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Robertson CC, Elgamal RM, Henry-Kanarek BA, Arvan P, Chen S, Dhawan S, Eizirik DL, Kaddis JS, Vahedi G, Parker SCJ, Gaulton KJ, Soleimanpour SA. Untangling the genetics of beta cell dysfunction and death in type 1 diabetes. Mol Metab 2024; 86:101973. [PMID: 38914291 PMCID: PMC11283044 DOI: 10.1016/j.molmet.2024.101973] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/14/2024] [Revised: 06/18/2024] [Accepted: 06/19/2024] [Indexed: 06/26/2024] Open
Abstract
BACKGROUND Type 1 diabetes (T1D) is a complex multi-system disease which arises from both environmental and genetic factors, resulting in the destruction of insulin-producing pancreatic beta cells. Over the past two decades, human genetic studies have provided new insight into the etiology of T1D, including an appreciation for the role of beta cells in their own demise. SCOPE OF REVIEW Here, we outline models supported by human genetic data for the role of beta cell dysfunction and death in T1D. We highlight the importance of strong evidence linking T1D genetic associations to bona fide candidate genes for mechanistic and therapeutic consideration. To guide rigorous interpretation of genetic associations, we describe molecular profiling approaches, genomic resources, and disease models that may be used to construct variant-to-gene links and to investigate candidate genes and their role in T1D. MAJOR CONCLUSIONS We profile advances in understanding the genetic causes of beta cell dysfunction and death at individual T1D risk loci. We discuss how genetic risk prediction models can be used to address disease heterogeneity. Further, we present areas where investment will be critical for the future use of genetics to address open questions in the development of new treatment and prevention strategies for T1D.
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Affiliation(s)
- Catherine C Robertson
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA; Center for Precision Health Research, National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA
| | - Ruth M Elgamal
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
| | - Belle A Henry-Kanarek
- Department of Internal Medicine and Division of Metabolism, Endocrinology, and Diabetes, University of Michigan, Ann Arbor, MI, USA
| | - Peter Arvan
- Department of Internal Medicine and Division of Metabolism, Endocrinology, and Diabetes, University of Michigan, Ann Arbor, MI, USA
| | - Shuibing Chen
- Department of Surgery, Weill Cornell Medicine, New York, NY, USA; Center for Genomic Health, Weill Cornell Medicine, New York, NY, USA
| | - Sangeeta Dhawan
- Department of Translational Research and Cellular Therapeutics, Arthur Riggs Diabetes and Metabolism Research Institute, City of Hope, Duarte, CA, USA
| | - Decio L Eizirik
- ULB Center for Diabetes Research, Université Libre de Bruxelles, Brussels, Belgium
| | - John S Kaddis
- Department of Diabetes and Cancer Discovery Science, Arthur Riggs Diabetes and Metabolism Research Institute, Beckman Research Institute, City of Hope, Duarte, CA, USA
| | - Golnaz Vahedi
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Stephen C J Parker
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA; Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA; Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA.
| | - Kyle J Gaulton
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA.
| | - Scott A Soleimanpour
- Department of Internal Medicine and Division of Metabolism, Endocrinology, and Diabetes, University of Michigan, Ann Arbor, MI, USA.
