Fcgr2b and Fcgr3 are the major genetic factors for cartilage antibody-induced arthritis, overriding the effect of Hc encoding complement C5

B suppressor cells and protective autoantibodies

Recently the importance of B cells has been highlighted for therapy of several autoimmune diseases including rheumatoid arthritis (RA). Still, the functional role of B cells and antibodies in the disease process are unclear. Using animal models, antibodies specifically binding cartilage are pathogenic, but it has also recently been shown that both B cells and antibodies could be protective. These have specificities that are similar to B cells and autoantibodies detected in humans, including antibodies to citrullinated proteins and collagen type II, and may play an important role hindering an inflammatory attack, whereafter pathogenic B cells and antibodies are functionally more important to initiate and drive the clinically observable disease.

Hub genes and key pathways of Graves' disease: bioinformatics analysis and validation

OBJECTIVE

This study aims to identify hub genes associated with the onset and progression of Graves' disease (GD) with the goal of developing novel biomarkers to enhance diagnosis and improve patient outcomes.

METHODS

mRNA profiles from thyroid tissue samples (24 GD vs. 24 normal controls) were obtained from GEO (GSE9340), ArrayExpress (E-MEXP-2612), and GTEx (Thyroid dataset). After batch correction via SVA algorithm, 366 differentially expressed genes (DEGs) were identified using limma. Functional enrichment, protein-protein interaction networks, and immune microenvironment analysis were performed. Hub genes were validated in clinical thyroid specimens (3 GD vs. 3 controls) using RT-qPCR.

RESULTS

A total of 366 DEGs were identified in the diseased and normal groups. Among these, eight hub genes (TYROBP, CSF1R, CD163, ITGAM, CD86, FCGR3B, ITGB2, and IL10RA) showed strong correlations with immune cell content. These genes were predominantly enriched in pathways related to amino acid metabolism, viral protein interactions with cytokines and cytokine receptors, phagosome, chemokine signaling, programmed cell death, NF-κB, and other pathways. Additionally, these hub genes were linked to 39 regulatory factors. mRNA levels of these hub genes were validated in clinical samples through RT-qPCR. It is noteworthy that eight genes were found to be upregulated in GD samples.

CONCLUSION

The study highlights the potential impact of ITGB 2, TYROBP, CSF1R, CD163, ITGAM, CD86, FCGR3B, and IL10RA on the development and progression of GD, supporting their role as potential biomarkers.

The need for Cre-loci controls in conditional mouse experiments: Mrp8-cre transgene predisposes mice to antibody-induced arthritis

The Cre/loxP system is extensively utilized to pinpoint gene functions in specific cell types or developmental stages, typically without major disturbance to the host's genome. However, we found that the random insertion of the Mrp8-cre transgene significantly promotes the host's innate immune response. This effect is characterized by elevated susceptibility to cartilage antibody-induced arthritis, likely due to interference with genes near the insertion site. These findings underscore the potential biological disturbances caused by random transgene integration, and the necessity for stringent control strategies to avoid biased interpretations when using Cre-conditional strains.

Identifying Therapeutic Targets and Potential Drugs for Diabetic Retinopathy: Focus on Oxidative Stress and Immune Infiltration

Background

Diabetic retinopathy (DR), a microvascular disorder linked to diabetes, is on the rise globally. Oxidative stress and immune cell infiltration are linked to illness initiation and progression, according to recent study. This study investigated biomarkers connected to DR and oxidative stress and their connection with immune cell infiltration using bioinformatics analysis and found possible therapeutic medications.

Methods

The Gene Expression Omnibus (GEO) database was used to obtain the gene expression data for DR. Differentially expressed genes (DEGs) and oxidative stress (OS)-related genes were intersected. The Enrichment analyses concentrate on OS-related differentially expressed genes (DEOSGs). Analysis of protein-protein interaction (PPI) networks and machine learning algorithms were used to identify hub genes. Single-gene Gene Set Enrichment Analysis (GSEA) identified biological functions, while nomograms and ROC curves assessed diagnostic potential. Immune infiltration analysis and regulatory networks were constructed. Drug prediction was validated through molecular docking, and hub gene expression was confirmed in dataset and animal models.

Results

Compared to the control group, 91 DEOSGs were found. Enrichment analyses showed that these DEOSGs were largely connected to oxidative stress response, PI3K/Akt pathway, inflammatory pathways, and immunological activation. Four hub genes were found via PPI networks and machine learning. These hub genes were diagnostically promising according to nomogram and ROC analysis. Analysis of immune cell infiltration highlighted the role of immune cells. Gene regulatory networks for transcription factor (TF) and miRNA were created. Using structural data, molecular docking shows potential drugs and hub genes have high binding affinity. Dataset analysis, Real-Time Quantitative Polymerase Chain Reaction (RT-qPCR) and Western Blot (WB) confirmed the CCL4 expression difference between DR and controls.

Conclusion

CCL4 was identified as potential oxidative stress-related biomarker in DR, providing new insights for DR diagnosis and treatment.

Genetic insights into therapeutic targets for gout: evidence from a multi-omics mendelian randomization study

BACKGROUND

Considering that the treatment of gout is poor, we performed a Mendelian randomization (MR) study to identify candidate biomarkers and therapeutic targets for gout.

METHODS

A drug-targeted MR study was performed for gout by integrating the gout genome-wide association studies (GWAS) summary data and cis expression quantitative trait loci of 2,633 druggable genes from multiple cohorts. Summary data-based Mendelian randomization (SMR) analyses based on transcript and protein levels were further implemented to validate the reliability of the identified potential therapeutic targets for gout. Phenome-wide MR (Phe-MR) analysis was conducted in 1403 diseases to investigate incidental side effects of potential therapeutic targets for gout.

RESULTS

Eight potential therapeutic targets (ALDH3B1, FCGR2B, IL2RB, NRBP1, RCE1, SLC7A7, SUMF1, THBS3) for gout were identified in the discovery cohort using MR analysis. Replication analysis and meta-analysis implemented in the replication cohort validated the robustness of the MR findings (P < 0.05). Evidence from the SMR analysis (P < 0.05) further strengthened the reliability of the 8 potential therapeutic targets for gout also revealed that high levels of ALDH3B1 reduced the gout risk possibly modified by the methylation site cg25402137. SMR analysis (P < 0.05) at the protein level added emphasis on the impact of the risk genes NRBP1 and SUMF1 on gout. Phe-MR analysis indicated significant causality between 7 gout causal genes and 45 diseases.

CONCLUSION

This study identified several biomarkers associated with gout risk, providing new insights into the etiology of gout and promising targets for the development of therapeutic agents.

Shift in perspective: autoimmunity protecting against rheumatoid arthritis

A hallmark of rheumatoid arthritis (RA) is the increased levels of autoantibodies preceding the onset and contributing to the classification of the disease. These autoantibodies, mainly anti-citrullinated protein antibody (ACPA) and rheumatoid factor, have been assumed to be pathogenic and many attempts have been made to link them to the development of bone erosion, pain and arthritis. We and others have recently discovered that most cloned ACPA protect against experimental arthritis in the mouse. In addition, we have identified suppressor B cells in healthy individuals, selected in response to collagen type II, and these cells decrease in numbers in RA. These findings provide a new angle on how to explain the development of RA and maybe also other complex autoimmune diseases preceded by an increased autoimmune response.