Evaluation of tool-like receptor-2 and 4 and interleukin-6 gene expressions in Turkish rheumatoid arthritis patients

Emerging evidence of Toll-like receptors as a putative pathway linking maternal inflammation and neurodevelopmental disorders in human offspring: A systematic review

Inflammation is increasingly recognised to play a major role in gene-environment interactions in neurodevelopmental disorders (NDDs). The effects of aberrant immune responses to environmental stimuli in the mother and in the child can affect neuroimmune signalling that is central to brain development. Toll-like receptors (TLR) are the best known innate immune pattern and danger recognition sensors to various environmental threats. In animal models, maternal immune activation (MIA), secondary to inflammatory factors including maternal gestational infection, obesity, diabetes, and stress activate the TLR pathway in maternal blood, placenta, and fetal brain, which correlate with offspring neurobehavioral abnormalities. Given the central role of TLR activation in animal MIA models, we systematically reviewed the human evidence for TLR activation and response to stimulation across the maternal-fetal interface. Firstly, we included 59 TLR studies performed in peripheral blood of adults in general population (outside of pregnancy) with six chronic inflammatory factors which have epidemiological evidence for increased risk of offspring NDDs, namely, obesity, diabetes mellitus, depression, low socio-economic status, autoimmune diseases, and asthma. Secondly, eight TLR studies done in human pregnancies with chronic inflammatory factors, involving maternal blood, placenta, and cord blood, were reviewed. Lastly, ten TLR studies performed in peripheral blood of individuals with NDDs were included. Despite these studies, there were no studies which examined TLR function in both the pregnant mother and their offspring. Increased TLR2 and TLR4 mRNA and/or protein levels in peripheral blood were common in obesity, diabetes mellitus, depression, autoimmune thyroid disease, and rheumatoid arthritis. To a lesser degree, TLR 3, 7, 8, and 9 activation were found in peripheral blood of humans with autoimmune diseases and depression. In pregnancy, increased TLR4 mRNA levels were found in the peripheral blood of women with diabetes mellitus and systemic lupus erythematosus. Placental TLR activation was found in mothers with obesity or diabetes. Postnatally, dysregulated TLR response to stimulation was found in peripheral blood of individuals with NDDs. This systematic review found emerging evidence that TLR activation may represent a mechanistic link between maternal inflammation and offspring NDD, however the literature is incomplete and longitudinal outcome studies are lacking. Identification of pathogenic mechanisms in MIA could create preventive and therapeutic opportunities to mitigate NDD prevalence and severity.

Innate immunity drives pathogenesis of rheumatoid arthritis

Rheumatoid arthritis (RA) is an autoimmune disease affecting ∼1% of the general population. This disease is characterized by persistent articular inflammation and joint damage driven by the proliferating synovial tissue fibroblasts as well as neutrophil, monocyte and lymphocyte trafficking into the synovium. The factors leading to RA pathogenesis remain poorly elucidated although genetic and environmental factors have been proposed to be the main contributors to RA. The majority of the early studies focused on the role of lymphocytes and adaptive immune responses in RA. However, in the past two decades, emerging studies showed that the innate immune system plays a critical role in the onset and progression of RA pathogenesis. Various innate immune cells including monocytes, macrophages and dendritic cells are involved in inflammatory responses seen in RA patients as well as in driving the activation of the adaptive immune system, which plays a major role in the later stages of the disease. Here we focus the discussion on the role of different innate immune cells and components in initiation and progression of RA. New therapeutic approaches targeting different inflammatory pathways and innate immune cells will be highlighted here. Recent emergence and the significant roles of innate lymphoid cells and inflammasomes will be also discussed.

Identification of dysregulated genes in rheumatoid arthritis based on bioinformatics analysis

BACKGROUND

Rheumatoid arthritis (RA) is a chronic auto-inflammatory disorder of joints. The present study aimed to identify the key genes in RA for better understanding the underlying mechanisms of RA.

METHODS

The integrated analysis of expression profiling was conducted to identify differentially expressed genes (DEGs) in RA. Moreover, functional annotation, protein-protein interaction (PPI) network and transcription factor (TF) regulatory network construction were applied for exploring the potential biological roles of DEGs in RA. In addition, the expression level of identified candidate DEGs was preliminarily detected in peripheral blood cells of RA patients in the GSE17755 dataset. Quantitative real-time polymerase chain reaction (qRT-PCR) was conducted to validate the expression levels of identified DEGs in RA.

RESULTS

A total of 378 DEGs, including 202 up- and 176 down-regulated genes, were identified in synovial tissues of RA patients compared with healthy controls. DEGs were significantly enriched in axon guidance, RNA transport and MAPK signaling pathway. RBFOX2, LCK and SERBP1 were the hub proteins in the PPI network. In the TF-target gene network, RBFOX2, POU6F1, WIPF1 and PFKFB3 had the high connectivity with TFs. The expression status of 11 candidate DEGs was detected in GSE17755, the expression levels of MAT2A and NSA2 were significantly down-regulated and CD47 had the up-regulated tendency in peripheral blood cells of patients with RA compared with healthy individuals. qRT-PCR results of MAT2A, NSA2, CD47 were compatible with our bioinformatics analyses.

DISCUSSION

Our study might provide valuable information for exploring the pathogenesis mechanism of RA and identifying the potential biomarkers for RA diagnosis.