机构:[1]Department of Rheumatology and Immunology, Peking University People’s Hospital & Beijing Key Laboratory for Rheumatism Mechanism and Immune Diagnosis (BZ0135), Beijing, China [2]Chongqing Key Laboratory of Intelligent Oncology for Breast Cancer, Cancer Hospital, School of Medicine, Chongqing University, Chongqing, China [3]General Medical Department, Huazhong University of Science and Technology Union Shenzhen Hospital, Shenzhen, China 深圳市康宁医院深圳市南山区人民医院深圳医学信息中心[4]Department of Rheumatology and Immunology, First Affiliated Hospital of Kunming Medical University., Kunming, China 昆明医科大学附属第一医院内科科室风湿免疫科[5]Beijing Protein Innovation, B-8, Airport Industrial Zone, Beijing, China [6]Department of Rheumatology, the First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China [7]Department of Rheumatology, The First Affiliated Hospital of Heilongjiang University of Traditional Chinese Medicine. No.24 Heping Road, Xiangfang District, Harbin, China [8]Department of Rheumatism and Immunology, Peking University Shenzhen Hospital, Shenzhen, China 北京大学深圳医院深圳市康宁医院深圳医学信息中心[9]State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Biomedical Pioneering Innovative Center (BIOPIC) & Beijing Advanced Innovation Center for Genomics (ICG), Center for Bioinformatics (CBI), Peking University, Beijing, China
Precise diagnostic biomarkers of anticitrullination protein antibody (ACPA)-negative and early-stage RA are still to be improved. We aimed to screen autoantibodies in ACPA-negative patients and evaluated their diagnostic performance. The human genome-wide protein arrays (HuProt arrays) were used to define specific autoantibodies from the sera of 182 RA patients and 261 disease and healthy controls. Statistical analysis was performed with SPSS 17.0. In Phase I study, 51 out of 19,275 recombinant proteins covering the whole human genome were selected. In Phase II validation study, anti-ANAPC15 (anaphase promoting complex subunit 15) exhibited 41.8% sensitivity and 91.5% specificity among total RA patients. There were five autoantibodies increased in ACPA-negative RA, including anti-ANAPC15, anti-LSP1, anti-APBB1, anti-parathymosin, and anti-UBL7. Anti- showed the highest prevalence of 46.2% (p = 0.016) in ACPA-negative early stage (<2 years) RA. To further improve the diagnostic efficacy, a prediction model was constructed with 44 autoantibodies. With increased threshold for RA calling, the specificity of the model is 90.8%, while the sensitivity is 66.1% (87.8% in ACPA-positive RA and 23.8% in ACPA-negative RA) in independent testing patients. Therefore, HuProt arrays identified RA-associated autoantibodies that might become possible diagnostic markers, especially in early stage ACPA-negative RA.
基金:
Beijing Municipal Science & Technology Commission [Z141107002514064]; Beijing Science and Technology Planning Project [Z191100006619112, Z171100000417007]; National Natural Science Foundation of China [82171775, 81801618]; Natural Science Foundation of Beijing [J230026]; Beijing Nova Program [20230484468]
第一作者机构:[1]Department of Rheumatology and Immunology, Peking University People’s Hospital & Beijing Key Laboratory for Rheumatism Mechanism and Immune Diagnosis (BZ0135), Beijing, China
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通讯作者:
推荐引用方式(GB/T 7714):
Liu Xu,Zhang Xiaoying,Kang Yu-Jian,et al.An autoantibody profile identified by human genome-wide protein arrays in rheumatoid arthritis[J].MEDCOMM.2024,5(8):doi:10.1002/mco2.679.
APA:
Liu, Xu,Zhang, Xiaoying,Kang, Yu-Jian,Huang, Fei,Liu, Shuang...&Sun, Xiaolin.(2024).An autoantibody profile identified by human genome-wide protein arrays in rheumatoid arthritis.MEDCOMM,5,(8)
MLA:
Liu, Xu,et al."An autoantibody profile identified by human genome-wide protein arrays in rheumatoid arthritis".MEDCOMM 5..8(2024)