Department of Rheumatology & Clinical Immunology, University Medical Center Utrecht and Utrecht University, Heidelberglaan 100, 3584 CX, Utrecht, The Netherlands.
Center for Translational Immunology, University Medical Center Utrecht and Utrecht University, Utrecht, The Netherlands.
J Clin Immunol. 2021 Feb;41(2):362-373. doi: 10.1007/s10875-020-00908-1. Epub 2020 Nov 15.
Patients with common variable immunodeficiency (CVID) can develop immune dysregulation complications such as autoimmunity, lymphoproliferation, enteritis, and malignancy, which cause significant morbidity and mortality. We aimed to (i) assess the potential of serum proteomics in stratifying patients with immune dysregulation using two independent cohorts and (ii) identify cytokine and chemokine signaling pathways that underlie immune dysregulation in CVID. A panel of 180 markers was measured in two multicenter CVID cohorts using Olink Protein Extension Assay technology. A classification algorithm was trained to distinguish CVID with immune dysregulation (CVIDid, n = 14) from CVID with infections only (CVIDio, n = 16) in the training cohort, and validated on a second testing cohort (CVIDid n = 23, CVIDio n = 24). Differential expression in both cohorts was used to determine relevant signaling pathways. An elastic net classifier using MILR1, LILRB4, IL10, IL12RB1, and CD83 could discriminate between CVIDid and CVIDio patients with a sensitivity of 0.83, specificity of 0.75, and area under the curve of 0.73 in an independent testing cohort. Activated pathways (fold change > 1.5, FDR-adjusted p < 0.05) in CVIDid included Th1 and Th17-associated signaling, as well as IL10 and other immune regulatory markers (LAG3, TNFRSF9, CD83). Targeted serum proteomics provided an accurate and reproducible tool to discriminate between patients with CVIDid and CVIDio. Cytokine profiles provided insight into activation of Th1 and Th17 pathways and indicate a possible role for chronic inflammation and exhaustion in immune dysregulation. These findings serve as a first step towards the development of biomarkers for immune dysregulation in CVID.
患有普通变异性免疫缺陷症 (CVID) 的患者可能会出现免疫失调并发症,如自身免疫、淋巴增生、肠炎和恶性肿瘤,这会导致显著的发病率和死亡率。我们旨在:(i) 使用两个独立的队列评估血清蛋白质组学在分层免疫失调患者中的潜力;(ii) 确定导致 CVID 免疫失调的细胞因子和趋化因子信号通路。使用 Olink Protein Extension Assay 技术在两个多中心 CVID 队列中测量了 180 个标志物。在训练队列中,使用分类算法来区分免疫失调的 CVID(CVIDid,n=14)和仅感染的 CVID(CVIDio,n=16),并在第二个测试队列(CVIDid n=23,CVIDio n=24)上进行验证。两个队列中的差异表达用于确定相关的信号通路。使用 MILR1、LILRB4、IL10、IL12RB1 和 CD83 的弹性网络分类器可以区分 CVIDid 和 CVIDio 患者,在独立测试队列中的敏感性为 0.83,特异性为 0.75,曲线下面积为 0.73。CVIDid 中激活的通路(倍数变化>1.5,经 FDR 调整的 p<0.05)包括 Th1 和 Th17 相关信号通路,以及 IL10 和其他免疫调节标记物(LAG3、TNFRSF9、CD83)。靶向血清蛋白质组学提供了一种准确且可重复的工具,可以区分 CVIDid 和 CVIDio 患者。细胞因子谱提供了 Th1 和 Th17 途径激活的深入了解,并表明慢性炎症和衰竭在免疫失调中可能发挥作用。这些发现是朝着开发 CVID 免疫失调生物标志物迈出的第一步。