An Autoantibody Profile Identified by Human Genome-wide Protein Arrays in Rheumatoid Arthritis

Overview

Journal MedComm (2020)

Specialty Health Services

Date 2024 Aug 12

PMID 39132510

Authors

Xu Liu

Xiaoying Zhang

Yu-Jian Kang

Fei Huang

Shuang Liu

Yixue Guo

Yingni Li

Changcheng Yin

Mingling Liu

Qimao Han

Qingwen Wang

Hua Ye

Haihong Yao

Chun Li

Jiahe Li

Wangzha Pingcuo

Yan Zhang

Yin Su

Ge Gao

Zhanguo Li

Xiaolin Sun

Affiliations

Soon will be listed here.

Abstract

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-parathymosin showed the highest prevalence of 46.2% ( = 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.

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