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Differentially expressed genes in systemic sclerosis: Towards predictive medicine with new molecular tools for clinicians. Autoimmun Rev 2023; 22:103314. [PMID: 36918090 DOI: 10.1016/j.autrev.2023.103314] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Accepted: 03/09/2023] [Indexed: 03/13/2023]
Abstract
Systemic sclerosis (SSc) is a rare and chronic autoimmune disease characterized by a pathogenic triad of immune dysregulation, vasculopathy, and progressive fibrosis. Clinical tools commonly used to assess patients, such as the modified Rodnan skin score, difference between limited or diffuse forms of skin involvement, presence of lung, heart or kidney involvement, or of various autoantibodies, are important prognostic factors, but still fail to reflect the large heterogeneity of the disease. SSc treatment options are diverse, ranging from conventional drugs to autologous hematopoietic stem cell transplantation, and predicting response is challenging. Genome-wide technologies, such as high throughput microarray analyses and RNA sequencing, allow accurate, unbiased, and broad assessment of alterations in expression levels of multiple genes. In recent years, many studies have shown robust changes in the gene expression profiles of SSc patients compared to healthy controls, mainly in skin tissues and peripheral blood cells. The objective analysis of molecular patterns in SSc is a powerful tool that can further classify SSc patients with similar clinical phenotypes and help predict response to therapy. In this review, we describe the journey from the first discovery of differentially expressed genes to the identification of enriched pathways and intrinsic subsets identified in SSc, using machine learning algorithms. Finally, we discuss the use of these new tools to predict the efficacy of various treatments, including stem cell transplantation. We suggest that the use of RNA gene expression-based classifications according to molecular subsets may bring us one step closer to precision medicine in Systemic Sclerosis.
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Roberson ED, Carns M, Cao L, Aren K, Goldberg IA, Morales-Heil DJ, Korman BD, Atkinson JP, Varga J. Alterations of the Primary Cilia Gene SPAG17 and SOX9 Locus Noncoding RNAs Identified by RNA-Sequencing Analysis in Patients With Systemic Sclerosis. Arthritis Rheumatol 2023; 75:108-119. [PMID: 35762854 PMCID: PMC10445493 DOI: 10.1002/art.42281] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Revised: 05/12/2022] [Accepted: 06/23/2022] [Indexed: 02/04/2023]
Abstract
OBJECTIVE Systemic sclerosis (SSc) is characterized by immune activation, vasculopathy, and unresolving fibrosis in the skin, lungs, and other organs. We performed RNA-sequencing analysis on skin biopsy samples and peripheral blood mononuclear cells (PBMCs) from SSc patients and unaffected controls to better understand the pathogenesis of SSc. METHODS We analyzed these data 1) to test for case/control differences and 2) to identify genes whose expression levels correlate with SSc severity as measured by local skin score, modified Rodnan skin thickness score (MRSS), forced vital capacity (FVC), or diffusing capacity for carbon monoxide (DLco). RESULTS We found that PBMCs from SSc patients showed a strong type I interferon signature. This signal was found to be replicated in the skin, with additional signals for increased extracellular matrix (ECM) genes, classical complement pathway activation, and the presence of B cells. Notably, we observed a marked decrease in the expression of SPAG17, a cilia component, in SSc skin. We identified genes that correlated with the MRSS, DLco, and FVC in SSc PBMCs and skin using weighted gene coexpression network analysis. These genes were largely distinct from the case/control differentially expressed genes. In PBMCs, type I interferon signatures negatively correlated with the DLco. In SSc skin, ECM gene expression positively correlated with the MRSS. Network analysis of SSc skin genes that correlated with clinical features identified the noncoding RNAs SOX9-AS1 and ROCR, both near the SOX9 locus, as highly connected, "hub-like" genes in the network. CONCLUSION These results identify noncoding RNAs and SPAG17 as novel factors potentially implicated in the pathogenesis of SSc.
