Gene and protein expression profiles in a mouse model of collagen-induced arthritis

Sun Yeong Gwon, Ki Jong Rhee, Ho Joong Sung

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)


The risk of rheumatoid arthritis (RA), an autoimmune disease, in the elderly population increases along with that of atherosclerosis, cardiovascular disease, type 2 diabetes, and Alzheimer’s disease. Identifying specific biomarkers for RA can clarify the underlying molecular mechanisms and can aid diagnosis and patient care. To this end, the present study investigated the genes and proteins that are differentially expressed in RA using a mouse collagen-induced arthritis (CIA) model. We performed gene microarray and proteome array analyses using blood samples from the mice and found that 50 genes and 24 proteins were upregulated and 48 genes were downregulated by more than 2-fold in the CIA model relative to the control. The gene microarray and proteome array results were validated by evaluating the expression levels of select genes and proteins by real-time PCR and western blotting, respectively. We found that the level of integrin α2, which has not been previously reported as a biomarker of RA, was significantly increased in CIA mice as compared to controls. These findings provide a set of novel biomarkers that can be useful for diagnosing and evaluating the progression of RA.

Original languageEnglish
Pages (from-to)77-85
Number of pages9
JournalInternational Journal of Medical Sciences
Issue number1
Publication statusPublished - 2018 Jan 1

Bibliographical note

Funding Information:
This research was supported by the Bio & Medical Technology Development Program of the National Research Foundation (NRF) & funded by the Korean government (MSIP&MOHW) (No. 2016M3A9B6904244).

Publisher Copyright:
© Ivyspring International Publisher.

All Science Journal Classification (ASJC) codes

  • Medicine(all)


Dive into the research topics of 'Gene and protein expression profiles in a mouse model of collagen-induced arthritis'. Together they form a unique fingerprint.

Cite this