Potential diagnostic markers and therapeutic targets for rheumatoid arthritis with comorbid depression based on bioinformatics analysis

Abstract

BackgroundRheumatoid arthritis (RA) and depression are prevalent diseases that have a negative impact on the quality of life and place a significant economic burden on society. There is increasing evidence that the two diseases are closely related, which could make the disease outcomes worse. In this study, we aimed to identify diagnostic markers and analyzed the therapeutic potential of key genes.MethodsWe assessed the differentially expressed genes (DEGs) specific for RA and Major depressive disorder (MDD) and used weighted gene co-expression network analysis (WGCNA) to identify co-expressed gene modules by obtaining the Gene expression profile data from Gene Expression Omnibus (GEO) database. By using the STRING database, a protein–protein interaction (PPI) network constructed and identified key genes. We also employed two types of machine learning techniques to derive diagnostic markers, which were assessed for their association with immune cells and potential therapeutic effects. Molecular docking and in vitro experiments were used to validate these analytical results.ResultsIn total, 48 DEGs were identified in RA with comorbid MDD. The PPI network was combined with WGCNA to identify 26 key genes of RA with comorbid MDD. Machine learning-based methods indicated that RA combined with MDD is likely related to six diagnostic markers: AURKA, BTN3A2, CXCL10, ERAP2, MARCO, and PLA2G7. CXCL10 and MARCO are closely associated with diverse immune cells in RA. However, apart from PLA2G7, the expression levels of the other five genes were associated with the composition of the majority of immune cells in MDD. Molecular docking and in vitro studies have revealed that Aucubin (AU) exerts the therapeutic effect through the downregulation of CXCL10 and BTN3A2 gene expression in PC12 cells.ConclusionOur study indicates that six diagnostic markers were the basis of the comorbidity mechanism of RA and MDD and may also be potential therapeutic targets. Further mechanistic studies of the pathogenesis and treatment of RA and MDD may be able to identify new targets using these shared pathways.

Bioinformatics analysis of the potential receptor and therapeutic drugs for Alzheimer’s disease with comorbid Parkinson’s disease

“…Uniform manifold approximation and projection (UMAP) analysis was performed to assess homogeneity, repeatability, and differences between the groups. Samples selected with a median that is basically on the same horizontal line for subsequent analysis ( Nayan et al, 2023 ; Zhou et al, 2023 ).…”

“…Gene Ontology (GO) term and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed, and a protein–protein interaction network (Genomes) was constructed. The MCODE plugin, CytoHubba plug-in, and CytoNCA algorithms were used to identify key genes related to AD and comorbid PD ( Nayan et al, 2023 ; Zhou et al, 2023 ). A connectivity map (CMap) was generated to identify the optimal drug for treating AD and comorbid PD.…”

Current landscape of fecal microbiota transplantation in treating depression

“…Rheumatoid arthritis (RA) and depression are prevalent diseases that harm patient quality of life and impose a significant economic burden on society ( 28 , 29 ). Depression is a frequent comorbidity in patients with RA, which not only reduces treatment effectiveness but also increases the risk of disability and death ( 30 ).…”

Viewpoint: Could better understanding of risk factors for comorbidities pave the way towards personalized therapy in rheumatoid arthritis?

“…Some potential biomarkers associated with depression in RA are IL-6, CRP, fibrinogen and SAA, although the majority of these markers mainly reflect inflammation, which may not be specific enough to help in the decision of treatment choices. A recent work using bioinformatic analysis and machine learning-based methods identified several genes likely involved in the mechanism underlying RA with depression, and also indicated that RA combined with depression is related to six diagnostic markers ( AURKA , BTN3A2 , CXCL10 , ERAP2 , MARCO , PLA2G7 ) [ 6 ], which could represent candidate biomarkers but need to be validated in RA cohorts. Treatment of RA-associated depression seems to be different from other forms.…”

“…In RA patients both tocilizumab and infliximab decrease depressive symptoms, but their effect on depression without RA is not evident [ 7 ]. Vice versa, in cases of depression in RA, antidepressants do not seem to be highly effective [ 6 ]. For depression in RA, many studies have shown beneficial effect of non-pharmacological treatments, for example there is some data regarding the efficacy of mind–body therapies like meditation, mindfulness or yoga [ 8 ].…”