Rheumatoid arthritis (RA) is a chronic autoimmune inflammatory disease associated with a high index of morbidity and mortality from cardiovascular diseases. We used ¹H NMR to characterize the plasma glycoprotein and lipoprotein profiles of a cohort of patients with RA (n = 210) versus healthy individuals (n = 203) to associate them with the RA disease and its severity. Using ¹H NMR, we developed a line-shape method to characterize the two peaks associated with glycoproteins (GlycA and GlycB) and its derived variables: areas of GlycB (Area GlycB) and GlycA (Area GlycA), shape factors of these two peaks (H/W = height/width), and the distance between them (Distance GlycB–GlycA). We also used the advanced lipoprotein test Liposcale (CE) to characterize the lipoprotein subclasses. The standard lipid panel and traditional inflammatory markers such as C-reactive protein, the erythrocyte sedimentation rate, fibrinogen, the rheumatoid factor, anticitrullinated peptide antibodies, and the DAS28 index have also been determined. RA patients presented a significant 10.65% increase in the GlycA associated area compared with the control group (p = 2.21 × 10^–10). They also presented significantly higher H/W GlycA and GlycB ratios than the control population (H/W GlycB p = 7.88 × 10^–8; H/W GlycA p = 5.61 × 10^–8). The prediction model that uses the traditional inflammatory variables and the ¹H NMR-derived parameters presented an AUC that was almost 10% higher than the model that only uses the traditional inflammatory variables (from 0.7 to 0.79 AUC). We have demonstrated that GlycA and GlycB variables derived from ¹H NMR, along with classic inflammatory parameters, help to improve the classification of individuals with high RA disease activity.

中文翻译：

---

¹ H NMR血浆糖蛋白的表征作为识别类风湿关节炎中炎症模式的新策略

类风湿关节炎（RA）是一种慢性自身免疫性炎性疾病，与心血管疾病的高发病率和高死亡率有关。我们使用¹ H NMR来表征一组RA患者（n = 210）与健康个体（n = 203）患者的血浆糖蛋白和脂蛋白谱，以将其与RA疾病及其严重程度相关联。使用¹1 H NMR，我们开发了一种线形方法来表征与糖蛋白相关的两个峰（GlycA和GlycB）及其衍生变量：GlycB的面积（Area GlycB）和GlycA的面积（Area GlycA），这两个峰的形状因子（H / W =高度/宽度），以及它们之间的距离（距离GlycB–GlycA）。我们还使用了高级脂蛋白测试脂秤（CE）来表征脂蛋白亚类。还确定了标准脂质组和传统的炎症标志物，例如C反应蛋白，红细胞沉降率，纤维蛋白原，类风湿因子，抗瓜氨酸肽抗体和DAS28指数。与对照组相比，RA患者的GlycA相关面积显着增加了10.65％（p = 2.21×10 ^–10）。他们还表现出明显高于对照人群的H / W GlycA和GlycB比率（H / W GlycB p = 7.88×10 ^–8； H / W GlycA p = 5.61×10 ^–8）。使用传统炎症变量和¹ H NMR衍生参数的预测模型显示的AUC比仅使用传统炎症变量（0.7至0.79 AUC）的模型高出近10％。我们已经证明，源自¹ H NMR的GlycA和GlycB变量以及经典的炎症参数有助于改善具有高RA疾病活性的个体的分类。