Anti-TROVE2 Antibody Determined by Immune-Related Array May Serve as a Predictive Marker for Adalimumab Immunogenicity and Effectiveness in RA

Author:

Chen Po-Ku12,Lan Joung-Liang23,Chen Yi-Ming45,Chen Hsin-Hua45,Chang Shih-Hsin23,Chung Chia-Min67,Rutt Nurul H.8,Tan Ti-Myen8,Mamat Raja Nurashirin Raja8,Anuar Nur Diana8,Blackburn Jonathan M.8,Chen Der-Yuan1239ORCID

Affiliation:

1. Translational Medicine Laboratory, Rheumatic Diseases Research Center, China Medical University Hospital, Taichung, Taiwan

2. College of Medicine, China Medical University, Taichung, Taiwan

3. Rheumatology and Immunology Center, China Medical University Hospital, Taichung, Taiwan

4. Department of Medical Research, Taichung Veterans General Hospital, Taiwan

5. Faculty of Medicine, National Yang-Ming University, Taipei, Taiwan

6. Center for Drug Abuse and Addiction, China Medical University Hospital, Taichung, Taiwan

7. Graduate Institute of Biomedical Sciences, China Medical University, Taichung, Taiwan

8. Sengenics Corporation Pte Ltd., Singapore

9. Ph.D. Program in Translational Medicine, National Chung Hsing University, Taichung, Taiwan

Abstract

Anti-drug antibody (ADAb) development is associated with secondary therapeutic failure in biologic-treated rheumatoid arthritis (RA) patients. With a treat-to-target goal, we aimed to identify biomarkers for predicting ADAb development and therapeutic response in adalimumab-treated patients. Three independent cohorts were enrolled. In Cohort-1, 24 plasma samples (6 ADAb-positive and 6 ADAb-negative patients at baseline and week 24 of adalimumab therapy, respectively) were assayed with immune-related microarray containing 1,636 correctly folded functional proteins. Next, we executed statistically powered autoantibody profiling analysis of 50 samples in Cohort-2 (24 ADAb-positive and 26 ADAb-negative patients). Subsequently, immunofluorescence assay was performed on 48 samples in Cohort-3 to correlate with ADAb titers and drug levels. The biomarkers were identified for predicting ADAb development and therapeutic response using the immune-related microarray and machine learning approach. ADAb-positive patients had lower drug levels at week 24 ( median = 0.024 μ g / ml ) compared with ADAb-negative patients ( median = 6.38 μ g / ml , p < 0.001 ). ROC analysis based on the ADAb status revealed the top 20 autoantibodies with AUC 0.7 in differentiating both groups in Cohort-1. Analysis of Cohort-2 dataset identified a panel of 8 biomarkers (TROVE2, SSB, NDE1, ZHX2, SH3GL1, CARD9, PTPN20, and KLHL12) with 80.6% specificity, 77.4% sensitivity, and 79.0% accuracy in discriminating poor from EULAR responders. Immunofluorescence assay validated that anti-TROVE2 antibody could highly predict ADAb development and poor EULAR response (AUC 0.79 and 0.89, respectively). Multivariate regression analysis proved anti-TROVE2 antibody to be an independent predictor for developing ADAb. Immune-related protein microarray and replication analysis identified anti-TROVE2 antibody as a useful biomarker for predicting ADAb development and therapeutic response in adalimumab-treated patients.

Funder

China Medical University Hospital

Publisher

Hindawi Limited

Subject

Immunology,General Medicine,Immunology and Allergy

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