Apolipoprotein A-I and platelet factor 4 are biomarkers for infliximab response in rheumatoid arthritis

Abstract

Objectives: The use of biologicals such as infliximab has dramatically improved the treatment of rheumatoid arthritis (RA). However, factors predictive of therapeutic response need to be identified. A proteomic study was performed prior to infliximab therapy to identify a panel of candidate protein biomarkers of RA predictive of treatment response.

Methods: Plasma profiles of 60 patients with RA (28 non-responders (as defined by the American College of Rheumatology 20% improvement criteria (ACR20)) negative and 32 responders (ACR70 positive) to infliximab) were studied by surface enhanced laser desorption/ionisation time-of-flight mass spectrometry (SELDI-TOF MS) technology on two types of arrays, an anion exchange array (SAX2) and a nickel affinity array (IMAC3-Ni). Biomarker characterisation was carried out using classical biochemical methods (purification by ammonium sulfate precipitation or metal affinity chromatography) and identification by matrix assisted laser desorption/ionisation time-of-flight (MALDI-TOF) MS analysis.

Results: Two distinct protein profiles were observed on both arrays and several proteins were differentially expressed in both patient populations. Five proteins at 3.86, 7.77, 7.97, 8.14 and 74.07 kDa were overexpressed in the non-responder group, whereas one at 28 kDa was increased in the responder population (sensitivity>56%, specificity>77.5%). Moreover, combination of several biomarkers improved the sensitivity and specificity of the detection of patient response to over 97%. The 28 kDa protein was characterised as apolipoprotein A-I and the 7.77 kDa biomarker was identified as platelet factor 4.

Conclusions: Six plasma biomarkers are characterised, enabling the detection of patient response to infliximab with high sensitivity and specificity. Apolipoprotein A-1 was predictive of a good response to infliximab, whereas platelet factor 4 was associated with non-responders.

Figures

Figure 1. Representative SELDI-TOF-MS plasma profiles on SAX2 and IMAC3-Ni arrays

Plasma proteome of RA patients was analyzed by SELDI-TOF-MS with different laser intensities to characterize large (A) and smaller (B) proteins. Spectra showed relative intensity of each protein according to its mass/charge (m/z) value. Some peak intensities are marked in italic typing.

Figure 2. Decision tree built from IMAC3-Ni protein profile

CART analysis was performed on the whole proteome peaks characterized on the IMAC-Ni array. The intensity (I) of each node corresponding to a protein will draw a path for each patient leading to a terminal node, classifying the patient as a responder (R) or a non-responder (NR)

Figure 3. Relative peak intensities of the 7,769 Da (A) the 8,210 (B) and the 27,976 Da biomarkers in the responder (R) and non-responder (NR) populations

The box represents the interquartile range, the line across the box is the median and the whiskers represent the 5th and 95th percentiles.

Figure 4. Identification of the 27,976 Da and the 7,769 Da biomarkers

(A) Proteins from a responder plasma were precipitated with 50% ammonium sulfate and after centrifugation, 1 μl of pellet (lane 2 – 42.63 μg), 5 μl of desalted supernatant (lane 3 – 6.35 μg) and 1 μl of pure plasma (lane 1 – 77.43 μg) were loaded on a 15% SDS-PAGE gel. The 28 kDa band in the supernatant (circled on the gel) was identified by LC-MSMS as apolipoprotein A-I. (B) The 7,769 Da biomarker purified on a cobalt-based IMAC was incubated with coated anti-PF4 monoclonal antibodies (1 to 10 μg/well) and after a 2 h incubation period, supernatant was loaded on an NP20 array. (C) The intensity of this protein peak (in parenthesis on spectra) normalized to the BSA signal decreased while amount of coated antibody increased (* p=0.022 calculated with the Wilcoxon’s test).