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Affiliation(s)
- Elisha D.O. Roberson
- Department of Medicine, Division of Rheumatology, Washington University, St. Louis, MO, USA
- Department of Genetics, Washington University, St. Louis, MO, USA
| | - Mary Carns
- Feinberg School of Medicine, Scleroderma Program, Northwestern University, Chicago, IL, USA
| | - Li Cao
- Department of Medicine, Division of Rheumatology, Washington University, St. Louis, MO, USA
| | - Kathleen Aren
- Feinberg School of Medicine, Scleroderma Program, Northwestern University, Chicago, IL, USA
| | - Isaac A. Goldberg
- Feinberg School of Medicine, Scleroderma Program, Northwestern University, Chicago, IL, USA
| | - David J. Morales-Heil
- Department of Medicine, Division of Rheumatology, Washington University, St. Louis, MO, USA
| | - Benjamin D. Korman
- Feinberg School of Medicine, Scleroderma Program, Northwestern University, Chicago, IL, USA
| | - John P. Atkinson
- Department of Medicine, Division of Rheumatology, Washington University, St. Louis, MO, USA
| | - John Varga
- Feinberg School of Medicine, Scleroderma Program, Northwestern University, Chicago, IL, USA
- Department of Internal Medicine, Division of Rheumatology, University of Michigan, Ann Arbor, MI, USA
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Abstract
From the clinical standpoint, systemic sclerosis (SSc) is characterized by skin and internal organ fibrosis, diffuse fibroproliferative vascular modifications, and autoimmunity. Clinical presentation and course are highly heterogenous and life expectancy variably affected mostly dependent on lung and heart involvement. SSc touches more women than men with differences in disease severity and environmental exposure. Pathogenetic events originate from altered homeostasis favored by genetic predisposition, environmental cues and a variety of endogenous and exogenous triggers. Epigenetic modifications modulate SSc pathogenesis which strikingly associate profound immune-inflammatory dysregulation, abnormal endothelial cell behavior, and cell trans-differentiation into myofibroblasts. SSc myofibroblasts show enhanced survival and enhanced extracellular matrix deposition presenting altered structure and altered physicochemical properties. Additional cell types of likely pathogenic importance are pericytes, platelets, and keratinocytes in conjunction with their relationship with vessel wall cells and fibroblasts. In SSc, the profibrotic milieu is favored by cell signaling initiated in the one hand by transforming growth factor-beta and related cytokines and in the other hand by innate and adaptive type 2 immune responses. Radical oxygen species and invariant receptors sensing danger participate to altered cell behavior. Conventional and SSc-specific T cell subsets modulate both fibroblasts as well as endothelial cell dysfunction. Beside autoantibodies directed against ubiquitous antigens important for enhanced clinical classification, antigen-specific agonistic autoantibodies may have a pathogenic role. Recent studies based on single-cell RNAseq and multi-omics approaches are revealing unforeseen heterogeneity in SSc cell differentiation and functional states. Advances in system biology applied to the wealth of data generated by unbiased screening are allowing to subgroup patients based on distinct pathogenic mechanisms. Deciphering heterogeneity in pathogenic mechanisms will pave the way to highly needed personalized therapeutic approaches.
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Baker Frost D, da Silveira W, Hazard ES, Atanelishvili I, Wilson RC, Flume J, Day KL, Oates JC, Bogatkevich GS, Feghali-Bostwick C, Hardiman G, Ramos PS. Differential DNA Methylation Landscape in Skin Fibroblasts from African Americans with Systemic Sclerosis. Genes (Basel) 2021; 12:129. [PMID: 33498390 PMCID: PMC7909410 DOI: 10.3390/genes12020129] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Revised: 01/15/2021] [Accepted: 01/18/2021] [Indexed: 01/20/2023] Open
Abstract
The etiology and reasons underlying the ethnic disparities in systemic sclerosis (SSc) remain unknown. African Americans are disproportionally affected by SSc and yet are underrepresented in research. The aim of this study was to comprehensively investigate the association of DNA methylation levels with SSc in dermal fibroblasts from patients of African ancestry. Reduced representation bisulfite sequencing (RRBS) was performed on primary dermal fibroblasts from 15 SSc patients and 15 controls of African ancestry, and over 3.8 million CpG sites were tested for differential methylation patterns between cases and controls. The dermal fibroblasts from African American patients exhibited widespread reduced DNA methylation. Differentially methylated CpG sites were most enriched in introns and intergenic regions while depleted in 5' UTR, promoters, and CpG islands. Seventeen genes and eleven promoters showed significant differential methylation, mostly in non-coding RNA genes and pseudogenes. Gene set enrichment analysis (GSEA) and gene ontology (GO) analyses revealed an enrichment of pathways related to interferon signaling and mesenchymal differentiation. The hypomethylation of DLX5 and TMEM140 was accompanied by these genes' overexpression in patients but underexpression for lncRNA MGC12916. These data show that differential methylation occurs in dermal fibroblasts from African American patients with SSc and identifies novel coding and non-coding genes.
