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

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 ( <a:math xmlns:a="http://www.w3.org/1998/Math/MathML" id="M1"> <a:mtext>median</a:mtext> <a:mo>=</a:mo> <a:mn>0.024</a:mn> <a:mtext> </a:mtext> <a:mi>μ</a:mi> <a:mtext>g</a:mtext> <a:mo>/</a:mo> <a:mtext>ml</a:mtext> </a:math> ) compared with ADAb-negative patients ( <c:math xmlns:c="http://www.w3.org/1998/Math/MathML" id="M2"> <c:mtext>median</c:mtext> <c:mo>=</c:mo> <c:mn>6.38</c:mn> <c:mtext> </c:mtext> <c:mi>μ</c:mi> <c:mtext>g</c:mtext> <c:mo>/</c:mo> <c:mtext>ml</c:mtext> </c:math> , <e:math xmlns:e="http://www.w3.org/1998/Math/MathML" id="M3"> <e:mi>p</e:mi> <e:mo>&lt;</e:mo> <e:mn>0.001</e:mn> </e:math> ). ROC analysis based on the ADAb status revealed the top 20 autoantibodies with <g:math xmlns:g="http://www.w3.org/1998/Math/MathML" id="M4"> <g:mtext>AUC</g:mtext> <g:mo>≥</g:mo> <g:mn>0.7</g:mn> </g:math> 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.