Circulating methylation level of HTR2A is associated with inflammation and disease activity in rheumatoid arthritis

Mood disorders and 5-HTR2A genetic variants - the moderator effect of inflammation on expression of affective polarity phenotype

BACKGROUND

Although repeatedly confirmed, the molecular nature of gene-environment (GxE) interactions has rarely been investigated in the clinical context of mood disorders. This study assesses the relationship between HTR2A genetic variants and the modulatory effect of inflammation in a collective cohort of patients with major depressive disorder (MDD) and bipolar disorder (BD), as a unified group with two distinct phenotypes.

METHODS

The study included 138 patients with acute mood episodes (BD = 83; MDD = 55). HTR2A rs6313 and rs6314 genotyping was performed while measuring platelet-derived indicators of inflammation (platelet count (PLT), mean platelet volume (MPV), plateletcrit, and platelet distribution width) and the MPV/PLT ratio.

RESULTS

The HTR2A rs6313 variant is a significant predictor of the polarity phenotype in mood disorders, with the MPV/PLT ratio moderating this relationship, but only under low-inflammatory conditions. In more pronounced inflammatory states, genetic influences lose their predictive role.

CONCLUSIONS

To our knowledge, this is the first study to investigate the complex interplay between platelet-derived indicators of inflammation and HTR2A variants in the context of mood disorders. Without pro-inflammatory conditions, mood disorders seem to be more genetically determined. Under pro-inflammatory conditions, phenotypic presentation is less dependent on genetic factors. GxE interactions in mood disorders are multifaceted, context-dependent and relevant for assessing their clinical presentation and course.

Fibroblast expression of neurotransmitter receptor HTR2A associates with inflammation in rheumatoid arthritis joint

The study of neuroimmune crosstalk and the involvement of neurotransmitters in inflammation and bone health has illustrated their significance in joint-related conditions. One important mode of cell-to-cell communication in the synovial fluid (SF) is through extracellular vesicles (EVs) carrying microRNAs (miRNAs). The role of neurotransmitter receptors in the pathogenesis of inflammatory joint diseases, and whether there are specific miRNAs regulating differentially expressed HTR2A, contributing to the inflammatory processes and bone metabolism is unclear. Expression of neurotransmitter receptors and their correlated inflammatory molecules were identified in rheumatoid arthritis (RA) and osteoarthritis (OA) synovium from a scRNA-seq dataset. Immunohistochemistry staining of synovial tissue (ST) from RA and OA patients was performed for validation. Expression of miRNAs targeting HTR2A carried by SF EVs was screened in low- and high-grade inflammation RA from a public dataset and validated by qPCR. HTR2A reduction by target miRNAs was verified by miRNAs mimics transfection into RA fibroblasts. HTR2A was found to be highly expressed in fibroblasts derived from RA synovial tissue. Its expression showed a positive correlation with the degree of inflammation observed. 5 miRNAs targeting HTR2A were decreased in RA SF EVs compared to OA, three of which, miR-214-3p, miR-3120-5p and miR-615-3p, mainly derived from monocytes in the SF, were validated as regulators of HTR2A expression. The findings suggest that fibroblast HTR2A may play a contributory role in inflammation and the pathogenesis of RA. Additionally, targeting miRNAs that act upon HTR2A could present novel therapeutic strategies for alleviating inflammation in RA.

Identification of clinical characteristics biomarkers for rheumatoid arthritis through targeted DNA methylation sequencing

OBJECTIVES

Rheumatoid arthritis (RA) is a complex disease with a challenging diagnosis, especially in seronegative patients. The aim of this study is to investigate whether the methylation sites associated with the overall immune response in RA can assist in clinical diagnosis, using targeted methylation sequencing technology on peripheral venous blood samples.

METHODS

The study enrolled 241 RA patients, 30 osteoarthritis patients (OA), and 30 healthy volunteers control (HC). Fifty significant cytosine guanine (CG) sites between undifferentiated arthritis and RA were selected and analyzed using targeted DNA methylation sequencing. Logistic regression models were used to establish diagnostic models for different clinical features of RA, and six machine learning methods (logit model, random forest, support vector machine, adaboost, naive bayes, and learning vector quantization) were used to construct clinical diagnostic models for different subtypes of RA. Least absolute shrinkage and selection operator regression and detrended correspondence analysis were utilized to screen for important CGs. Spearman correlation was used to calculate the correlation coefficient.