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Mi K, Zeng L, Chen Y, Yang S. Integrative Analysis of Single-Cell and Bulk RNA Sequencing Reveals Prognostic Characteristics of Macrophage Polarization-Related Genes in Lung Adenocarcinoma. Int J Gen Med 2023; 16:5031-5050. [PMID: 37942473 PMCID: PMC10629586 DOI: 10.2147/ijgm.s430408] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Accepted: 10/30/2023] [Indexed: 11/10/2023] Open
Abstract
Background Lung adenocarcinoma (LUAD) is a group of cancers with poor prognosis. The combination of single-cell RNA sequencing (scRNA-seq) and bulk RNA sequencing (RNA-seq) can identify important genes involved in cancer development and progression from a broader perspective. Methods The scRNA-seq data and bulk RNA-seq data of LUAD were downloaded from the Gene Expression Omnibus (GEO) database and the Cancer Genome Atlas (TCGA) database. Analyzing scRNA-seq for core cells in the GSE131907 dataset, and the uniform manifold approximation and projection (UMAP) was used for dimensionality reduction and cluster identification. Macrophage polarization-associated subtypes were acquired from the TCGA-LUAD dataset after analysis, followed by further identification of differentially expressed genes (DEGs) in the TCGA-LUAD dataset (normal/LUAD tissue samples, two subtypes). Venn diagrams were utilized to visualize differentially expressed and highly variable macrophage polarization-related genes. Subsequently, a prognostic risk model for LUAD patients was constructed by univariate Cox and Least Absolute Shrinkage and Selection Operator (LASSO), and the model was investigated for stability in the external data GSE72094. After analyzing the correlation between the trait genes and significantly mutated genes, the immune infiltration between the high/low-risk groups was then examined. The Monocle package was applied to analyze the pseudo-temporal trajectory analysis of different cell clusters in macrophage clusters. Subsequently, cell clusters of data macrophages were selected as key cell clusters to explore the role of characteristic genes in different cell populations and to identify transcription factors (TFs) that affect signature genes. Finally, qPCR were employed to validate the expression levels of prognosis signature genes in LUAD. Results 424 macrophage highly variable genes, 3920 DEGs, and 9561 DEGs were obtained from macrophage clusters, the macrophage polarization-related subtypes, and normal/LUAD tissue samples, respectively. Twenty-eight differentially expressed and highly mutated MPRGs were obtained. A prognostic risk model with 7 DE-MPRGs (RGS13, ADRB2, DDIT4, MS4A2, ALDH2, CTSH, and PKM) was constructed. This prognostic model still has a good prediction effect in the GSE72094 dataset. ZNF536 and DNAH9 were mutated in the low-risk group, while COL11A1 was mutated in the high-risk group, and they were highly correlated with the characteristic genes. A total of 11 immune cells were significantly different in the high/low-risk groups. Five cell types were again identified in the macrophage cluster, and then NK cells: CD56hiCD62L+ differentiated earlier and were present mainly on 2 branches. While macrophages were present on 2 branches and differentiated later. It was found that the expression levels of BCLAF1 and MAX were higher in cluster 1, which might be the TFs affecting the expression of the characteristic genes. Moreover, qPCR confirmed that the expression of the prognosis genes was generally consistent with the results of the bioinformatic analysis. Conclusion Seven MPRGs (RGS13, ADRB2, DDIT4, MS4A2, ALDH2, CTSH, and PKM) were identified as prognostic genes for LUAD and revealed the mechanisms of MPRGs at the single-cell level.
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Affiliation(s)
- Ke Mi
- Department of Respiratory and Critical Care Medicine, the Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, People’s Republic of China
| | - Lizhong Zeng
- Department of Respiratory and Critical Care Medicine, the Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, People’s Republic of China
| | - Yang Chen
- Department of Respiratory and Critical Care Medicine, the Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, People’s Republic of China
| | - Shuanying Yang
- Department of Respiratory and Critical Care Medicine, the Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, People’s Republic of China
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Wang Y, Zhao J, Gu Y, Wang H, Jiang M, Zhao S, Qing H, Ni J. Cathepsin H: molecular characteristics and clues to function and mechanism. Biochem Pharmacol 2023; 212:115585. [PMID: 37148981 DOI: 10.1016/j.bcp.2023.115585] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Revised: 04/26/2023] [Accepted: 04/28/2023] [Indexed: 05/08/2023]
Abstract
Cathepsin H (CatH) is a lysosomal cysteine protease with a unique aminopeptidase activity that is extensively expressed in the lung, pancreas, thymus, kidney, liver, skin, and brain. Owing to its specific enzymatic activity, CatH has critical effects on the regulation of biological behaviours of cancer cells and pathological processes in brain diseases. Moreover, a neutral pH level is optimal for CatH activity, so it is expected to be active in the extra-lysosomal and extracellular space. In the present review, we describe the expression, maturation, and enzymatic properties of CatH, and summarize the available experimental evidence that mechanistically links CatH to various physiological and pathological processes. Finally, we discuss the challenges and potentials of CatH inhibitors in CatH-induced disease therapy.
