP) analysis. A total of 8 hub immune-related DEmRNAs were obtained, including IL18R1, IL18RAP, SLC11A1, CSF2RA, CCR3, IL1R2, PGLYRP1, and IL1R1. The TFs network showed that 8 hub immune-related DEmRNAs had interacting TFs. The co-expression network showed that 7 hub immune-related DEmRNAs (IL18R1, IL18RAP, SLC11A1, CSF2RA, IL-1R2, PGLYRP1, and IL1R1) had lncRNA-mRNA co-expression relationship. In addition, the lncRNA-miRNA-mRNA network includes 32 miRNAs, 7 hub immune-related mRNAs (IL18R1, IL18RAP, CSF2RA, CCR3, IL1R2, PGLYRP1, and IL1R1), and 11 lncRNAs. Conclusion Our study provides a novel and in-depth identification of co-expressed mRNAs and lncRNAs in patients combined with osteoporosis and vertebral fracture at a molecular level. This may provide new candidate biomarkers for the diagnosis of patients with high-risk fractures in the future.
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Affiliation(s)
- Rongxin Sun
- Department of Orthopaedics, The Sixth Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang Province, People’s Republic of China
| | - Desheng Duan
- Second Department of Orthopaedics, Third People’s Hospital of Anyang City, Anyang City, Henan Province, People’s Republic of China
| | - Renzeng Li
- Second Department of Orthopaedics, Third People’s Hospital of Anyang City, Anyang City, Henan Province, People’s Republic of China
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Liao S, Yang M, Li D, Wu Y, Sun H, Lu J, Liu X, Deng T, Wang Y, Xie N, Tang D, Nie G, Fan X. Comprehensive bulk and single-cell transcriptome profiling give useful insights into the characteristics of osteoarthritis associated synovial macrophages. Front Immunol 2023; 13:1078414. [PMID: 36685529 PMCID: PMC9849898 DOI: 10.3389/fimmu.2022.1078414] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Accepted: 12/06/2022] [Indexed: 01/07/2023] Open
Abstract
Background Osteoarthritis (OA) is a common chronic joint disease, but the association between molecular and cellular events and the pathogenic process of OA remains unclear. Objective The study aimed to identify key molecular and cellular events in the processes of immune infiltration of the synovium in OA and to provide potential diagnostic and therapeutic targets. Methods To identify the common differential expression genes and function analysis in OA, we compared the expression between normal and OA samples and analyzed the protein-protein interaction (PPI). Additionally, immune infiltration analysis was used to explore the differences in common immune cell types, and Gene Set Variation Analysis (GSVA) analysis was applied to analyze the status of pathways between OA and normal groups. Furthermore, the optimal diagnostic biomarkers for OA were identified by least absolute shrinkage and selection operator (LASSO) models. Finally, the key role of biomarkers in OA synovitis microenvironment was discussed through single cell and Scissor analysis. Results A total of 172 DEGs (differentially expressed genes) associated with osteoarticular synovitis were identified, and these genes mainly enriched eight functional categories. In addition, immune infiltration analysis found that four immune cell types, including Macrophage, B cell memory, B cell, and Mast cell were significantly correlated with OA, and LASSO analysis showed that Macrophage were the best diagnostic biomarkers of immune infiltration in OA. Furthermore, using scRNA-seq dataset, we also analyzed the cell communication patterns of Macrophage in the OA synovial inflammatory microenvironment and found that CCL, MIF, and TNF signaling pathways were the mainly cellular communication pathways. Finally, Scissor analysis identified a population of M2-like Macrophages with high expression of CD163 and LYVE1, which has strong anti-inflammatory ability and showed that the TNF gene may play an important role in the synovial microenvironment of OA. Conclusion Overall, Macrophage is the best diagnostic marker of immune infiltration in osteoarticular synovitis, and it can communicate with other cells mainly through CCL, TNF, and MIF signaling pathways in microenvironment. In addition, TNF gene may play an important role in the development of synovitis.
