Document Type

Journal Article

Department/Unit

School of Chinese Medicine

Language

English

Abstract

This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Rheumatoid arthritis (RA) and coronary artery disease (CAD) are both complex inflammatory diseases, and an increased prevalence of CAD and a high rate of mortality have been observed in RA patients. But the molecular mechanism of inflammation that is shared between the two disorders is unclear. High-throughput techniques, such as transcriptome analysis, are becoming important tools for genetic biomarker discovery in highly complex biological samples, which is critical for the diagnosis, prognosis, and treatment of disease. In the present study, we reported one type of transcriptome analysis method: digital gene expression profiling of peripheral blood mononuclear cells of 10 RA patients, 10 CAD patients and 10 healthy people. In all, 213 and 152 differently expressed genes (DEGs) were identified in RA patients compared with normal controls (RA vs. normal) and CAD patients compared with normal controls (CAD vs. normal), respectively, with 73 shared DEGs between them. Using this technique in combination with Ingenuity Pathways Analysis software, the effects on inflammation of four shared canonical pathways, three shared activated predicted upstream regulators and three shared molecular interaction networks were identified and explored. These shared molecular mechanisms may provide the genetic basis and potential targets foroptimizing the application of current drugs to more effectively treat these diseases simultaneously and for preventing one when the other is diagnosed.

Publication Date

12-2014

Source Publication Title

PLoS ONE

Volume

9

Issue

12

Start Page

e113659

Publisher

Public Library of Science

Peer Reviewed

1

Copyright

© 2014 Niu et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funder

This study was supported by (1) International cooperation project of Ministry of science and technology (Project ID: 2014DFA31490) to Cheng Xiao, (2) Interdisciplinary Research Matching Scheme (IRMS) of Hong Kong Baptist University (Project ID: RC-IRMS/12-13/02), Research Committee of Hong Kong Baptist University (Project ID: FRG2/ 12-13/027) to Ge Zhang, and (3) Science and Technology Projects for supervisors of Beijing outstanding doctorate dissertation (Project ID: 20118450201) to Aiping Lu.

DOI

10.1371/journal.pone.0113659

ISSN (print)

19326203

ISSN (electronic)

19326203

Additional Files

JA-4984-27420_suppl.docx (73 kB)

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