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Affiliation(s)
- Yanfeng Wang
- Key Laboratory of Molecular Medicine and Biotherapy, Department of Biology, School of Life Science, Beijing Institute of Technology, Beijing, 100081, China
| | - Juan Zhao
- Key Laboratory of Molecular Medicine and Biotherapy, Department of Biology, School of Life Science, Beijing Institute of Technology, Beijing, 100081, China; Aerospace Medical Center, Aerospace Center Hospital, Beijing, 100081, China
| | - Yebo Gu
- Department of Stomatology, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, 200072, China
| | - Haiping Wang
- School of Pharmaceutical Science, Nanjing Tech University, Nanjing, China
| | - Muzhou Jiang
- Department of Periodontics, Liaoning Provincial Key Laboratory of Oral Diseases, School and Hospital of Stomatology, China Medical University, Shenyang, 110002, China
| | - Shuxuan Zhao
- Key Laboratory of Molecular Medicine and Biotherapy, Department of Biology, School of Life Science, Beijing Institute of Technology, Beijing, 100081, China
| | - Hong Qing
- Key Laboratory of Molecular Medicine and Biotherapy, Department of Biology, School of Life Science, Beijing Institute of Technology, Beijing, 100081, China.
| | - Junjun Ni
- Key Laboratory of Molecular Medicine and Biotherapy, Department of Biology, School of Life Science, Beijing Institute of Technology, Beijing, 100081, China.
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Mohammadi-Motlagh HR, Sadeghalvad M, Yavari N, Primavera R, Soltani S, Chetty S, Ganguly A, Regmi S, Fløyel T, Kaur S, Mirza AH, Thakor AS, Pociot F, Yarani R. β Cell and Autophagy: What Do We Know? Biomolecules 2023; 13:biom13040649. [PMID: 37189396 DOI: 10.3390/biom13040649] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2022] [Revised: 03/27/2023] [Accepted: 03/30/2023] [Indexed: 05/17/2023] Open
Abstract
Pancreatic β cells are central to glycemic regulation through insulin production. Studies show autophagy as an essential process in β cell function and fate. Autophagy is a catabolic cellular process that regulates cell homeostasis by recycling surplus or damaged cell components. Impaired autophagy results in β cell loss of function and apoptosis and, as a result, diabetes initiation and progress. It has been shown that in response to endoplasmic reticulum stress, inflammation, and high metabolic demands, autophagy affects β cell function, insulin synthesis, and secretion. This review highlights recent evidence regarding how autophagy can affect β cells' fate in the pathogenesis of diabetes. Furthermore, we discuss the role of important intrinsic and extrinsic autophagy modulators, which can lead to β cell failure.
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Affiliation(s)
- Hamid-Reza Mohammadi-Motlagh
- Medical Biology Research Center, Health Technology Institute, Kermanshah University of Medical Sciences, Kermanshah 67155-1616, Iran
| | - Mona Sadeghalvad
- Department of Immunology, School of Medicine, Tehran University of Medical Sciences, Tehran 1416634793, Iran
| | - Niloofar Yavari
- Department of Cellular and Molecular Medicine, The Panum Institute, Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark
| | - Rosita Primavera
- Interventional Regenerative Innovation at Stanford (IRIS), Department of Radiology, Stanford University School of Medicine, Palo Alto, CA 94304, USA
| | - Setareh Soltani
- Clinical Research Development Center, Taleghani and Imam Ali Hospital, Kermanshah University of Medical Sciences, Kermanshah 67145-1673, Iran
| | - Shashank Chetty
- Interventional Regenerative Innovation at Stanford (IRIS), Department of Radiology, Stanford University School of Medicine, Palo Alto, CA 94304, USA
| | - Abantika Ganguly
- Interventional Regenerative Innovation at Stanford (IRIS), Department of Radiology, Stanford University School of Medicine, Palo Alto, CA 94304, USA
| | - Shobha Regmi
- Interventional Regenerative Innovation at Stanford (IRIS), Department of Radiology, Stanford University School of Medicine, Palo Alto, CA 94304, USA
| | - Tina Fløyel
- Translational Type 1 Diabetes Research, Department of Clinical Research, Steno Diabetes Center Copenhagen, 2730 Herlev, Denmark
| | - Simranjeet Kaur
- Translational Type 1 Diabetes Research, Department of Clinical Research, Steno Diabetes Center Copenhagen, 2730 Herlev, Denmark
| | - Aashiq H Mirza