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Affiliation(s)
- DeAnna Baker Frost
- Department of Medicine, Division of Rheumatology and Immunology, Medical University of South Carolina, Charleston, SC 29425, USA; (D.B.F.); (I.A.); (J.F.); (J.C.O.); (G.S.B.); (C.F.-B.)
| | - Willian da Silveira
- Institute for Global Food Security, School of Biological Sciences, Queens University Belfast, Belfast BT9 5DL, UK; (W.d.S.); (G.H.)
| | - E. Starr Hazard
- Computational Biology Resource Center, Medical University of South Carolina, Charleston, SC 29425, USA;
| | - Ilia Atanelishvili
- Department of Medicine, Division of Rheumatology and Immunology, Medical University of South Carolina, Charleston, SC 29425, USA; (D.B.F.); (I.A.); (J.F.); (J.C.O.); (G.S.B.); (C.F.-B.)
| | - Robert C. Wilson
- Department of Pathology and Laboratory Medicine, Medical University of South Carolina, Charleston, SC 29425, USA;
| | - Jonathan Flume
- Department of Medicine, Division of Rheumatology and Immunology, Medical University of South Carolina, Charleston, SC 29425, USA; (D.B.F.); (I.A.); (J.F.); (J.C.O.); (G.S.B.); (C.F.-B.)
| | | | - James C. Oates
- Department of Medicine, Division of Rheumatology and Immunology, Medical University of South Carolina, Charleston, SC 29425, USA; (D.B.F.); (I.A.); (J.F.); (J.C.O.); (G.S.B.); (C.F.-B.)
- Rheumatology Section, Ralph H. Johnson VA Medical Center, Charleston, SC 29425, USA
| | - Galina S. Bogatkevich
- Department of Medicine, Division of Rheumatology and Immunology, Medical University of South Carolina, Charleston, SC 29425, USA; (D.B.F.); (I.A.); (J.F.); (J.C.O.); (G.S.B.); (C.F.-B.)
| | - Carol Feghali-Bostwick
- Department of Medicine, Division of Rheumatology and Immunology, Medical University of South Carolina, Charleston, SC 29425, USA; (D.B.F.); (I.A.); (J.F.); (J.C.O.); (G.S.B.); (C.F.-B.)
| | - Gary Hardiman
- Institute for Global Food Security, School of Biological Sciences, Queens University Belfast, Belfast BT9 5DL, UK; (W.d.S.); (G.H.)
| | - Paula S. Ramos
- Department of Medicine, Division of Rheumatology and Immunology, Medical University of South Carolina, Charleston, SC 29425, USA; (D.B.F.); (I.A.); (J.F.); (J.C.O.); (G.S.B.); (C.F.-B.)
- Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC 29425, USA
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Mehta BK, Espinoza ME, Hinchcliff M, Whitfield ML. Molecular "omic" signatures in systemic sclerosis. Eur J Rheumatol 2020; 7:S173-S180. [PMID: 33164732 DOI: 10.5152/eurjrheum.2020.19192] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2019] [Accepted: 03/05/2020] [Indexed: 01/15/2023] Open
Abstract
Systemic sclerosis (SSc) is a connective tissue disorder characterized by immunologic, vascular, and extracellular matrix abnormalities. Variation in the proportion and/or timing of activation in the deregulated molecular pathways that underlie SSc may explain the observed clinical heterogeneity in terms of disease phenotype and treatment response. In recent years, SSc research has generated massive amounts of "omics" level data. In this review, we discuss the body of "omics" level work in SSc and how each layer provides unique insight to our understanding of SSc. We posit that effective integration of genomic, transcriptomic, metagenomic, and epigenomic data is an important step toward precision medicine and is vital to the identification of effective therapeutic options for patients with SSc.
