Home » Publications » Page 2

Publications

Discover how PEPperPRINT Peptide Microarray products have been used in different fields of research.

Autoantibodies to a novel Rpp38 (Th/To) derived B-cell epitope are specific for systemic sclerosis and associate with a distinct clinical phenotype

Koenig, Martial; Bentow, Chelsea; Satoh, Minoru; Fritzler, Marvin J; Senécal, Jean-Luc; Mahler, Michael
Abstract Objective Detection of antinuclear antibodies and specific autoantibodies is important in the diagnosis and classification of SSc. Several proteins of the Th/To complex, including Rpp25, Rpp38 and hPop1 are the target of autoantibodies in SSc patients. However, very little is known about the epitope distribution of this autoantigen. Consequently, we screened Rpp25, Rpp38 and hPop1 for B cell epitopes and evaluated their clinical relevance. Methods Serum pools with (n = 2) and without (n = 1) anti-Th/To autoantibodies were generated and used for epitope discovery. Identified biomarker candidate sequences were then utilized to synthesize synthetic, biotinylated, soluble peptides. The peptides were tested to determine reactivity with sera from SSc cohorts (n = 202) and controls (n = 159) using a chemiluminescence immunoassay. Additionally, samples were also tested for antibodies to full-length recombinant Rpp25 antibodies by chemiluminescence immunoassay. Results Several immunodominant regions were found on the three proteins. The strongest reactivity was observed with an Rpp38 peptide (aa 229–243). Autoantibodies to the Rpp38 peptide were detected in 8/149 (5.4%) limited cutaneous SSc patients, but not in any of 159 controls (P = 0.003 by two-sided Fisher’s exact probability test). Although reactivity to the novel antigenic peptide was correlated with the binding to Rpp25 (rho = 0.44; P < 0.0001), subsets of patient sera either reacted strongly with Rpp25 or with the novel Rpp38-derived peptide. Conclusion A novel Rpp38 epitope holds promise to increase the sensitivity in the detection of anti-Th/To autoantibodies, thus enhancing the serological diagnosis of SSc.

In-depth serum proteomics reveals biomarkers of psoriasis severity and response to traditional Chinese medicine

Xu, Meng; Deng, Jingwen; Xu, Kaikun; Zhu, Tiansheng; Han, Ling; Yan, Yuhong; Yao, Danni; Deng, Hao; Wang, Dan; Sun, Yaoting; Chang, Cheng; Zhang, Xiaomei; Dai, Jiayu; Yue, Liang; Zhang, Qiushi; Cai, Xue; Zhu, Yi; Duan, Hu; Liu, Yuan; Li, Dong; Zhu, Yunping; Radstake, Timothy R. D. J.; Balak, Deepak M.W.; Xu, Danke; Guo, Tiannan; Lu, Chuanjian; Yu, Xiaobo
Theranostics.
Apr 2019
Serum and plasma contain abundant biological information that reflect the body’s physiological and pathological conditions and are therefore a valuable sample type for disease biomarkers. However, comprehensive profiling of the serological proteome is challenging due to the wide range of protein concentrations in serum. Methods: To address this challenge, we developed a novel in-depth serum proteomics platform capable of analyzing the serum proteome across ~10 orders or magnitude by combining data obtained from Data Independent Acquisition Mass Spectrometry (DIA-MS) and customizable antibody microarrays. Results: Using psoriasis as a proof-of-concept disease model, we screened 50 serum proteomes from healthy controls and psoriasis patients before and after treatment with traditional Chinese medicine (YinXieLing) on our in-depth serum proteomics platform. We identified 106 differentially-expressed proteins in psoriasis patients involved in psoriasis-relevant biological processes, such as blood coagulation, inflammation, apoptosis and angiogenesis signaling pathways. In addition, unbiased clustering and principle component analysis revealed 58 proteins discriminating healthy volunteers from psoriasis patients and 12 proteins distinguishing responders from non-responders to YinXieLing. To further demonstrate the clinical utility of our platform, we performed correlation analyses between serum proteomes and psoriasis activity and found a positive association between the psoriasis area and severity index (PASI) score with three serum proteins (PI3, CCL22, IL-12B). Conclusion: Taken together, these results demonstrate the clinical utility of our in-depth serum proteomics platform to identify specific diagnostic and predictive biomarkers of psoriasis and other immune-mediated diseases.

Quote form