Differentially expressed genes between systemic sclerosis and rheumatoid arthritis

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

Background

Evidence is accumulating to characterise the key differences between systemic sclerosis (SSc) and rheumatoid arthritis (RA), which are similar but distinct systemic autoimmune diseases. However, the differences at the genetic level are not yet clear. Therefore, the aim of the present study was to identify key differential genes between patients with SSc and RA.

Methods

The Gene Expression Omnibus database was used to identify differentially expressed genes (DEGs) between SSc and RA biopsies. The DEGs were then functionally annotated using Gene Ontology (GO) terms and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways with the Database for Annotation, Visualization and Integrated Discovery (DAVID) tools. A protein–protein interaction (PPI) network was constructed with Cytoscape software. The Molecular Complex Detection (MCODE) plugin was also used to evaluate the biological importance of the constructed gene modules.

Results

A total of 13,556 DEGs were identified between the five SSc patients and seven RA patients, including 13,465 up-regulated genes and 91 down-regulated genes. Interestingly, the most significantly enriched GO terms of up- and down-regulated genes were related to extracellular involvement and immune activity, respectively, and the top six highly enriched KEGG pathways were related to the same processes. In the PPI network, the top 10 hub nodes and top four modules harboured the most relevant genes contributing to the differences between SSc and RA, including key genes such as IL6, EGF, JUN, FGF2, BMP2, FOS, BMP4, LRRK2, CTNNB1, EP300, CD79, and CXCL13.

Conclusions

These genes such as IL6, EGF, JUN, FGF2, BMP2, FOS, BMP4, LRRK2, CTNNB1, EP300, CD79, and CXCL13 can serve as new targets for focused research on the distinct molecular pathogenesis of SSc and RA. Furthermore, these genes could serve as potential biomarkers for differential diagnoses or therapeutic targets for treatment.

Electronic supplementary material

The online version of this article (10.1186/s41065-019-0091-y) contains supplementary material, which is available to authorized users.

Related collections

Most cited references 33

Record: found
Abstract: found
Article: not found

DAVID: Database for Annotation, Visualization, and Integrated Discovery.

Glynn Dennis, Brad T. Sherman, Douglas A Hosack … (2003)

Functional annotation of differentially expressed genes is a necessary and critical step in the analysis of microarray data. The distributed nature of biological knowledge frequently requires researchers to navigate through numerous web-accessible databases gathering information one gene at a time. A more judicious approach is to provide query-based access to an integrated database that disseminates biologically rich information across large datasets and displays graphic summaries of functional information. Database for Annotation, Visualization, and Integrated Discovery (DAVID; http://www.david.niaid.nih.gov) addresses this need via four web-based analysis modules: 1) Annotation Tool - rapidly appends descriptive data from several public databases to lists of genes; 2) GoCharts - assigns genes to Gene Ontology functional categories based on user selected classifications and term specificity level; 3) KeggCharts - assigns genes to KEGG metabolic processes and enables users to view genes in the context of biochemical pathway maps; and 4) DomainCharts - groups genes according to PFAM conserved protein domains. Analysis results and graphical displays remain dynamically linked to primary data and external data repositories, thereby furnishing in-depth as well as broad-based data coverage. The functionality provided by DAVID accelerates the analysis of genome-scale datasets by facilitating the transition from data collection to biological meaning.

0 comments Cited 1428 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: found

Systemic sclerosis.

Christopher P. Denton, Dinesh Khanna (2017)

Systemic sclerosis, also called scleroderma, is an immune-mediated rheumatic disease that is characterised by fibrosis of the skin and internal organs and vasculopathy. Although systemic sclerosis is uncommon, it has a high morbidity and mortality. Improved understanding of systemic sclerosis has allowed better management of the disease, including improved classification and more systematic assessment and follow-up. Additionally, treatments for specific complications have emerged and a growing evidence base supports the use of immune suppression for the treatment of skin and lung fibrosis. Some manifestations of the disease, such as scleroderma renal crisis, pulmonary arterial hypertension, digital ulceration, and gastro-oesophageal reflux, are now treatable. However, the burden of non-lethal complications associated with systemic sclerosis is substantial and is likely to become more of a challenge. Here, we review the clinical features of systemic sclerosis and describe the best practice approaches for its management. Furthermore, we identify future areas for development.