- Translational Type 1 Diabetes Research, Department of Clinical Research, Steno Diabetes Center Copenhagen, 2730 Herlev, Denmark
- Department of Pharmacology, Weill Cornell Medicine, New York, NY 10065, USA
| | - Avnesh S Thakor
- Interventional Regenerative Innovation at Stanford (IRIS), Department of Radiology, Stanford University School of Medicine, Palo Alto, CA 94304, USA
| | - Flemming Pociot
- Translational Type 1 Diabetes Research, Department of Clinical Research, Steno Diabetes Center Copenhagen, 2730 Herlev, Denmark
- Institute for Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark
| | - Reza Yarani
- Interventional Regenerative Innovation at Stanford (IRIS), Department of Radiology, Stanford University School of Medicine, Palo Alto, CA 94304, USA
- Translational Type 1 Diabetes Research, Department of Clinical Research, Steno Diabetes Center Copenhagen, 2730 Herlev, Denmark
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Cathepsin H Knockdown Reverses Radioresistance of Hepatocellular Carcinoma via Metabolic Switch Followed by Apoptosis. Int J Mol Sci 2023; 24:ijms24065257. [PMID: 36982347 PMCID: PMC10049059 DOI: 10.3390/ijms24065257] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Accepted: 03/01/2023] [Indexed: 03/12/2023] Open
Abstract
Despite the wide application of radiotherapy in HCC, radiotherapy efficacy is sometimes limited due to radioresistance. Although radioresistance is reported with high glycolysis, the underlying mechanism between radioresistance and cancer metabolism, as well as the role of cathepsin H (CTSH) within it, remain unclear. In this study, tumor-bearing models and HCC cell lines were used to observe the effect of CTSH on radioresistance. Proteome mass spectrometry, followed by enrichment analysis, were used to investigate the cascades and targets regulated by CTSH. Technologies such as immunofluorescence co-localization flow cytometry and Western blot were used for further detection and verification. Through these methods, we originally found CTSH knockdown (KD) perturbed aerobic glycolysis and enhanced aerobic respiration, and thus promoted apoptosis through up-regulation and the release of proapoptotic factors such as AIFM1, HTRA2, and DIABLO, consequently reducing radioresistance. We also found that CTSH, together with its regulatory targets (such as PFKL, HK2, LDH, and AIFM1), was correlated with tumorigenesis and poor prognosis. In summary, our study found that the cancer metabolic switch and apoptosis were regulated by CTSH signaling, leading to the occurrence of radioresistance in HCC cells and suggesting the potential value of HCC diagnosis and therapy.
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Cathepsin C Regulates Cytokine-Induced Apoptosis in β-Cell Model Systems. Genes (Basel) 2021; 12:genes12111694. [PMID: 34828301 PMCID: PMC8622156 DOI: 10.3390/genes12111694] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Revised: 10/14/2021] [Accepted: 10/22/2021] [Indexed: 11/17/2022] Open
Abstract
Emerging evidence suggests that several of the lysosomal cathepsin proteases are genetically associated with type 1 diabetes (T1D) and participate in immune-mediated destruction of the pancreatic β cells. We previously reported that the T1D candidate gene cathepsin H is downregulated by pro-inflammatory cytokines in human pancreatic islets and regulates β-cell function, apoptosis, and disease progression in children with new-onset T1D. In the present study, the objective was to investigate the expression patterns of all 15 known cathepsins in β-cell model systems and examine their role in the regulation of cytokine-induced apoptosis. Real-time qPCR screening of the cathepsins in human islets, 1.1B4 and INS-1E β-cell models identified several cathepsins that were expressed and regulated by pro-inflammatory cytokines. Using small interfering RNAs to knock down (KD) the cytokine-regulated cathepsins, we identified an anti-apoptotic function of cathepsin C as KD increased cytokine-induced apoptosis. KD of cathepsin C correlated with increased phosphorylation of JNK and p38 mitogen-activated protein kinases, and elevated chemokine CXCL10/IP-10 expression. This study suggests that cathepsin C is a modulator of β-cell survival, and that immune modulation of cathepsin expression in islets may contribute to immune-mediated β-cell destruction in T1D.
