A genome-wide screen for variants influencing certolizumab pegol response in a moderate to severe rheumatoid arthritis population

Genetics of rheumatoid arthritis

In the past four decades, a plethora of genetic association studies have been carried out in cohorts of patients with rheumatoid arthritis. These studies have highlighted key aspects of disease pathogenesis and suggested causal mechanisms. In this review, we discuss major advances in our understanding of the genetic architecture of rheumatoid arthritis susceptibility, severity and treatment response and explain how genetics supports current models of disease pathogenesis and outcome. We outline future research directions, like Mendelian randomisation, and present a number of potential avenues for clinical translation, including risk and outcome prediction, patient stratification into treatment response groups and pharmacological applications.

The Role of Semaphorins in the Pathogenesis of Rheumatoid Arthritis

Rheumatoid arthritis (RA) is one of the most common autoimmune diseases. Inflammation of the synovial fluid propagates the pathological process of angiogenesis. Semaphorins play a crucial role in the context of endothelial cell function, and their pleiotropic nature has various effects on the further development of RA. This narrative review summarises the various roles of semaphorins in the pathology of RA and whether they could play a role in developing novel RA treatment options.

-Omic Approaches and Treatment Response in Rheumatoid Arthritis

Rheumatoid arthritis (RA) is an inflammatory disorder characterized by an aberrant activation of innate and adaptive immune cells. There are different drugs used for the management of RA, including disease-modifying antirheumatic drugs (DMARDs). However, a significant percentage of RA patients do not initially respond to DMARDs. This interindividual variation in drug response is caused by a combination of environmental, genetic and epigenetic factors. In this sense, recent -omic studies have evidenced different molecular signatures involved in this lack of response. The aim of this review is to provide an updated overview of the potential role of -omic approaches, specifically genomics, epigenomics, transcriptomics, and proteomics, to identify molecular biomarkers to predict the clinical efficacy of therapies currently used in this disorder. Despite the great effort carried out in recent years, to date, there are still no validated biomarkers of response to the drugs currently used in RA. -Omic studies have evidenced significant differences in the molecular profiles associated with treatment response for the different drugs used in RA as well as for different cell types. Therefore, global and cell type-specific -omic studies analyzing response to the complete therapeutical arsenal used in RA, including less studied therapies, such as sarilumab and JAK inhibitors, are greatly needed.

Regulatory Role of miRNAs and lncRNAs in Gout

Objective

To explore the regulatory functions of ceRNA networks in the nosogenesis of gout and search for potential therapeutic targets.

Methods

We searched the GEO database and downloaded the lncRNA microarray chipset GSE160170. This matrix series was analyzed to yield differentially expressed lncRNAs and mRNAs. Then, the correlations between lncRNAs and miRNAs were obtained by comparing the highly conserved miRNA families. The predicted miRNA-regulating mRNAs were matched to the differentially expressed mRNAs from the chipset analyses to obtain miRNA–mRNA interactions. Next, we used the Cytoscape software to model ceRNA networks and the STRING database to determine their protein–protein interactions. The R software was used to algorithmically screen the functional pathways of key PPI modules in the ceRNA networks.

Results

A total of 354 lncRNAs (140 downregulated and 214 upregulated) and 693 mRNAs (399 downregulated and 294 upregulated) were differentially expressed between the gout group and the healthy group. The ceRNA network of differentially expressed lncRNAs contained 86 lncRNAs (35 downregulated and 51 upregulated), 29 miRNAs, and 57 mRNAs. The processes identified in the GO enrichment analysis included gene transcription, RNA polymerase II transcription, and the regulation of cell growth and apoptosis. The pathways identified in the KEGG enrichment analysis included IL-17, TNF, and MAPK signaling. Nine lncRNAs (AC104024, AC084082, AC083843, FAM182A, AC022819, FAM215B, AP000525, TTTY10, and ZNF346-IT1), eleven miRNAs (hsa-miR-1297, hsa-miR-17-5p, hsa-miR-429, hsa-miR-139-5p, hsa-miR-449c-5p, hsa-miR-125a-5p, hsa-miR-125b-5p, hsa-miR-23b-3p, hsa-miR-217, hsa-miR-363-3p, and hsa-miR-20b-5p), and nine mRNAs (JUN, CASP2, PMAIP1, FOS, TNFAIP3, MAP3K8, BTG2, NR4A2, and DUSP2) were identified in the exploration of the key modules.

Conclusion

Characterization of ceRNA networks could be a promising approach for better understanding the pathogenesis of gout, with the TTTY10/hsa-miR-139-5p/AP-1 axis likely to be of clinical significance.