0 comments Cited 735 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

Serum levels of interleukin-6 and interleukin-10 correlate with total skin thickness score in patients with systemic sclerosis.

Shinichi Sato, Minoru Hasegawa, Kazuhiko Takehara (2001)

Various growth factors and cytokines have been suggested to play a central role in initiating and developing fibrosis in systemic sclerosis (SSc). To determine which serum levels of soluble mediators are the most relevant to the degree of skin sclerosis in SSc, serum levels of various soluble mediators were examined by ELISA and correlated with skin thickening that was measured using modified Rodnan total skin thickness scoring (TSS) system. Serum levels of IL-4, IL-12, IL-13, tumor necrosis factor-alpha, connective tissue growth factor (CTGF), vascular endothelial growth factor, monocyte chemotactic protein-1, macrophage inflammatory protein-1beta, soluble IL-6 receptor, and soluble L-selectin were higher in SSc patients than normal controls. Levels of IL-6, IL-10, and CTGF in patients with diffuse cutaneous SSc were higher than patients with limited cutaneous SSc and controls. Serum levels of IL-6 and IL-10 positively correlated with TSS in patients with SSc (r=0.625, P<0.0001 and r=0.663, P<0.0001, respectively). In addition, IL-10 levels significantly correlated with pulmonary fibrosis. Thus, serum levels of IL-6 and IL-10 most strongly reflect the extent of skin thickening in SSc, suggesting that levels of IL-6 and IL-10 are useful serological indicators for skin fibrosis in SSc.

0 comments Cited 81 times – based on 0 reviews      Review now

Bookmark

All references

Author and article information

Contributors

Degang Yu: 18019790572 , ydg163@126.com

Yuanqing Mao:

ORCID: http://orcid.org/0000-0002-8469-7014

18019790572 , yuanqingmao@163.com

Journal

Journal ID (nlm-ta): Hereditas

Journal ID (iso-abbrev): Hereditas

Title: Hereditas

Publisher: BioMed Central (London )

ISSN (Print): 0018-0661

ISSN (Electronic): 1601-5223

Publication date (Electronic): 4 June 2019

Publication date PMC-release: 4 June 2019

Publication date Collection: 2019

Volume: 156

Electronic Location Identifier: 17

Affiliations

[1 ]ISNI 0000 0004 0368 8293, GRID grid.16821.3c, Shanghai Key Laboratory of Orthopaedic Implants, Department of Orthopaedic Surgery, Shanghai Ninth People’s Hospital, , Shanghai Jiao Tong University School of Medicine, ; Shanghai, China

[2 ]ISNI 0000 0004 0368 8293, GRID grid.16821.3c, Shanghai Key Laboratory of Orthopaedic Implants, Department of Orthopaedic Surgery, Shanghai Ninth People’s Hospital, , Shanghai Jiao Tong University School of Medicine, ; Shanghai, China

Author information

Yuanqing Mao http://orcid.org/0000-0002-8469-7014

Article

Publisher ID: 91

DOI: 10.1186/s41065-019-0091-y

PMC ID: 6549285

PubMed ID: 31178673

SO-VID: ded4ffae-d884-4857-b67e-6e085c9762ea

License:

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

History

Date received : 23 January 2019

Date accepted : 10 May 2019

Funding

Funded by: National Natural Science Foundation of China

Award ID: 81772361

Award Recipient : Yuanqing Mao

Custom metadata

Keywords: gene expression data,systemic sclerosis,rheumatoid arthritis,microarray,differentially expressed genes,key genes

Data availability:

Keywords: gene expression data, systemic sclerosis, rheumatoid arthritis, microarray, differentially expressed genes, key genes

Differentially expressed genes between systemic sclerosis and rheumatoid arthritis

Read this article at

Abstract

Background

Methods

Results

Conclusions

Electronic supplementary material

Related collections

Genes & Diseases

Most cited references 33

DAVID: Database for Annotation, Visualization, and Integrated Discovery.

Systemic sclerosis.

Serum levels of interleukin-6 and interleukin-10 correlate with total skin thickness score in patients with systemic sclerosis.

Author and article information

Contributors

Journal

Affiliations

Author information

Article

History

Funding

Categories

Custom metadata

Comments

Comment on this article

Similar content 56

Cited by 4

Most referenced authors 1,080