Background Ankylosing spondylitis (AS) is a chronic inflammatory rheumatic diseases which mainly affects the spine and sacroiliac joint. So far, the pathogenesis of AS remains elusive, making it difficult to improve early diagnosis and treatment. Proteomics is a new enabling technology to screen disease associated proteins which can be used in diagnostics or therapeutics.

Objectives The surface-enhanced laser desorption ionization/time of flight mass spectrometry (SELDI-TOF-MS) and protein chip screening specific biomarkers in serum of patients with ankylosing spondylitis (AS) are used to diagnose and assess the disease as well as to anticipate the program of disease.

Methods The serum samples of 69 AS patients, 10 rheumatoid arthritis (RA) and 12 healthy individuals were detected by SELDI-TOF-MS and weak cation exchange (WCX-2) chip. Then 69 AS patients were divided into several types such as the active and inactive stage of illness, axial arthritis involved and peripheral and axial arthritis involved, the positive and negative group of HLA-B27 to study differentially expressed proteins in the pathogenesis of AS by using Biomarker Wizard and Biomarker Pattern software of SELDI to screen the specific proteins and set up the diagnostic prediction models of disease.

Results 1.The contents of 27 proteins between AS patients and healthy groups were significantly different. Of these proteins, 14 were up-regulated and 13 were down-regulated in patients with AS.The diagnostic model made up of 8085, 2640 and 2932 could be used to diagnose AS, which the sensitivity and specificity were 94.23% and 100% respectively.

2.The contents of 30 proteins were significantly different. Of these proteins, 14 were up-regulated and 16 were down-regulated in the active stage of AS. The diagnostic model made up of 3677, 3880, 2539, 3159 and 3242 could be used to determine the disease activity of AS, which the sensitivity and specificity were 98.11% and 100% respectively.

3.The contents of 3 proteins were significantly different. The protein of M/Z 8687 was up-regulated in the axial arthritis involved of AS, while the proteins of M/Z 4700, 18538 were down-regulated. The diagnostic model made up of the three proteins could be used to predict AS whether peripheral arthritis was involved or not, which the sensitivity and specificity were 80.00% and 82.35% respectively.

4.There were no different expressed proteins in serum between the positive and negative group of HLA-B27.

5.The contents of 23 proteins were significantly different. Of these proteins, 14 were up-regulated and 9 were down-regulated in the AS patient. The diagnostic model made up of 10259, 7972, 2048, 2154 and 2954 could be used to distinguish AS and RA, which the sensitivity and specificity were 100% and 100% respectively.

Conclusions The serum protein fingerprinting set up by SELDI-TOF-MS could screen new biomarkers in AS, which is expected to become a screening platform in diagnose and assessment of disease.

References

1. Kabeerdoss J, Kurien BT, Ganapati A, et al. Proteomics in rheumatology[J]. Int J Rheum Dis, 2015, 18(8): 815–817.

2. Li Y, Sun X, Zhang X, et al. Establishment of a decision tree model for diagnosis of early rheumatoid arthritis by proteomic finger printing[J]. Int J Rheum Dis, 2015, 18(8): 835–841.

3. Liu J, Zhu P, Peng J, et al. Identification of disease-associated proteins by proteomic approach in ankylosing spondylitis[J]. Biochem Biophys Res Commun, 2007, 357(2): 531–536.

References

Disclosure of Interest None declared