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Integrative Clinical, Molecular, and Computational Analysis Identify Novel Biomarkers and Differential Profiles of Anti-TNF Response in Rheumatoid Arthritis.

ABSTRACT: Background: This prospective multicenter study developed an integrative clinical and molecular longitudinal study in Rheumatoid Arthritis (RA) patients to explore changes in serologic parameters following anti-TNF therapy (TNF inhibitors, TNFi) and built on machine-learning algorithms aimed at the prediction of TNFi response, based on clinical and molecular profiles of RA patients. Methods: A total of 104 RA patients from two independent cohorts undergoing TNFi and 29 healthy donors (HD) were enrolled for the discovery and validation of prediction biomarkers. Serum samples were obtained at baseline and 6 months after treatment, and therapeutic efficacy was evaluated. Serum inflammatory profile, oxidative stress markers and NETosis-derived bioproducts were quantified and miRNomes were recognized by next-generation sequencing. Then, clinical and molecular changes induced by TNFi were delineated. Clinical and molecular signatures predictors of clinical response were assessed with supervised machine learning methods, using regularized logistic regressions. Results: Altered inflammatory, oxidative and NETosis-derived biomolecules were found in RA patients vs. HD, closely interconnected and associated with specific miRNA profiles. This altered molecular profile allowed the unsupervised division of three clusters of RA patients, showing distinctive clinical phenotypes, further linked to the TNFi effectiveness. Moreover, TNFi treatment reversed the molecular alterations in parallel to the clinical outcome. Machine-learning algorithms in the discovery cohort identified both, clinical and molecular signatures as potential predictors of response to TNFi treatment with high accuracy, which was further increased when both features were integrated in a mixed model (AUC: 0.91). These results were confirmed in the validation cohort. Conclusions: Our overall data suggest that: 1. RA patients undergoing anti-TNF-therapy conform distinctive clusters based on altered molecular profiles, which are directly linked to their clinical status at baseline. 2. Clinical effectiveness of anti-TNF therapy was divergent among these molecular clusters and associated with a specific modulation of the inflammatory response, the reestablishment of the altered oxidative status, the reduction of NETosis, and the reversion of related altered miRNAs. 3. The integrative analysis of the clinical and molecular profiles using machine learning allows the identification of novel signatures as potential predictors of therapeutic response to TNFi therapy.

SUBMITTER: Luque-Tevar M

PROVIDER: S-EPMC8022208 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundDifferential diagnosis among psoriatic arthritis (PsA) and seronegative rheumatoid arthritis (Abneg RA) can be challenging particularly in the clinical setting of peripheral phenotype and autoantibodies seronegativity. The aim of the study was to identify synovial tissue (ST) biomarkers differentially expressed in PsA and Abneg RA and test their predictive value of therapeutic response.MethodsThirty-four PsA patients [12 DMARD naive and 22 non-responder to methotrexate (MTX-IR)] with peripheral joint involvement and 55 Abneg RA (27 DMARD naive and 28 MTX-IR) underwent US-guided ST biopsy and immunohistochemistry (IHC) for CD68+, CD3+, CD20+, CD21+, CD117+, and CD138+ cells. After study entry, each DMARD-naive patient started MTX therapy and was followed in an outpatient setting for at least 6 months to define the achievement of Minimal Disease Activity (PsA) and DAS remission (Abneg RA) status respectively. Each IR-MTX patient was treated according to EULAR recommendations.ResultsAt study entry, IHC analysis revealed that PsA patients had comparable levels of lining and sublining CD68+ and sublining CD21+, CD20+, and CD3+ cells than Abneg RA, despite the therapeutic regimen. Moreover, regardless of the therapeutic scheme, PsA patients showed higher IHC score of CD117+ cells (p = 0.0004 and p = 0.0005 for naive and MTX-IR patients respectively) compared to Abneg RA patients. Conversely, Abneg RA patients showed higher IHC score of CD138+ cells, irrespective to the therapeutic scheme (p = 0.04 and p = 0.002 for naive and MTX-IR patients respectively). Analyzing the response rate to the therapeutic scheme, naive PsA patients reaching MDA status at 6 months follow-up, showed, at the study entry, lower IHC score of CD3+ cells compared to PsA patients not reaching this outcome (p = 0.02); conversely, naive Abneg RA patients reaching DAS remission status at 6 months follow-up, showed, at the study entry, lower IHC score of sublining CD68+ cells compared to Abneg RA patients not reaching this outcome (p < 0.001).ConclusionsCD117+ and CD138+ cells are differentially distributed among PsA and Abneg RA. Histological analysis of ST may help to solve the clinical overlap between the two diseases and provides prognostic data about the therapy success.

Project description:In 15 patients with rheumatoid arthritis the baseline expression (t=0) of type I IFN-regulated genes was determined in peripheral blood cells (PAXgene) using cDNA-microarrays and compared to levels one month after (t=1) anti-TNF treatment (infliximab). Therefore, we used 43K cDNA microarrays from the Stanford Functional Genomics Facility (http://microarray.org/sfgf/) printed on aminosilane-coated slides containing ~20.000 unique genes. Only one batch of arrays was used for all experiments. First DNA spots were UV-cross linked to the slide using 150-300 mJoules. Sample preparation and microarray hybridization were performed as described previously (1,2). Data storage and filtering was performed using the Stanford Microarray Database (http://genome-www5.stanford.edu//) as described previously. 1. van der Pouw Kraan TC, Wijbrandts CA, van Baarsen LG, Voskuyl AE, Rustenburg F, Baggen JM et al.: Rheumatoid arthritis subtypes identified by genomic profiling of peripheral blood cells: assignment of a type I interferon signature in a subpopulation of patients. Ann Rheum Dis 2007, 66: 1008-1014. 2. van der Pouw Kraan TC, van Baarsen LG, Rustenburg F, Baltus B, Fero M, Verweij CL: Gene expression profiling in rheumatology. Methods Mol Med 2007, 136: 305-327. Abbreviations: - Bnrs are the different patients analyzed - PAX or Paxgene indicates the total RNA was isolated from peripheral blood obtained in PAXgene tubes - CRS: common reference sample: We made a common reference that consisted of a mixture of mRNAs isolated from 11 different cell lines (Perou CM, Jeffrey SS, van de RM et al. Distinctive gene expression patterns in human mammary epithelial cells and breast cancers. Proc Natl Acad Sci U S A. 1999; 96:9212-9217) supplemented with RNA from rheumatoid synovial tissue, fibroblasts, and activated peripheral blood mononuclear cells (PBMCs). - PMT: photomultiplier tube: the sensitivity/intensity of the scanner can be adjusted to prevent spot saturation. Compound Based Treatment: anti-TNF (infliximab) reference_design

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Integrative Clinical, Molecular, and Computational Analysis Identify Novel Biomarkers and Differential Profiles of Anti-TNF Response in Rheumatoid Arthritis.

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