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Affiliation(s)
- Bhaven K Mehta
- Department of Molecular and Systems Biology, Geisel School of Medicine at Dartmouth, Hanover, NH, USA
| | - Monica E Espinoza
- Department of Molecular and Systems Biology, Geisel School of Medicine at Dartmouth, Hanover, NH, USA
| | - Monique Hinchcliff
- Department of Rheumatology, Allergy & Immunology, Yale School of Medicine, New Haven, CT, USA
| | - Michael L Whitfield
- Department of Molecular and Systems Biology, Geisel School of Medicine at Dartmouth, Hanover, NH, USA.,Department of Biomedical Data Science, Dartmouth College, Hanover, NH, USA
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Distler JHW, Györfi AH, Ramanujam M, Whitfield ML, Königshoff M, Lafyatis R. Shared and distinct mechanisms of fibrosis. Nat Rev Rheumatol 2019; 15:705-730. [DOI: 10.1038/s41584-019-0322-7] [Citation(s) in RCA: 197] [Impact Index Per Article: 39.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/03/2019] [Indexed: 02/07/2023]
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Xu C, Meng LB, Duan YC, Cheng YJ, Zhang CM, Zhou X, Huang CB. Screening and identification of biomarkers for systemic sclerosis via microarray technology. Int J Mol Med 2019; 44:1753-1770. [PMID: 31545397 PMCID: PMC6777682 DOI: 10.3892/ijmm.2019.4332] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2019] [Accepted: 08/13/2019] [Indexed: 12/25/2022] Open
Abstract
Systemic sclerosis (SSc) is a complex autoimmune disease. The pathogenesis of SSc is currently unclear, although like other rheumatic diseases its pathogenesis is complicated. However, the ongoing development of bioinformatics technology has enabled new approaches to research this disease using microarray technology to screen and identify differentially expressed genes (DEGs) in the skin of patients with SSc compared with individuals with healthy skin. Publicly available data were downloaded from the Gene Expression Omnibus (GEO) database and intra-group data repeatability tests were conducted using Pearson's correlation test and principal component analysis. DEGs were identified using an online tool, GEO2R. Functional annotation of DEGs was performed using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Finally, the construction and analysis of the protein-protein interaction (PPI) network and identification and analysis of hub genes was carried out. A total of 106 DEGs were detected by the screening of SSc and healthy skin samples. A total of 10 genes [interleukin-6, bone morphogenetic protein 4, calumenin (CALU), clusterin, cysteine rich angiogenic inducer 61, serine protease 23, secretogranin II, suppressor of cytokine signaling 3, Toll-like receptor 4 (TLR4), tenascin C] were identified as hub genes with degrees ≥10, and which could sensitively and specifically predict SSc based on receiver operator characteristic curve analysis. GO and KEGG analysis showed that variations in hub genes were mainly enriched in positive regulation of nitric oxide biosynthetic processes, negative regulation of apoptotic processes, extracellular regions, extracellular spaces, cytokine activity, chemo-attractant activity, and the phosphoinositide 3 kinase-protein kinase B signaling pathway. In summary, bioinformatics techniques proved useful for the screening and identification of biomarkers of disease. A total of 106 DEGs and 10 hub genes were linked to SSc, in particular the TLR4 and CALU genes.
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Affiliation(s)
- Chen Xu
- Department of Rheumatology, Beijing Hospital, National Center of Gerontology, Beijing 100730, P.R. China
| | - Ling-Bing Meng
- Department of Neurology, Beijing Hospital, National Center of Gerontology, Beijing 100730, P.R. China
| | - Yu-Chen Duan
- Department of Rheumatology, Beijing Hospital, National Center of Gerontology, Beijing 100730, P.R. China
| | - Yong-Jing Cheng
- Department of Rheumatology, Beijing Hospital, National Center of Gerontology, Beijing 100730, P.R. China
| | - Chun-Mei Zhang
- Department of Rheumatology, Beijing Hospital, National Center of Gerontology, Beijing 100730, P.R. China
| | - Xing Zhou
- Department of Rheumatology, Beijing Hospital, National Center of Gerontology, Beijing 100730, P.R. China
| | - Ci-Bo Huang
- Department of Rheumatology, Beijing Hospital, National Center of Gerontology, Beijing 100730, P.R. China
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Wermuth PJ, Piera-Velazquez S, Rosenbloom J, Jimenez SA. Existing and novel biomarkers for precision medicine in systemic sclerosis. Nat Rev Rheumatol 2019; 14:421-432. [PMID: 29789665 DOI: 10.1038/s41584-018-0021-9] [Citation(s) in RCA: 42] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
The discovery and validation of biomarkers resulting from technological advances in the analysis of genomic, transcriptomic, lipidomic and metabolomic pathways involved in the pathogenesis of complex human diseases have led to the development of personalized and rationally designed approaches for the clinical management of such disorders. Although some of these approaches have been applied to systemic sclerosis (SSc), an unmet need remains for validated, non-invasive biomarkers to aid in the diagnosis of SSc, as well as in the assessment of disease progression and response to therapeutic interventions. Advances in global transcriptomic technology over the past 15 years have enabled the assessment of microRNAs that circulate in the blood of patients and the analysis of the macromolecular content of a diverse group of lipid bilayer membrane-enclosed extracellular vesicles, such as exosomes and other microvesicles, which are released by all cells into the extracellular space and circulation. Such advances have provided new opportunities for the discovery of biomarkers in SSc that could potentially be used to improve the design and evaluation of clinical trials and that will undoubtedly enable the development of personalized and individualized medicine for patients with SSc.
