‡Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, China; ¶School of Agriculture, Ludong University, Yantai 264025, China.
‡Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, China.
Mol Cell Proteomics. 2019 Sep;18(9):1851-1863. doi: 10.1074/mcp.RA119.001582. Epub 2019 Jul 15.
Systemic lupus erythematosus (SLE) is one of the most serious autoimmune diseases, characterized by highly diverse clinical manifestations. A biomarker is still needed for accurate diagnostics. SLE serum autoantibodies were discovered and validated using serum samples from independent sample cohorts encompassing 306 participants divided into three groups, healthy, SLE patients, and other autoimmune-related diseases. To discover biomarkers for SLE, a phage displayed random peptide library (Ph.D. 12) and deep sequencing were applied to screen specific autoantibodies in a total of 100 serum samples from 50 SLE patients and 50 healthy controls. A statistical analysis protocol was set up for the identification of peptides as potential biomarkers. For validation, 10 peptides were analyzed using enzyme-linked immunosorbent assays (ELISA). As a result, four peptides (SLE2018Val001, SLE2018Val002, SLE2018Val006, and SLE2018Val008) were discovered with high diagnostic power to differentiate SLE patients from healthy controls. Among them, two peptides, SLE2018Val001 and SLE2018Val002, were confirmed between SLE with other autoimmune patients. The procedure we established could be easily adopted for the identification of autoantibodies as biomarkers for many other diseases.
系统性红斑狼疮(SLE)是一种最严重的自身免疫性疾病之一,其临床表现高度多样化。目前仍需要一种生物标志物用于准确诊断。我们使用来自三个独立样本队列的血清样本发现并验证了 SLE 血清自身抗体,这三个队列共包含 306 名参与者,分为三组:健康人、SLE 患者和其他自身免疫性疾病相关患者。为了发现 SLE 的生物标志物,我们应用噬菌体展示随机肽库(Ph.D. 12)和深度测序技术,总共对 100 例来自 50 例 SLE 患者和 50 例健康对照者的血清样本进行了特定自身抗体的筛选。我们建立了一个统计分析方案来识别潜在的生物标志物肽。为了验证,我们使用酶联免疫吸附试验(ELISA)分析了 10 个肽。结果发现,有四个肽(SLE2018Val001、SLE2018Val002、SLE2018Val006 和 SLE2018Val008)具有较高的诊断能力,可区分 SLE 患者与健康对照者。其中,两个肽(SLE2018Val001 和 SLE2018Val002)在 SLE 与其他自身免疫性疾病患者之间得到了确认。我们建立的程序可以很容易地应用于其他许多疾病的自身抗体作为生物标志物的识别。