Isotypes of autoantibodies against differentially expressed novel malondialdehyde-modified peptide adducts in serum of Taiwanese women with rheumatoid arthritis

Using anti-malondialdehyde-modified peptide adduct autoantibodies in serum of taiwanese women to diagnose primary Sjogren's syndrome

BACKGROUND

Sjogren's syndrome (SS) is a systemic autoimmune disease featured with a dry mouth and dry eyes. Several autoantibodies, including anti-SSA, anti-SSB, antinuclear antibodies can be detected in patients with SS. Oxidation-specific epitopes (OSEs) can be formed from malondialdehyde (MDA)-modified protein adducts and trigger chronic inflammation. In this study, our purposes were used serum levels of anti-MDA-modified peptide adducts autoantibodies to evaluate predictive performance by machine learning algorithms in primary Sjögren's syndrome (pSS) and assess the association between pSS and healthy controls.

METHODS

Three novel MDA-modified peptide adducts, including immunoglobulin (Ig) gamma heavy chain 1 (IGHG1)^102-131, complement factor H (CFAH)^1045-1062_, and Ig heavy constant alpha 1 (IGHA1)^307-327 were identified and validated. Serum levels of protein, MDA-modified protein adducts, MDA, and autoantibodies recognizing unmodified peptides and MDA-modified peptide adducts were measured. Statistically significance in correlations and odds ratios (ORs) were estimated.

RESULTS

The random forest classifier utilized autoantibodies combination composed of IgM anti-IGHG1^102-131, IgM anti-IGHG1^102-131 MDA and IgM anti-IGHA1^307-327 achieved predictive performance as an accuracy of 88.0%, a sensitivity of 93.7%, and a specificity of 84.4% which may be as potential diagnostic biomarkers to differentiate patients with pSS from rheumatoid arthritis (RA), and secondary SS in RA and HCs.

CONCLUSIONS

Our findings imply that low levels of IgA anti-IGHG1^102-131 MDA (OR = 2.646), IgA anti-IGHG1^102-131 (OR = 2.408), IgA anti-CFAH^1045-1062 (OR = 2.571), and IgA anti-IGHA1^307-327 (OR = 2.905) may denote developing risks of pSS, respectively.

UV induced changes in proteome of rats plasma are reversed by dermally applied cannabidiol

UV radiation is known to induce a multiple changes in the metabolism of skin-building cells, what can affect the functioning not only neighboring cells, but also, following signal transduction releasing into the blood vessels, the entire body. Therefore, the aim of this study was to analyze the proteomic disturbances occurred in plasma of chronically UVA/UVB irradiated rats and define the effect on these changes of skin topically applied cannabidiol (CBD). Obtained results showed significant changes in the expression of numerous anti-inflammatory and signaling proteins including: NFκB inhibitor, 14-3-3 protein, protein kinase C, keratin, and protein S100 after UV irradiation and CBD treatment. Moreover, the effects of UVA and UVB were manifested by increased level of lipid peroxidation products-protein adducts formation. CBD partially prevented all of these changes, but in a various degree depending on the UV radiation type. Moreover, topical treatment with CBD resulted in the penetration of CBD into the blood and, as a consequence, in direct modifications to the plasma protein structure by creating CBD adducts with molecules, such as proline-rich protein 30, transcription factor 19, or N-acetylglucosamine-6-sulfatase, what significantly changed the activity of these proteins. In conclusion, it may be suggested that CBD applied topically may be an effective compound against systemic UV-induced oxidative stress, but its effectiveness requires careful analysis of CBD's effects on other tissues of the living organism.

Using Anti-Malondialdehyde Modified Peptide Autoantibodies to Import Machine Learning for Predicting Coronary Artery Stenosis in Taiwanese Patients with Coronary Artery Disease

Machine learning (ML) algorithms have been applied to predicting coronary artery disease (CAD). Our purpose was to utilize autoantibody isotypes against four different unmodified and malondialdehyde (MDA)-modified peptides among Taiwanese with CAD and healthy controls (HCs) for CAD prediction. In this study, levels of MDA, MDA-modified protein (MDA-protein) adducts, and autoantibody isotypes against unmodified peptides and MDA-modified peptides were measured with enzyme-linked immunosorbent assay (ELISA). To improve the performance of ML, we used decision tree (DT), random forest (RF), and support vector machine (SVM) coupled with five-fold cross validation and parameters optimization. Levels of plasma MDA and MDA-protein adducts were higher in CAD patients than in HCs. IgM anti-IGKC^76-99 MDA and IgM anti-A1AT^284-298 MDA decreased the most in patients with CAD compared to HCs. In the experimental results of CAD prediction, the decision tree classifier achieved an area under the curve (AUC) of 0.81; the random forest classifier achieved an AUC of 0.94; the support vector machine achieved an AUC of 0.65 for differentiating between CAD patients with stenosis rates of 70% and HCs. In this study, we demonstrated that autoantibody isotypes imported into machine learning algorithms can lead to accurate models for clinical use.