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Affiliation(s)
- Peter J Wermuth
- Jefferson Institute of Molecular Medicine, Thomas Jefferson University, Philadelphia, PA, USA.,The Joan and Joel Rosenbloom Center for Fibrosis Research, Thomas Jefferson University, Philadelphia, PA, USA
| | - Sonsoles Piera-Velazquez
- Jefferson Institute of Molecular Medicine, Thomas Jefferson University, Philadelphia, PA, USA.,The Joan and Joel Rosenbloom Center for Fibrosis Research, Thomas Jefferson University, Philadelphia, PA, USA
| | - Joel Rosenbloom
- Jefferson Institute of Molecular Medicine, Thomas Jefferson University, Philadelphia, PA, USA.,The Joan and Joel Rosenbloom Center for Fibrosis Research, Thomas Jefferson University, Philadelphia, PA, USA
| | - Sergio A Jimenez
- Jefferson Institute of Molecular Medicine, Thomas Jefferson University, Philadelphia, PA, USA. .,The Joan and Joel Rosenbloom Center for Fibrosis Research, Thomas Jefferson University, Philadelphia, PA, USA. .,The Scleroderma Center, Thomas Jefferson University, Philadelphia, PA, USA.
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Shi K, Li N, Yang M, Li W. Identification of Key Genes and Pathways in Female Lung Cancer Patients Who Never Smoked by a Bioinformatics Analysis. J Cancer 2019; 10:51-60. [PMID: 30662525 PMCID: PMC6329865 DOI: 10.7150/jca.26908] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2018] [Accepted: 10/17/2018] [Indexed: 01/10/2023] Open
Abstract
Smoking is considered the major risk factor for lung cancer, but only a small portion of female lung adenocarcinoma patients are associated with smoking. Thus, identifying crucial genes and pathways related to nonsmoking female lung cancer patients is of great importance. Gene expression profiles were downloaded from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) databases. The R software packages were applied to screen the differentially expressed genes (DEGs). GO term enrichment and KEGG pathway analyses were carried out using DAVID tools. The protein-protein interaction (PPI) network was constructed by Cytoscape software. In total, 487 downregulated and 199 upregulated DEGs were identified. The down-regulated DEGs were mainly enriched for behavior and response to wounding, and the upregulated DEGs were significantly enriched for multicellular organismal metabolic process and cell division. The KEGG pathway analysis revealed that the downregulated DEGs were significantly enriched for cell adhesion molecules and neuroactive ligand-receptor interaction, while the upregulated DEGs were mainly enriched for cell cycle and the p53 signaling pathway. The top 10 hub genes and top 3 gene interaction modules were selected from the PPI network. Of the ten hub genes, a high expression of five genes was related to a poor OS in female lung cancer patients who never smoked, including IL6, CXCR2, FPR2, PPBP and HBA1. However, a low expression of GNG11, LRRK2, CDH5, CAV1 and SELE was associated with a worse OS for the female lung cancer patients who never smoked. In conclusion, our study provides novel insight for a better understanding of the pathogenesis of nonsmoking female lung cancer, and these identified DEGs may serve as biomarkers for diagnostics and treatment.
