Proteomics analysis reveals differential pattern of widespread protein expression and novel role of histidine-rich glycoprotein and lipopolysaccharide-binding protein in rheumatoid arthritis.

Rheumatoid factor (RF) is an auto-antibody against antigen-antibody immune complexes. RF is valuable as a biomarker for the screening of autoimmune and infectious diseases. However, it is suggested that RF would be a more powerful biomarker when used complementarily with RF-correlated proteins. In this study, we utilized a proteomic approach to analyze global protein expression in RF-low and RF-high subjects using high-performance liquid chromatography tandem mass spectrometry. Histidine-rich glycoprotein (HRG) and lipopolysaccharide-binding protein (LBP) were found to be differentially expressed between RF-low and RF-high subjects (cut-off > 2-fold, p < 0.05), which was validated by enzyme-linked immunosorbent assay. To evaluate whether both proteins allow discriminating rheumatoid arthritis patients from healthy controls, receiver-operating characteristic (ROC) curves were analyzed. Areas under the ROC curves of HRG and LBP were 0.861 and 0.888, respectively. The correlation between RF and HRG was statistically significant (p = 0.003), and LBP was also correlated with RF (p = 0.044), as indicated by correlation analysis. HRG and LBP are reportedly involved in RF-producing and RF-correlated diseases. Thus, we propose that HRG and LBP could be useful screening markers for RF-correlated diseases.

Identification and Validation of SAA4 as a Rheumatoid Arthritis Prescreening Marker by Liquid Chromatography Tandem-mass Spectrometry.

Rheumatoid arthritis (RA) is a chronic autoimmune disease that progresses into systemic inflammation and joint deformity. RA diagnosis is a complicated procedure, and early diagnostic methods are insufficient. Therefore, in this study, we attempted to identify new markers to improve the accuracy of RA prescreening. e identified differentially expressed proteins (DEPs) by using liquid chromatography tandem-mass spectrometry in health-prescreening sera with high rheumatoid factor (RF) values, and compared the findings with those from sera with normal RF values. We identified 93 DEPs; of these, 36 were upregulated, and 57 were downregulated in high-RF sera. Pathway analysis revealed that these DEPs were related to immune responses. Additionally, four DEPs were statistically analyzed by proteomic analysis; of these, SAA4 was significantly validated in individual enzyme-linked immunosorbent assays. Moreover, SAA4 was significantly upregulated in RA patients (n = 40, 66.43 ± 12.97 ng/mL) compared with normal controls (n = 40, 4.79 ± 0.95 ng/mL) and had a higher area under the curve than C-reactive protein. Thus, we identified SAA4 as a protein that was positively correlated with RF and RA. SAA4 may represent a novel prescreening marker for the diagnosis of RA.

Proteomic analysis of serum from patients with major depressive disorder to compare their depressive and remission statuses.

OBJECTIVE: Currently, there are a few biological markers to aid in the diagnosis and treatment of depression. However, it is not sufficient for diagnosis. We attempted to identify differentially expressed proteins during depressive moods as putative diagnostic biomarkers by using quantitative proteomic analysis of serum. METHODS: Blood samples were collected twice from five patients with major depressive disorder (MDD) at depressive status before treatment and at remission status during treatment. Samples were individually analyzed by liquid chromatography-tandem mass spectrometry for protein profiling. Differentially expressed proteins were analyzed by label-free quantification. Enzyme-linked immunosorbent assay (ELISA) results and receiver-operating characteristic (ROC) curves were used to validate the differentially expressed proteins. For validation, 8 patients with MDD including 3 additional patients and 8 matched normal controls were analyzed. RESULTS: The quantitative proteomic studies identified 10 proteins that were consistently upregulated or downregulated in 5 MDD patients. ELISA yielded results consistent with the proteomic analysis for 3 proteins. Expression levels were significantly different between normal controls and MDD patients. The 3 proteins were ceruloplasmin, inter-alpha-trypsin inhibitor heavy chain H4 and complement component 1qC, which were upregulated during the depressive status. The depressive status could be distinguished from the euthymic status from the ROC curves for these proteins, and this discrimination was enhanced when all 3 proteins were analyzed together. CONCLUSION: This is the first proteomic study in MDD patients to compare intra-individual differences dependent on mood. This technique could be a useful approach to identify MDD biomarkers, but requires additional proteomic studies for validation.