Abstract

BackgroundRheumatoid arthritis (RA) is an autoimmune disorder with systemic inflammation and may be induced by oxidative stress that affects an inflamed joint. Our objectives were to examine isotypes of autoantibodies against 4-hydroxy-2-nonenal (HNE) modifications in RA and associate them with increased levels of autoantibodies in RA patients.MethodsSerum samples from 155 female patients [60 with RA, 35 with osteoarthritis (OA), and 60 healthy controls (HCs)] were obtained. Four novel differential HNE-modified peptide adducts, complement factor H (CFAH)1211–1230, haptoglobin (HPT)78–108, immunoglobulin (Ig) kappa chain C region (IGKC)2–19, and prothrombin (THRB)328–345, were re-analyzed using tandem mass spectrometric (MS/MS) spectra (ProteomeXchange: PXD004546) from RA patients vs. HCs. Further, we determined serum protein levels of CFAH, HPT, IGKC and THRB, HNE-protein adducts, and autoantibodies against unmodified and HNE-modified peptides. Significant correlations and odds ratios (ORs) were calculated.ResultsLevels of HPT in RA patients were greatly higher than the levels in HCs. Levels of HNE-protein adducts and autoantibodies in RA patients were significantly greater than those of HCs. IgM anti-HPT78−108 HNE, IgM anti-IGKC2−19, and IgM anti-IGKC2−19 HNE may be considered as diagnostic biomarkers for RA. Importantly, elevated levels of IgM anti-HPT78−108 HNE, IgM anti-IGKC2−19, and IgG anti-THRB328−345 were positively correlated with the disease activity score in 28 joints for C-reactive protein (DAS28-CRP). Further, the ORs of RA development through IgM anti-HPT78−108 HNE (OR 5.235, p < 0.001), IgM anti-IGKC2−19 (OR 12.655, p < 0.001), and IgG anti-THRB328−345 (OR 5.761, p < 0.001) showed an increased risk. Lastly, we incorporated three machine learning models to differentiate RA from HC and OA, and performed feature selection to determine discriminative features. Experimental results showed that our proposed method achieved an area under the receiver operating characteristic curve of 0.92, which demonstrated that our selected autoantibodies combined with machine learning can efficiently detect RA.ConclusionsThis study discovered that some IgG- and IgM-NAAs and anti-HNE M-NAAs may be correlated with inflammation and disease activity in RA. Moreover, our findings suggested that IgM anti-HPT78−108 HNE, IgM anti-IGKC2−19, and IgG anti-THRB328−345 may play heavy roles in RA development.

Highlights

  • Rheumatoid arthritis (RA) is an autoimmune disorder with systemic inflammation and may be induced by oxidative stress that affects an inflamed joint

  • This study discovered that some IgG- and immunoglobulin M (IgM)-NAAs and anti-HNE M-NAAs may be correlated with inflammation and disease activity in RA

  • Our findings suggested that IgM anti-HPT78−108 HNE, IgM antiIGKC2−19, and IgG anti-THRB328−345 may play heavy roles in RA development

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Summary

Introduction

Rheumatoid arthritis (RA) is an autoimmune disorder with systemic inflammation and may be induced by oxidative stress that affects an inflamed joint. One of the lipid peroxidation-generated highly bioactive electrophilic oxidation products, 4-hydroxy 2-nonenal (HNE), is produced through oxidative stress-generated reactive oxygen species (ROS)-targeted n-6 polyunsaturated fatty acids that contribute to the pathogenesis of various diseases, including RA, diabetes mellitus (DM), systemic lupus erythematosus (SLE), alcoholic liver disease (ALD), aging, neurodegenerative diseases, chronic obstructive pulmonary disease (COPD), cardiovascular diseases (CDs), and inflammation-driven cancers [7,8,9,10]. The aldehyde group in HNE can react by forming Schiff base adducts and increase mass of 138 Da in the non-reduced form (CHKAL) or 140 Da in the reduced form (CHKR) [11,12,13]. The non-reduced form of the Schiff base adducts (CHKR) further spontaneously rearranges to form a pyrrole adduct with a mass increase of 120 Da [14, 15]

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