Rachid Zaim Samir, Savage Adam K, Gillespie Mark A, Castillo Jazmine D, Bennett Christy, Torgerson Troy R, Becker Lynne A, Mahler Michael, Moss LauraKay, Feser Marie L, Edison Jess D, Mikuls Ted R, Holers V Michael, Li Xiao-Jun, Deane Kevin D
Allen Institute for Immunology, Seattle, Washington.
Inova Diagnostics, San Diego, California.
Arthritis Rheumatol. 2025 Sep;77(9):1166-1178. doi: 10.1002/art.43175. Epub 2025 May 13.
This longitudinal case-control study evaluated serum proteomics before a clinical diagnosis of rheumatoid arthritis (RA) (ie, pre-RA) to evaluate biologic pathways of disease development and inform prediction of timing of onset of future disease.
Patients (n = 213) meeting the 1987 American College of Rheumatology classification criteria for RA and matched controls without RA (n = 215) were identified in the Department of Defense Serum Repository. Serum samples from patients before and after RA diagnosis and controls were tested for RA-related autoantibodies (anti-cyclic citrullinated peptide-3 [anti-CCP3] and rheumatoid factor [RF] isotypes IgM and IgA) and 197 proteins using a commercial platform (Olink). We applied linear mixed effect models to identify biomarkers distinguishing patients from controls before RA diagnosis and analyzed longitudinal patterns of enriched pathways; in addition, models were developed to classify the time of a sample in relationship to the time of RA diagnosis.
Levels of anti-CCP3, RFIgA, and RFIgM demonstrated the greatest differences between patients and controls ≤5 years before RA diagnosis. Longitudinal analyses identified 104 proteins that were differentially expressed between patients and controls; 60 proteins were differentially expressed ≤5 years before diagnosis, 42 proteins were differentially expressed within and before five years of diagnosis, and 2 proteins were differentially expressed >5 years before diagnosis. Kyoto Encyclopedia of Genes and Genomes analyses identified that these proteins were associated with 32 pathways, including 21 pathways that were enriched ≤5 years before diagnosis. Within the anti-citrullinated protein antibody-positive samples from before RA diagnosis and controls, a set of features classified if that sample was from a period <3 years before RA diagnosis, with an area under the receiver operating characteristic (ROC) curve of 0.78 (95% confidence interval 0.67-0.89) in a training set and 0.80 (0.68-0.92) in a validation set.
Autoantibodies and protein signatures evolve in distinct stages before a diagnosis of RA. Furthermore, protein biomarkers may identify biologic pathways relevant to specific stages. These can be further explored to potentially improve prediction of disease onset and identify stage-specific biologic pathways to target with preventive interventions.
这项纵向病例对照研究评估了类风湿关节炎（RA）临床诊断前（即RA前期）的血清蛋白质组学，以评估疾病发展的生物学途径，并为预测未来疾病发病时间提供依据。
在国防部血清库中识别出符合1987年美国风湿病学会RA分类标准的患者（n = 213）以及匹配的无RA对照（n = 215）。使用商业平台（Olink）对RA诊断前后患者及对照的血清样本进行RA相关自身抗体（抗环瓜氨酸肽-3 [抗CCP3]以及类风湿因子[RF]的IgM和IgA亚型）和197种蛋白质的检测。我们应用线性混合效应模型来识别在RA诊断前区分患者与对照的生物标志物，并分析富集途径的纵向模式；此外，还建立了模型以根据样本时间与RA诊断时间的关系对样本进行分类。
在RA诊断前≤5年时，抗CCP3、RF IgA和RF IgM水平在患者与对照之间显示出最大差异。纵向分析确定了104种在患者与对照之间差异表达的蛋白质；60种蛋白质在诊断前≤5年差异表达，42种蛋白质在诊断前5年内及诊断前差异表达，2种蛋白质在诊断前>5年差异表达。京都基因与基因组百科全书分析确定这些蛋白质与32条途径相关，包括21条在诊断前≤5年富集的途径。在RA诊断前及对照的抗瓜氨酸化蛋白抗体阳性样本中，一组特征可对该样本是否来自RA诊断前<3年的时期进行分类，在训练集中受试者操作特征（ROC）曲线下面积为0.78（95%置信区间0.67 - 0.89），在验证集中为0.80（0.68 - 0.92）。
自身抗体和蛋白质特征在RA诊断前的不同阶段演变。此外，蛋白质生物标志物可能识别与特定阶段相关的生物学途径。这些可进一步探索，以潜在地改善疾病发病预测，并识别可通过预防性干预靶向的阶段特异性生物学途径。