RESULTS

The study identified 16 important CG sites, including tumor necrosis factort receptor associated factor 5 (TRAF5) (chr1:211500151), mothers against decapentaplegic homolog 3 (SMAD3) (chr15:67357339), tumor endothelial marker 1 (CD248) (chr11:66083766), lysosomal trafficking regulator (LYST) (chr1:235998714), PR domain zinc finger protein 16 (PRDM16) (chr1:3307069), A-kinase anchoring protein 10 (AKAP10) (chr17:19850460), G protein subunit gamma 7 (GNG7) (chr19:2546620), yes1 associated transcriptional regulator (YAP1) (chr11:101980632), PRDM16 (chr1:3163969), histone deacetylase complex subunit sin3a (SIN3A) (chr15:75747445), prenylated rab acceptor protein 2 (ARL6IP5) (chr3:69134502), mitogen-activated protein kinase kinase kinase 4 (MAP3K4) (chr6:161412392), wnt family member 7A (WNT7A) (chr3:13895991), inhibin subunit beta B (INHBB) (chr2:121107018), deoxyribonucleic acid replication helicase/nuclease 2 (DNA2) (chr10:70231628) and chromosome 14 open reading frame 180 (C14orf180) (chr14:105055171). Seven CG sites showed abnormal changes between the three groups (P < 0.05), and 16 CG sites were significantly correlated with common clinical indicators (P < 0.05). Diagnostic models constructed using different CG sites had an area under the receiver operating characteristic curve (AUC) range of 0.64-0.78 for high-level clinical indicators of high clinical value, with specificity ranging from 0.42 to 0.77 and sensitivity ranging from 0.57 to 0.88. The AUC range for low-level clinical indicators of high clinical value was 0.63-0.72, with specificity ranging from 0.48 to 0.74 and sensitivity ranging from 0.72 to 0.88. Diagnostic models constructed using different CG sites showed good overall diagnostic accuracy for the four subtypes of RA, with an accuracy range of 0.61-0.96, a balanced accuracy range of 0.46-0.94, and an AUC range of 0.46-0.94.

CONCLUSIONS

This study identified potential clinical diagnostic biomarkers for RA and provided novel insights into the diagnosis and subtyping of RA. The use of targeted deoxyribonucleic acid (DNA) methylation sequencing and machine learning methods for establishing diagnostic models for different clinical features and subtypes of RA is innovative and can improve the accuracy and efficiency of RA diagnosis.

Global research trends in DNA methylation in rheumatoid arthritis: A bibliometric analysis and visual analysis

Rheumatoid arthritis (RA) is a prevalent autoimmune disorder with a significant global economic burden. Epigenetic modifications, particularly DNA methylation, play a crucial role in RA. This study conducted a bibliometric analysis to explore the evolving trends and predominant themes in RA and DNA methylation research over the past two decades. A total of 1800 articles met the inclusion criteria, and the analysis revealed consistent growth in the literature, with a notable increase in output after 2019. The research involved 70 countries, 2139 academic institutions, 23,365 unique authors, and 58,636 co-cited authors. The United States emerged as a dominant contributor in this research domain. The significance of DNA methylation in shaping research directions for RA management is increasingly evident. Recent investigations have shed light on the pivotal role of DNA methylation in RA, particularly in characterizing synovial tissue and exploring the underlying mechanisms of disease pathogenesis. This study provides valuable insights into the landscape of DNA methylation research in RA and highlights the importance of epigenetics in autoimmune diseases.

