{
  "abstract": "Objective To identify blood-based predictive and pharmacodynamic biomarkers at different timepoints in patients with active rheumatoid arthritis (RA) treated with anti-interleukin-6 receptor (anti-IL-6R) and anti-tumour necrosis factor-α (anti-TNF-α).Methods This study used blood samples from the MONARCH trial ( NCT02332590), a randomised, double-blind, phase III trial that compared the safety and efficacy of sarilumab (anti-IL-6R) and adalimumab (anti-TNF-α) monotherapy in patients with RA who were intolerant/inadequate responders to methotrexate. The study evaluated predictive biomarkers to anti-IL-6R and anti-TNF-α treatments at baseline and week 2 and pharmacodynamic biomarkers at week 2 and week 24 using Olink proteomics analysis (n=804 serum samples from 268 patients). Change in gene expression levels (n=522 peripheral blood samples from 261 patients) by both treatments was assessed using RNA sequencing analysis.Results Serum biomarkers most predictive to anti-IL-6R were different from those of anti-TNF-α; predictive biomarkers for anti-IL-6R were correlated with innate immune activation and synovial inflammation, while predictive biomarkers for anti-TNF-α seemed to be more T-cell and neutrophil-related. For baseline predictive biomarkers, we had to focus on relative prediction as the absolute prediction performance of single and combination biomarkers using cross-validation was limited. Additionally, the pharmacodynamic effects of anti-IL-6R and anti-TNF-α on biomarkers as well as pathway signatures were distinct.Conclusion The unbiased analysis of serum proteins identified biomarkers most predictive of anti-IL-6R and anti-TNF-α at different timepoints that could explain the difference in the response rate in patients with RA. Further, both biomarker and pathway results highlighted a differentiated mode of action of both treatments.",
  "authors": [
    {
      "affiliations": [
        "Sanofi R&D, Biostatistics, Industriepark Hoechst, Frankfurt am Main, Germany"
      ],
      "name": "Inoncent Agueusop"
    },
    {
      "affiliations": [
        "Sanofi R&D, Digital and Data Science, Industriepark Hoechst, Frankfurt am Main, Germany"
      ],
      "name": "Daniel Margerie"
    },
    {
      "affiliations": [
        "Sanofi R&D, Translational Sciences, Chilly-Mazarin, France"
      ],
      "name": "Anne Remaury"
    },
    {
      "affiliations": [
        "Sanofi R&D, Biostatistics, Industriepark Hoechst, Frankfurt am Main, Germany"
      ],
      "name": "Raphaël Brard"
    },
    {
      "affiliations": [
        "Sanofi R&D, Digital and Data Science, Industriepark Hoechst, Frankfurt am Main, Germany"
      ],
      "name": "Francesca Frau"
    },
    {
      "affiliations": [
        "Sanofi, Randomised Clinical Trials and Post Hoc Analyses Team, Gentilly, France"
      ],
      "name": "Emilie Gerard"
    },
    {
      "affiliations": [
        "Sanofi R&D, Translational Sciences, Chilly-Mazarin, France"
      ],
      "name": "Gilbert Thill"
    },
    {
      "affiliations": [
        "Sanofi R&D, Translational Sciences, Chilly-Mazarin, France"
      ],
      "name": "Yaligara Veeranagouda"
    },
    {
      "affiliations": [
        "Sanofi R&D, Translational Sciences, Chilly-Mazarin, France"
      ],
      "name": "Michel Didier"
    },
    {
      "affiliations": [
        "Sanofi R&D, Early Clinical Development Therapeutic Area Immunology and Inflammation, Industriepark Hoechst, Frankfurt am Main, Germany"
      ],
      "name": "Markus Kohlmann"
    },
    {
      "affiliations": [
        "Sanofi R&D, Immunology and Inflammation Therapeutic Area, Type 1/17 Immunology Cluster, Industriepark Hoechst, Frankfurt am Main, Germany"
      ],
      "name": "Matthias Herrmann"
    },
    {
      "affiliations": [
        "Sanofi R&D, Immunology and Inflammation Therapeutic Area, Type 1/17 Immunology Cluster, Industriepark Hoechst, Frankfurt am Main, Germany"
      ],
      "name": "Nadine Biesemann"
    }
  ],
  "title": "Deciphering differential biomarkers for anti-interleukin-6 receptor and anti-tumour necrosis factor-α treatment response in rheumatoid arthritis by multiomics analysis",
  "uid": "8fa2354b-d560-5c26-9aaa-e2df7384754a"
}