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Affiliation(s)
- Ke Shi
- Department of Geriatrics, Clinical Laboratory, Xiangya Hospital of Central South University, Changsha, People's Republic of China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital of Central South University, Changsha, People's Republic of China
| | - Na Li
- Department of Pathology, the First Affiliated Hospital of Hunan University of Medicine, Huaihua, People's Republic of China
| | - Meilan Yang
- Department of Pathology, the First Affiliated Hospital of Hunan University of Medicine, Huaihua, People's Republic of China
| | - Wei Li
- Department of Geriatrics, Clinical Laboratory, Xiangya Hospital of Central South University, Changsha, People's Republic of China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital of Central South University, Changsha, People's Republic of China
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Zhu M, Wang Q, Zhou W, Liu T, Yang L, Zheng P, Zhang L, Ji G. Integrated analysis of hepatic mRNA and miRNA profiles identified molecular networks and potential biomarkers of NAFLD. Sci Rep 2018; 8:7628. [PMID: 29769539 PMCID: PMC5955949 DOI: 10.1038/s41598-018-25743-8] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2017] [Accepted: 04/24/2018] [Indexed: 12/17/2022] Open
Abstract
To enhance our understanding of molecular mechanisms and mine novel biomarkers of non-alcoholic fatty liver disease (NAFLD), RNA sequencing was performed to gain hepatic expression profiles of mRNAs and miRNAs in NAFLD and normal rats. Using DESeq with thresholds of a two-fold change and a false discovery rate (FDR) less than 0.05, 336 mRNAs and 21 miRNAs were identified as differentially expressed. Among those, 17 miRNAs (e.g., miR-144-3p, miR-99a-3p, miR-200b-3p, miR-200b-5p, miR-200c-3p, etc.) might serve as novel biomarkers of NAFLD. MiRNA target genes (13565) were predicted by the miRWalk database. Using DAVID 6.8, the intersection (195 genes) of differentially expressed mRNAs and miRNA-predicted target genes were enriched in 47 gene ontology (GO) terms and 28 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Using Cytoscape, pathway interaction and protein-protein interaction (PPI) networks were constructed, and hub genes (e.g., Abcg8, Cyp1a1, Cyp51, Hmgcr, etc.) associated with NAFLD were obtained. Moreover, 673 miRNA-mRNA negative regulatory pairs were obtained, and networks were constructed. Finally, several representative miRNAs and mRNAs were validated by real-time qPCR. In conclusion, potential molecular mechanisms of NAFLD could be inferred from integrated analysis of mRNA and miRNA profiles, which may indicate novel biomarkers of NAFLD.
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Affiliation(s)
- Mingzhe Zhu
- Institute of Digestive Diseases, Longhua Hospital, China-Canada Center of Research for Digestive Diseases (ccCRDD), Shanghai University of Traditional Chinese Medicine, Shanghai, 200032, China.,School of Public Health, Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, China
| | - Qianlei Wang
- Institute of Digestive Diseases, Longhua Hospital, China-Canada Center of Research for Digestive Diseases (ccCRDD), Shanghai University of Traditional Chinese Medicine, Shanghai, 200032, China
| | - Wenjun Zhou
- Institute of Digestive Diseases, Longhua Hospital, China-Canada Center of Research for Digestive Diseases (ccCRDD), Shanghai University of Traditional Chinese Medicine, Shanghai, 200032, China
| | - Tao Liu
- Institute of Digestive Diseases, Longhua Hospital, China-Canada Center of Research for Digestive Diseases (ccCRDD), Shanghai University of Traditional Chinese Medicine, Shanghai, 200032, China
| | - Lili Yang
- Institute of Digestive Diseases, Longhua Hospital, China-Canada Center of Research for Digestive Diseases (ccCRDD), Shanghai University of Traditional Chinese Medicine, Shanghai, 200032, China
| | - Peiyong Zheng
- Institute of Digestive Diseases, Longhua Hospital, China-Canada Center of Research for Digestive Diseases (ccCRDD), Shanghai University of Traditional Chinese Medicine, Shanghai, 200032, China
| | - Li Zhang
- Institute of Digestive Diseases, Longhua Hospital, China-Canada Center of Research for Digestive Diseases (ccCRDD), Shanghai University of Traditional Chinese Medicine, Shanghai, 200032, China.
| | - Guang Ji
- Institute of Digestive Diseases, Longhua Hospital, China-Canada Center of Research for Digestive Diseases (ccCRDD), Shanghai University of Traditional Chinese Medicine, Shanghai, 200032, China.
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Pope JE, Lee JJ, Denton CP. Editorial: Bench to Bedside—and Back Again: Finding the Goldilocks Zone Within the Scleroderma Universe. Arthritis Rheumatol 2017; 70:155-156. [DOI: 10.1002/art.40373] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2017] [Accepted: 11/03/2017] [Indexed: 11/10/2022]
Affiliation(s)
- Janet E. Pope
- St. Joseph's Health Care University of Western Ontario London Ontario Canada
| | - Jason J. Lee
- University of Western Ontario London Ontario Canada
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