Protein profiling and network enrichment analysis in individuals before and after the onset of rheumatoid arthritis

Abstract

BackgroundAntibodies and upregulated cytokines and chemokines predate the onset of rheumatoid arthritis (RA) symptoms. We aimed to identify the pathways related to the early processes leading to RA development, as well as potential novel biomarkers, using multiple protein analyses.MethodsA case-control study was conducted within the Biobank of northern Sweden. The plasma samples from 118 pre-symptomatic individuals (207 samples; median predating time 4.1 years), 79 early RA patients, and 74 matched controls were analyzed. The levels of 122 unique proteins with an acknowledged relationship to autoimmunity were analyzed using 153 antibodies and a bead-based multiplex system (FlexMap3D; Luminex Corp.). The data were analyzed using multifactorial linear regression model, random forest, and network enrichment analysis (NEA) based on the 10 most significantly differentially expressed proteins for each two-by-two group comparison, using the MSigDB collection of hallmarks.ResultsThere was a high agreement between the different statistical methods to identify the most significant proteins. The adipogenesis and interferon alpha response hallmarks differentiated pre-symptomatic individuals from controls. These two hallmarks included proteins involved in innate immunity. Between pre-symptomatic individuals and RA patients, three hallmarks were identified as follows: apical junction, epithelial mesenchymal transition, and TGF-β signaling, including proteins suggestive of cell interaction, remodulation, and fibrosis. The adipogenesis and heme metabolism hallmarks differentiated RA patients from controls.ConclusionsWe confirm the importance of interferon alpha signaling and lipids in the early phases of RA development. Network enrichment analysis provides a tool for a deeper understanding of molecules involved at different phases of the disease progression.

Interferon-α-mediated therapeutic resistance in early rheumatoid arthritis implicates epigenetic reprogramming

“…The permissive effects of IFN-α on lymphocyte activation and development of autoimmune characteristics are well documented1 and murine transfer of IFN-α secreting dendritic cells propagated a persistent inflammatory arthritis 18. IFN-α associated with raised ESR in our cohort and in other autoimmune conditions12 but is also relevant prior to onset of inflammation as an IGS predicts progression to RA in ‘at risk’ cohorts 19–21. Furthermore, autoantibodies predate clinical presentation, and we demonstrate a clear association between IFN-α and RF titres in eRA consistent with previous observations in autoimmunity 12 17.…”

Rheumatoid cachexia: the underappreciated role of myoblast, macrophage and fibroblast interplay in the skeletal muscle niche

“…Gene expression analysis of skeletal muscle samples from RA patients demonstrated a correlation between disease activity and disability and increased concentrations of amino acid precursors to muscle fibrosis [20]. Analysis of blood samples from patients with active RA highlighted differences in cell-cell interactions, altered EMT, and increased TGF-β proteins suggestive of increased de novo ECM synthesis and fibrosis [89]. Fibrosis has been demonstrated in several tissues from RA patients and rodent studies.…”

Multivariate analysis reveals differentially expressed genes among distinct subtypes of diffuse astrocytic gliomas: diagnostic implications

“…Finally, a total of 44,723 probe sets corresponding to RNA expression probes of 21,336 genes were included in the analysis ( Supplementary Table S4). Bioinformatics analyses were implemented using the R-package rCUR to perform CUR decomposition 49 , limma to detect significant genes with differential gene expression levels between groups -providing models to compare many RNA targets simultaneously 50 , NMF to conduct NMF factorization 19 and MultBiplotR to perform Canonical Biplot analysis and representation 51 . The R-code to reproduce the analyses in this work is available in https ://githu b.com/anani eto/Scien tif-Repor ts-Gonza lez-Garci a_et_al.…”