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Affiliation(s)
- Shengyou Liao
- Shenzhen Key Laboratory of Nanozymes and Translational Cancer Research, Department of Otolaryngology, Shenzhen Institute of Translational Medicine, The First Affiliated Hospital of Shenzhen University, Shenzhen Second People’s Hospital, Shenzhen, Guangdong, China
| | - Ming Yang
- Department of Otolaryngology, Shenzhen First People’s Hospital, The Affiliated Hospital of Jinan University, Shenzhen, Guangdong, China
| | - Dandan Li
- Guangdong Provincial Engineering Research Center of Autoimmune Disease Precision Medicine, the Second Clinical Medical College of Jinan University, the First Affiliated Hospital of Southern University of Science and Technology, Shenzhen People’s Hospital, Shenzhen, China
| | - Ye Wu
- Shenzhen Key Laboratory of Nanozymes and Translational Cancer Research, Department of Otolaryngology, Shenzhen Institute of Translational Medicine, The First Affiliated Hospital of Shenzhen University, Shenzhen Second People’s Hospital, Shenzhen, Guangdong, China,Department of Otolaryngology, School of Basic Medical Sciences, Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Hong Sun
- The Bio-bank of Shenzhen Second People’s Hospital, The First Affiliated Hospital of Shenzhen University, Shenzhen, Guangdong, China
| | - Jingxiao Lu
- The Bio-bank of Shenzhen Second People’s Hospital, The First Affiliated Hospital of Shenzhen University, Shenzhen, Guangdong, China
| | - Xinying Liu
- The Bio-bank of Shenzhen Second People’s Hospital, The First Affiliated Hospital of Shenzhen University, Shenzhen, Guangdong, China
| | - Tingting Deng
- Shenzhen Key Laboratory of Nanozymes and Translational Cancer Research, Department of Otolaryngology, Shenzhen Institute of Translational Medicine, The First Affiliated Hospital of Shenzhen University, Shenzhen Second People’s Hospital, Shenzhen, Guangdong, China
| | - Yujie Wang
- Shenzhen Key Laboratory of Nanozymes and Translational Cancer Research, Department of Otolaryngology, Shenzhen Institute of Translational Medicine, The First Affiliated Hospital of Shenzhen University, Shenzhen Second People’s Hospital, Shenzhen, Guangdong, China
| | - Ni Xie
- The Bio-bank of Shenzhen Second People’s Hospital, The First Affiliated Hospital of Shenzhen University, Shenzhen, Guangdong, China
| | - Donge Tang
- Guangdong Provincial Engineering Research Center of Autoimmune Disease Precision Medicine, the Second Clinical Medical College of Jinan University, the First Affiliated Hospital of Southern University of Science and Technology, Shenzhen People’s Hospital, Shenzhen, China
| | - Guohui Nie
- Shenzhen Key Laboratory of Nanozymes and Translational Cancer Research, Department of Otolaryngology, Shenzhen Institute of Translational Medicine, The First Affiliated Hospital of Shenzhen University, Shenzhen Second People’s Hospital, Shenzhen, Guangdong, China,State Key Laboratory of Chemical Oncogenomics, Guangdong Provincial Key Laboratory of Chemical Genomics, Peking University Shenzhen Graduate School, Shenzhen, Guangdong, China,*Correspondence: Guohui Nie, ; Xiaoqin Fan,
| | - Xiaoqin Fan
- Shenzhen Key Laboratory of Nanozymes and Translational Cancer Research, Department of Otolaryngology, Shenzhen Institute of Translational Medicine, The First Affiliated Hospital of Shenzhen University, Shenzhen Second People’s Hospital, Shenzhen, Guangdong, China,The Bio-bank of Shenzhen Second People’s Hospital, The First Affiliated Hospital of Shenzhen University, Shenzhen, Guangdong, China,*Correspondence: Guohui Nie, ; Xiaoqin Fan,
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Haas-Neil S, Dvorkin-Gheva A, Forsythe P. Severe, but not moderate asthmatics share blood transcriptomic changes with post-traumatic stress disorder and depression. PLoS One 2022; 17:e0275864. [PMID: 36206293 PMCID: PMC9543640 DOI: 10.1371/journal.pone.0275864] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Accepted: 09/23/2022] [Indexed: 11/24/2022] Open
Abstract
Asthma, an inflammatory disorder of the airways, is one of the most common chronic illnesses worldwide and is associated with significant morbidity. There is growing recognition of an association between asthma and mood disorders including post-traumatic stress disorder (PTSD) and major depressive disorder (MDD). Although there are several hypotheses regarding the relationship between asthma and mental health, there is little understanding of underlying mechanisms and causality. In the current study we utilized publicly available datasets of human blood mRNA collected from patients with severe and moderate asthma, MDD, and PTSD. We performed differential expression (DE) analysis and Gene Set Enrichment Analysis (GSEA) on diseased subjects against the healthy subjects from their respective datasets, compared the results between diseases, and validated DE genes and gene sets with 4 more independent datasets. Our analysis revealed that commonalities in blood transcriptomic changes were only found between the severe form of asthma and mood disorders. Gene expression commonly regulated in PTSD and severe asthma, included ORMDL3 a gene known to be associated with asthma risk and STX8, which is involved in TrkA signaling. We also identified several pathways commonly regulated to both MDD and severe asthma. This study reveals gene and pathway regulation that potentially drives the comorbidity between severe asthma, PTSD, and MDD and may serve as foci for future research aimed at gaining a better understanding of both the relationship between asthma and PTSD, and the pathophysiology of the individual disorders.
