Department of Chemistry and Biochemistry, University of Oklahoma, Norman, OK, 73019, USA.
Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202, USA.
Sci Rep. 2019 Feb 20;9(1):2345. doi: 10.1038/s41598-018-38380-y.
Detecting autoimmune diseases at an early stage is crucial for effective treatment and disease management to slow disease progression and prevent irreversible organ damage. In many autoimmune diseases, disease-specific autoantibodies are produced by B cells in response to soluble autoantigens due to defects in B cell tolerance mechanisms. Autoantibodies accrue early in disease development, and several are so disease-specific they serve as classification criteria. In this study, we established a high-throughput, sensitive, intact serum autoantibody analysis platform based on the optimization of a one dimensional ultra-high-pressure liquid chromatography top-down mass spectrometry platform (1D UPLC-TDMS). This approach has been successfully applied to a 12 standard monoclonal antibody antigen-binding fragment (Fab) mixture, demonstrating the feasibility to separate and sequence intact antibodies with high sequence coverage and high sensitivity. We then applied the optimized platform to characterize total serum antibody Fabs in a systemic lupus erythematosus (SLE) patient sample and compared it to healthy control samples. From this analysis, we show that the SLE sample has many dominant antibody Fab-related mass features unlike the healthy controls. To our knowledge, this is the first top-down demonstration of serum autoantibody pool analysis. Our proposed approach holds great promise for discovering novel serum autoantibody biomarkers that are of interest for diagnosis, prognosis, and tolerance induction, as well as improving our understanding of pathogenic autoimmune processes.
早期发现自身免疫性疾病对于有效治疗和疾病管理至关重要，可以减缓疾病进展并预防不可逆的器官损伤。在许多自身免疫性疾病中，B 细胞由于 B 细胞耐受机制的缺陷而针对可溶性自身抗原产生疾病特异性自身抗体。自身抗体在疾病发展的早期积累，并且有几种自身抗体具有如此高的疾病特异性，以至于它们被用作分类标准。在这项研究中，我们建立了一个基于优化一维超高压力液相色谱自上而下质谱平台（1D UPLC-TDMS）的高通量、敏感、完整血清自身抗体分析平台。这种方法已成功应用于 12 种标准单克隆抗体抗原结合片段（Fab）混合物，证明了具有高序列覆盖率和高灵敏度的分离和测序完整抗体的可行性。然后，我们将优化后的平台应用于系统性红斑狼疮（SLE）患者样本中的总血清抗体 Fab 进行表征，并将其与健康对照组样本进行比较。从这项分析中，我们表明，SLE 样本具有许多不同于健康对照组的优势抗体 Fab 相关质量特征。据我们所知，这是首次对血清自身抗体库进行自上而下的演示。我们提出的方法为发现新的血清自身抗体生物标志物提供了巨大的希望，这些标志物对诊断、预后和诱导耐受具有重要意义，并有助于我们更好地了解致病性自身免疫过程。