Skeletal muscle redox signaling in rheumatoid arthritis

Rheumatoid arthritis (RA) is a chronic inflammatory disease characterized by synovitis and the presence of serum autoantibodies. In addition, skeletal muscle weakness is a common comorbidity that contributes to inability to work and reduced quality of life. Loss in muscle mass cannot alone account for the muscle weakness induced by RA, but instead intramuscular dysfunction appears as a critical factor underlying the decreased force generating capacity for patients afflicted by arthritis. Oxidative stress and associated oxidative post-translational modifications have been shown to contribute to RA-induced muscle weakness in animal models of arthritis and patients with RA. However, it is still unclear how and which sources of reactive oxygen and nitrogen species (ROS/RNS) that are involved in the oxidative stress that drives the progression toward decreased muscle function in RA. Nevertheless, mitochondria, NADPH oxidases (NOX), nitric oxide synthases (NOS) and phospholipases (PLA) have all been associated with increased ROS/RNS production in RA-induced muscle weakness. In this review, we aim to cover potential ROS sources and underlying mechanisms of oxidative stress and loss of force production in RA. We also addressed the use of antioxidants and exercise as potential tools to counteract oxidative stress and skeletal muscle weakness.

Isotypes of autoantibodies against novel differential 4-hydroxy-2-nonenal-modified peptide adducts in serum is associated with rheumatoid arthritis in Taiwanese women

Background

Rheumatoid 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.

Methods

Serum 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.

Results

Levels 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-THRB^328−345 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-THRB^328−345 (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.

Conclusions

This 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-THRB^328−345 may play heavy roles in RA development.

Sample preparation approaches for qualitative and quantitative analysis of lipid-derived electrophile modified proteomes by mass spectrometry

Lipid-derived electrophile (LDE) modifications, which are covalent modifications of proteins by endogenous LDEs, are essential types of protein posttranslational modifications. LDE modifications alter the protein structure and regulate their biological processes in cells. LDE modifications of proteins are also closely associated with several diseases and function as potential biomarkers for clinical diagnosis. The crucial step in studying the LDE modifications is to enrich the LDE modified proteins/peptides from complex biological samples with high efficiency and high selectivity and quantify modified proteins/peptides with high accuracy. In this review, we summarize the recent progress in MS-based proteomic technologies to globally identify and quantify LDE modified proteomes, mainly focusing on discussing the qualitative and quantitative technologies.

Modulation of the Oxidative Stress and Lipid Peroxidation by Endocannabinoids and Their Lipid Analogues

Growing evidence supports the pivotal role played by oxidative stress in tissue injury development, thus resulting in several pathologies including cardiovascular, renal, neuropsychiatric, and neurodegenerative disorders, all characterized by an altered oxidative status. Reactive oxygen and nitrogen species and lipid peroxidation-derived reactive aldehydes including acrolein, malondialdehyde, and 4-hydroxy-2-nonenal, among others, are the main responsible for cellular and tissue damages occurring in redox-dependent processes. In this scenario, a link between the endocannabinoid system (ECS) and redox homeostasis impairment appears to be crucial. Anandamide and 2-arachidonoylglycerol, the best characterized endocannabinoids, are able to modulate the activity of several antioxidant enzymes through targeting the cannabinoid receptors type 1 and 2 as well as additional receptors such as the transient receptor potential vanilloid 1, the peroxisome proliferator-activated receptor alpha, and the orphan G protein-coupled receptors 18 and 55. Moreover, the endocannabinoids lipid analogues N-acylethanolamines showed to protect cell damage and death from reactive aldehydes-induced oxidative stress by restoring the intracellular oxidants-antioxidants balance. In this review, we will provide a better understanding of the main mechanisms triggered by the cross-talk between the oxidative stress and the ECS, focusing also on the enzymatic and non-enzymatic antioxidants as scavengers of reactive aldehydes and their toxic bioactive adducts.