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Affiliation(s)
- Sandor Haas-Neil
- The Brain Body Institute, St. Joseph’s Hospital, McMaster University, Hamilton, Ontario, Canada
| | - Anna Dvorkin-Gheva
- McMaster Immunology Research Centre, Department of Medicine, McMaster University, Hamilton, Ontario, Canada
| | - Paul Forsythe
- Alberta Respiratory Centre, Division of Pulmonary Medicine, Department of Medicine, University of Alberta, Edmonton, Alberta, Canada
- * E-mail:
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Cao J, Ding H, Shang J, Ma L, Wang Q, Feng S. Weighted gene co-expression network analysis reveals specific modules and hub genes related to immune infiltration of osteoarthritis. ANNALS OF TRANSLATIONAL MEDICINE 2021; 9:1525. [PMID: 34790731 PMCID: PMC8576690 DOI: 10.21037/atm-21-4566] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Accepted: 10/19/2021] [Indexed: 12/26/2022]
Abstract
Background The incidence of osteoarthritis (OA), a chronic degenerative disease, is increasing every year. There is no effective clinical treatment for OA and the pathological mechanism remains unclear. Early diagnosis is an effective strategy to control the progress of OA. In this study, we aimed to identify potential early diagnostic biomarkers. Methods We downloaded the gene expression profile dataset, GSE51588 and GSE55235, from the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) public database. The differentially expressed genes (DEGs) were screened out using the “limma” R package. Weighted gene co-expression network analysis (WGCNA) was utilized to build the co-expression network between the normal and OA samples. A Venn diagram was constructed to detect the hub genes. Potential molecular mechanisms and signaling pathways were enriched by gene set variation analysis (GSVA). Single sample gene set enrichment analysis (ssGSEA) was used to identify the immune infiltration of OA. Results We screened out three hub genes based on WGCNA and DEGs in this study. GSVA results showed that nuclear factor interleukin-3 (NFIL3) was related to tumor necrosis factor alpha (TNF-α) signaling via nuclear factor kappa-B (NF-κB), the reactive oxygen species pathway, and myelocytomatosis (MYC) targets v2. Highly-expressed ADM (adrenomedullin) pathways included TNF-α signaling via NF-κB, the reactive oxygen species pathway, and ultraviolet (UV) response up. OGN (osteoglycin)-enriched pathways included epithelial mesenchymal transition, coagulation, and peroxisome. Conclusions We identified three hub genes (NFIL3, ADM, and OGN) that were correlated to the development and progression of OA, which may provide new biomarkers for early diagnosis.
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Affiliation(s)
- Jiangang Cao
- Department of Orthopedics, Tianjin Medical University General Hospital, Tianjin, China.,International Science and Technology Cooperation Base of Spinal Cord Injury, Tianjin Key Laboratory of Spine and Spinal Cord Injury, Department of Orthopedics, Tianjin Medical University General Hospital, Tianjin, China
| | - Han Ding
- Department of Orthopedics, Tianjin Medical University General Hospital, Tianjin, China.,International Science and Technology Cooperation Base of Spinal Cord Injury, Tianjin Key Laboratory of Spine and Spinal Cord Injury, Department of Orthopedics, Tianjin Medical University General Hospital, Tianjin, China
| | - Jun Shang
- Department of Orthopedics, Tianjin Medical University General Hospital, Tianjin, China.,International Science and Technology Cooperation Base of Spinal Cord Injury, Tianjin Key Laboratory of Spine and Spinal Cord Injury, Department of Orthopedics, Tianjin Medical University General Hospital, Tianjin, China
| | - Lei Ma
- Department of Orthopedics, Tianjin Medical University General Hospital, Tianjin, China.,International Science and Technology Cooperation Base of Spinal Cord Injury, Tianjin Key Laboratory of Spine and Spinal Cord Injury, Department of Orthopedics, Tianjin Medical University General Hospital, Tianjin, China
| | - Qi Wang
- Department of Orthopedics, Tianjin Medical University General Hospital, Tianjin, China.,International Science and Technology Cooperation Base of Spinal Cord Injury, Tianjin Key Laboratory of Spine and Spinal Cord Injury, Department of Orthopedics, Tianjin Medical University General Hospital, Tianjin, China
| | - Shiqing Feng
- Department of Orthopedics, Tianjin Medical University General Hospital, Tianjin, China.,International Science and Technology Cooperation Base of Spinal Cord Injury, Tianjin Key Laboratory of Spine and Spinal Cord Injury, Department of Orthopedics, Tianjin Medical University General Hospital, Tianjin, China
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