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Wang Z, Gu Y, Sun Y, Xu Y, Zhang M, Jiang T. Analysis of Communal Molecular Mechanism and Potential Therapeutic Targets in Heart Failure and Type 2 Diabetes Mellitus. Int J Gen Med 2021; 14:6549-6561. [PMID: 34675622 PMCID: PMC8518481 DOI: 10.2147/ijgm.s325339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Accepted: 09/29/2021] [Indexed: 11/23/2022] Open
Abstract
Background Although increasing evidence has suggested an interaction between heart failure (HF) and Type 2 diabetes mellitus (T2DM), the common mechanisms of the two diseases remain unclear. Therefore, this study aimed to obtain the differentially expressed genes (DEGs) and potential biomarkers or therapeutic targets in HF and T2DM. Methods The communal DEGs of HF and T2DM were identified by analyzing the two microarray datasets (GSE84796 and GSE95849), and functional annotation was performed for the communal DEGs to uncover the potential molecular mechanisms of HF and T2DM. Subsequently, STRING database and Cytoscape software were used to construct the protein-protein interaction (PPI) network and screen the hub genes. Finally, co-expression and drug-gene interaction prediction analysis and mRNA-miRNA regulatory network analysis were performed for hub genes. Results A total of 233 up-regulated genes and 3 down-regulated genes were found between HF and T2DM. The functional enrichment of DEGs and genes in each four modules were mainly involved in immunity. In addition, five hub genes were identified from PPI network, including SYK, SELL, RAC2, TLR8 and ITGAX. Conclusion The communal DEGs and hub genes identified in this research contribute to discover the underlying biological mechanisms and presents potential biomarkers or therapeutic targets in HF and T2DM.
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Affiliation(s)
- Zuoxiang Wang
- Department of Cardiology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, People's Republic of China.,Department of Medicine, Soochow University, Suzhou, Jiangsu, People's Republic of China
| | - Yiyu Gu
- Department of Cardiology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, People's Republic of China.,Department of Medicine, Soochow University, Suzhou, Jiangsu, People's Republic of China
| | - Yunjuan Sun
- Department of Cardiology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, People's Republic of China
| | - Yinan Xu
- Department of Cardiology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, People's Republic of China.,Department of Medicine, Soochow University, Suzhou, Jiangsu, People's Republic of China
| | - Mingyang Zhang
- Department of Cardiology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, People's Republic of China.,Department of Medicine, Soochow University, Suzhou, Jiangsu, People's Republic of China
| | - Tingbo Jiang
- Department of Cardiology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, People's Republic of China
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Kang J, Kwon EJ, Ha M, Lee H, Yu Y, Kang JW, Kim Y, Lee EY, Joo JY, Heo HJ, Kim EK, Kim TW, Kim YH, Park HR. Identification of Shared Genes and Pathways in Periodontitis and Type 2 Diabetes by Bioinformatics Analysis. Front Endocrinol (Lausanne) 2021; 12:724278. [PMID: 35145474 PMCID: PMC8822582 DOI: 10.3389/fendo.2021.724278] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Accepted: 12/20/2021] [Indexed: 01/06/2023] Open
Abstract
INTRODUCTION It is well known that the presence of diabetes significantly affects the progression of periodontitis and that periodontitis has negative effects on diabetes and diabetes-related complications. Although this two-way relationship between type 2 diabetes and periodontitis could be understood through experimental and clinical studies, information on common genetic factors would be more useful for the understanding of both diseases and the development of treatment strategies. MATERIALS AND METHODS Gene expression data for periodontitis and type 2 diabetes were obtained from the Gene Expression Omnibus database. After preprocessing of data to reduce heterogeneity, differentially expressed genes (DEGs) between disease and normal tissue were identified using a linear regression model package. Gene ontology and Kyoto encyclopedia of genes and genome pathway enrichment analyses were conducted using R package 'vsn'. A protein-protein interaction network was constructed using the search tool for the retrieval of the interacting genes database. We used molecular complex detection for optimal module selection. CytoHubba was used to identify the highest linkage hub gene in the network. RESULTS We identified 152 commonly DEGs, including 125 upregulated and 27 downregulated genes. Through common DEGs, we constructed a protein-protein interaction and identified highly connected hub genes. The hub genes were up-regulated in both diseases and were most significantly enriched in the Fc gamma R-mediated phagocytosis pathway. DISCUSSION We have identified three up-regulated genes involved in Fc gamma receptor-mediated phagocytosis, and these genes could be potential therapeutic targets in patients with periodontitis and type 2 diabetes.
