Systemic lupus erythematosus (SLE) is a clinically and biologically heterogenous autoimmune disease. We aimed to investigate the plasma proteome of patients with active SLE to identify novel subgroups, or endotypes, of patients. Plasma was collected from patients with active SLE who were enrolled in the British Isles Lupus Assessment Group Biologics Registry (BILAG-BR). The plasma proteome was analysed using a data-independent acquisition method, Sequential Window Acquisition of All theoretical mass spectra mass spectrometry (SWATH-MS). Unsupervised, data-driven clustering algorithms were used to delineate groups of patients with a shared proteomic profile. In 223 patients, six clusters were identified based on quantification of 581 proteins. Between the clusters, there were significant differences in age (p = 0.012) and ethnicity (p = 0.003). There was increased musculoskeletal disease activity in cluster 1 (C1), 19/27 (70.4%) (p = 0.002) and renal activity in cluster 6 (C6) 15/24 (62.5%) (p = 0.051). Anti-SSa/Ro was the only autoantibody that significantly differed between clusters (p = 0.017). C1 was associated with p21-activated kinases (PAK) and Phospholipase C (PLC) signalling. Within C1 there were two sub-clusters (C1A and C1B) defined by 49 proteins related to cytoskeletal protein binding. C2 and C6 demonstrated opposite Rho family GTPase and Rho GDI signalling. Three proteins (MZB1, SND1 and AGL) identified in C6 increased the classification of active renal disease although this did not reach statistical significance (p = 0.0617). Unsupervised proteomic analysis identifies clusters of patients with active SLE, that are associated with clinical and serological features, which may facilitate biomarker discovery. The observed proteomic heterogeneity further supports the need for a personalised approach to treatment in SLE.

中文翻译：

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蛋白质组学分析确定了活动性系统性红斑狼疮患者的亚组

系统性红斑狼疮（SLE）是一种临床和生物学异质性自身免疫性疾病。我们的目的是研究活动性 SLE 患者的血浆蛋白质组，以确定患者的新亚组或内型。血浆采集自参加不列颠群岛狼疮评估组生物制品登记处 (BILAG-BR) 的活动性 SLE 患者。使用数据独立的采集方法，即所有理论质谱的连续窗口采集质谱法 (SWATH-MS) 来分析血浆蛋白质组。使用无监督、数据驱动的聚类算法来描绘具有共享蛋白质组谱的患者组。根据 581 种蛋白质的定量，在 223 名患者中鉴定出 6 个簇。各簇之间的年龄 (p = 0.012) 和种族 (p = 0.003) 存在显着差异。第 1 组 (C1) 中的肌肉骨骼疾病活动增加，19/27 (70.4%) (p = 0.002)，第 6 组 (C6) 15/24 (62.5%) (p = 0.051) 中的肾脏活动增加。抗 SSa/Ro 是唯一在簇之间存在显着差异的自身抗体 (p = 0.017)。C1 与 p21 激活激酶 (PAK) 和磷脂酶 C (PLC) 信号传导相关。C1 内有两个亚簇（C1A 和 C1B），由 49 个与细胞骨架蛋白结合相关的蛋白定义。C2 和 C6 表现出相反的 Rho 家族 GTPase 和 Rho GDI 信号传导。C6 中鉴定的三种蛋白（MZB1、SND1 和 AGL）增加了活动性肾病的分类，尽管这没有达到统计学显着性（p = 0.0617）。无监督蛋白质组学分析可识别活动性 SLE 患者群，这些患者与临床和血清学特征相关，这可能有助于生物标志物的发现。观察到的蛋白质组异质性进一步支持了系统性红斑狼疮个性化治疗方法的需要。