Clark Kristina E N, Csomor Eszter, Campochiaro Corrado, Galwey Nicholas, Nevin Katherine, Morse Mary A, Teo Yee Voan, Freudenberg Johannes, Ong Voon H, Derrett-Smith Emma, Wisniacki Nicolas, Flint Shaun M, Denton Christopher P
Centre for Rheumatology, University College London, London, UK.
Immunoinflammation, GlaxoSmithKline, Stevenage, UK.
Lancet Rheumatol. 2022 Jun 23;4(7):e507-e516. doi: 10.1016/S2665-9913(22)00094-7. eCollection 2022 Jul.
Skin fibrosis is a hallmark feature of systemic sclerosis. Skin biopsy transcriptomics and blister fluid proteomics give insight into the local environment of the skin. We have integrated these modalities with the aim of developing a surrogate for the modified Rodnan skin score (mRSS), using candidate genes and proteins from the skin and blister fluid as anchors to identify key analytes in the plasma.
In this single-centre, prospective observational study at the Royal Free Campus, University College London, London, UK, transcriptional and proteomic analyses of blood and skin were performed in a cohort of patients with systemic sclerosis (n=52) and healthy controls (n=16). Weighted gene co-expression network analysis was used to explore the association of skin transcriptomics data, clinical traits, and blister fluid proteomic results. Candidate hub analytes were identified as those present in both blister and skin gene sets (modules), and which correlated with plasma (module membership >0·7 and gene significance >0·6). Hub analytes were confirmed using RNA transcript data obtained from skin biopsy samples from patients with early diffuse cutaneous systemic sclerosis at 12 months.
We identified three modules in the skin, and two in blister fluid, which correlated with a diagnosis of early diffuse cutaneous systemic sclerosis. From these modules, 11 key hub analytes were identified, present in both skin and blister fluid modules, whose transcript and protein levels correlated with plasma protein concentrations, mRSS, and showed statistically significant correlation on repeat transcriptomic samples taken at 12 months. Multivariate analysis identified four plasma analytes as correlates of mRSS (COL4A1, COMP, SPON1, and TNC), which can be used to differentiate disease subtype.
This unbiased approach has identified potential biological candidates that might be drivers of local skin pathogenesis in systemic sclerosis. By focusing on measurable analytes in the plasma, we generated a promising composite plasma protein biomarker that could be used for assessment of skin severity, case stratification, and as a potential outcome measure for clinical trials and practice. Once fully validated, the biomarker score could replace a clinical score such as the mRSS, which carries substantial variability.
GlaxoSmithKline and UK Medical Research Council.
皮肤纤维化是系统性硬化症的标志性特征。皮肤活检转录组学和水疱液蛋白质组学有助于深入了解皮肤的局部环境。我们整合了这些方法，旨在开发一种改良罗德南皮肤评分（mRSS）的替代指标，使用来自皮肤和水疱液的候选基因和蛋白质作为锚定物来识别血浆中的关键分析物。
在英国伦敦大学学院皇家自由校区进行的这项单中心前瞻性观察研究中，对一组系统性硬化症患者（n = 52）和健康对照者（n = 16）进行了血液和皮肤的转录组学和蛋白质组学分析。加权基因共表达网络分析用于探索皮肤转录组学数据、临床特征和水疱液蛋白质组学结果之间的关联。候选枢纽分析物被确定为同时存在于水疱和皮肤基因集（模块）中且与血浆相关的分析物（模块成员关系>0·7且基因显著性>0·6）。使用从早期弥漫性皮肤系统性硬化症患者12个月时的皮肤活检样本中获得的RNA转录数据对枢纽分析物进行了验证。
我们在皮肤中鉴定出三个模块，在水疱液中鉴定出两个模块，它们与早期弥漫性皮肤系统性硬化症的诊断相关。从这些模块中，鉴定出11种关键枢纽分析物，它们同时存在于皮肤和水疱液模块中，其转录本和蛋白质水平与血浆蛋白浓度、mRSS相关，并且在12个月时采集的重复转录组学样本中显示出统计学上的显著相关性。多变量分析确定了四种血浆分析物为mRSS的相关因素（COL4A1、COMP、SPON1和TNC），可用于区分疾病亚型。
这种无偏倚的方法已经确定了可能是系统性硬化症局部皮肤发病机制驱动因素的潜在生物学候选物。通过关注血浆中可测量的分析物，我们生成了一种有前景的复合血浆蛋白生物标志物，可用于评估皮肤严重程度、病例分层，以及作为临床试验和实践的潜在结局指标。一旦经过充分验证，该生物标志物评分可以取代mRSS等临床评分，因为后者存在很大的变异性。
葛兰素史克公司和英国医学研究理事会。