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Affiliation(s)
- Junho Kang
- Medical Research Institute, Pusan National University, Busan, South Korea
| | - Eun Jung Kwon
- Interdisciplinary Program of Genomic Data Science, Pusan National University, Busan, South Korea
| | - Mihyang Ha
- Interdisciplinary Program of Genomic Data Science, Pusan National University, Busan, South Korea
| | - Hansong Lee
- Interdisciplinary Program of Genomic Data Science, Pusan National University, Busan, South Korea
| | - Yeuni Yu
- Interdisciplinary Program of Genomic Data Science, Pusan National University, Busan, South Korea
| | - Ji Wan Kang
- Interdisciplinary Program of Genomic Data Science, Pusan National University, Busan, South Korea
| | - Yeongjoo Kim
- Interdisciplinary Program of Genomic Data Science, Pusan National University, Busan, South Korea
| | - Eun Young Lee
- Department of Oral Pathology, School of Dentistry, Pusan National University, Yangsan, South Korea
| | - Ji-Young Joo
- Department of Periodontology, School of Dentistry, Pusan National University, Yangsan, South Korea
| | - Hye Jin Heo
- Departmment of Anatomy, School of Medicine, Pusan National University, Yangsan, South Korea
| | - Eun Kyoung Kim
- Departmment of Anatomy, School of Medicine, Pusan National University, Yangsan, South Korea
| | - Tae Woo Kim
- Department of Orthopaedic Surgery, Pusan National University Yangsan Hospital, School of Medicine, Pusan National University, Yangsan, South Korea
| | - Yun Hak Kim
- Departmment of Anatomy, School of Medicine, Pusan National University, Yangsan, South Korea
- Department of Biomedical Informatics, School of Medicine, Pusan National University, Yangsan, South Korea
- *Correspondence: Yun Hak Kim, ; Hae Ryoun Park,
| | - Hae Ryoun Park
- Department of Oral Pathology, School of Dentistry, Pusan National University, Yangsan, South Korea
- *Correspondence: Yun Hak Kim, ; Hae Ryoun Park,
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Ye J, Stefan-Lifshitz M, Tomer Y. Genetic and environmental factors regulate the type 1 diabetes gene CTSH via differential DNA methylation. J Biol Chem 2021; 296:100774. [PMID: 33992646 PMCID: PMC8191311 DOI: 10.1016/j.jbc.2021.100774] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2020] [Revised: 05/05/2021] [Accepted: 05/12/2021] [Indexed: 12/13/2022] Open
Abstract
Cathepsin H (CTSH) is a type 1 diabetes (T1D) risk gene; large-scale genetic and epidemiological studies found that T1D genetic risk correlates with high CTSH expression, rapid decline of beta-cell function, and early onset T1D. Counterintuitively, transcriptional downregulation of CTSH by proinflammatory cytokines has been shown to promote beta-cell apoptosis. Here, we potentially explain these observed contrasting effects, describing a new mechanism where proinflammatory cytokines and T1D genetic risk variants regulate CTSH transcription via differential DNA methylation. We show that, in human islets, CTSH downregulation by the proinflammatory cytokine cocktail interleukin 1β + tumor necrosis factor α + interferon γ was coupled with DNA hypermethylation in an open chromatin region in CTSH intron 1. A luciferase assay in human embryonic kidney 293 cells revealed that methylation of three key cytosine-phosphate-guanine dinucleotide (CpG) residues in intron 1 was responsible for the reduction of promoter activity. We further found that cytokine-induced intron 1 hypermethylation is caused by lowered Tet1/3 activities, suggesting that attenuated active demethylation lowered CTSH transcription. Importantly, individuals who carry the T1D risk variant showed lower methylation variability at the intron 1 CpG residues, presumably making them less sensitive to cytokines, whereas individuals who carry the protective variant showed higher methylation variability, presumably making them more sensitive to cytokines and implying differential responses to environment between the two patient populations. These findings suggest that genetic and environmental influences on a T1D locus are mediated by differential variability and mean of DNA methylation.
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Affiliation(s)
- Jody Ye
- Division of Endocrinology, Department of Medicine, Albert Einstein College of Medicine, Bronx, New York, USA.
| | - Mihaela Stefan-Lifshitz
- Division of Endocrinology, Department of Medicine, Albert Einstein College of Medicine, Bronx, New York, USA
| | - Yaron Tomer
- Division of Endocrinology, Department of Medicine, Albert Einstein College of Medicine, Bronx, New York, USA
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