Role of signaling lymphocytic activation molecule family of receptors in the pathogenesis of rheumatoid arthritis: insights and application

Rheumatoid arthritis (RA) is an autoimmune disease characterized by chronic inflammation and joint damage. The signaling lymphocytic activation molecule (SLAMF) family of receptors are expressed on various hematopoietic and non-hematopoietic cells and can regulate both immune cell activation and cytokine production. Altered expression of certain SLAMF receptors contributes to aberrant immune responses in RA. In RA, SLAMF1 is upregulated on T cells and may promote inflammation by participating in immune cell-mediated responses. SLAMF2 and SLAMF4 are involved in regulating monocyte tumor necrosis factor production and promoting inflammation. SLAMF7 activates multiple inflammatory pathways in macrophages to drive inflammatory gene expression. SLAMF8 inhibition can reduce inflammation in RA by blocking ERK/MMPs signaling. Of note, there are differences in SLAMF receptor (SFR) expression between normal and arthritic joint tissues, suggesting a role as potential diagnostic biomarkers. This review summarizes recent advances on the roles of SLAMF receptors 1, 2, 4, 7, and 8 in RA pathogenesis. However, further research is needed to elucidate the mechanisms of SLAMF regulation of immune cells in RA. Understanding interactions between SLAMF receptors and immune cells will help identify selective strategies for targeting SLAMF signaling without compromising normal immunity. Overall, the SLAMF gene family holds promise as a target for precision medicine in RA, but additional investigation of the underlying immunological mechanisms is needed. Targeting SLAMF receptors presents opportunities for new diagnostic and therapeutic approaches to dampen damaging immune-mediated inflammation in RA.

Network pharmacological analysis to reveal the mechanism governing the effect of Qin Xi Tong on osteoarthritis and rheumatoid arthritis

INTRODUCTION

Qin Xi Tong (QXT), produced by water extracts of Caulis Sinomenii, is clinically effective in the therapy of rheumatoid arthritis (RA). It is also a complementary agent for osteoarthritis (OA). This study aimed to screen the candidate targets and identify the potential mechanisms of QXT against RA and OA.

METHOD

The active ingredients contained in QXT were queried from the TCMSP database. Their predicted targets were obtained through web-based databases, including TCMSP, BATMAN-TCM, CTD, and PharmMapper. The OA and RA targets were collected from the Genecards database and the GSE55235 dataset. Based on the DAVID database, GO and KEGG enrichment analyses of disease-drug common targets predicted potential signaling pathways for QXT. In addition, core targets were identified by mapping component-target-disease interaction networks with Cytoscape 3.9.1 and STRING. The Swissdock and Pymol tools further validate the predicted results.

RESULTS

A total of 161 genes were put forward as potential targets for treating RA and OA. These genes might be involved in joint inflammation, including the IL-17 signaling pathway, MAPK signaling pathway, and TNF signaling pathway. They also regulated the progression of joint injuries, such as apoptosis, Th17 cell differentiation, and osteoclast differentiation. In addition, we identified 12 core targets of QXT. Molecular docking results showed that QXT has a high affinity with these core targets.

CONCLUSIONS

This study reveals the mechanism governing the effect of QXT on RA and OA, predicts the direct target, and provides new ideas for clinical treatment. Key Points • Our study reveals the underlying mechanism of QXT in the treatment of RA and OA. • Further research into the effects of compounds in QXT alone would be of interest.

Role of the granzyme family in rheumatoid arthritis: Current Insights and future perspectives

Rheumatoid arthritis (RA) is a complex autoimmune disease characterized by chronic inflammation that affects synovial tissues of multiple joints. Granzymes (Gzms) are serine proteases that are released into the immune synapse between cytotoxic lymphocytes and target cells. They enter target cells with the help of perforin to induce programmed cell death in inflammatory and tumor cells. Gzms may have a connection with RA. First, increased levels of Gzms have been found in the serum (GzmB), plasma (GzmA, GzmB), synovial fluid (GzmB, GzmM), and synovial tissue (GzmK) of patients with RA. Moreover, Gzms may contribute to inflammation by degrading the extracellular matrix and promoting cytokine release. They are thought to be involved in RA pathogenesis and have the potential to be used as biomarkers for RA diagnosis, although their exact role is yet to be fully elucidated. The purpose of this review was to summarize the current knowledge regarding the possible role of the granzyme family in RA, with the aim of providing a reference for future research on the mechanisms of RA and the development of new therapies.