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The AMP RA/Lupus Network  is a collaborative group composed of leading scientists from all over the United States and internationally. The Network is conducting systems-level studies to understand the gene expression and signaling pathways in tissues from affected end organs, including synovium (the tissue that lines joints) for Rheumatoid Arthritis (RA), kidney and skin for lupus, and blood cells. The initial focus of research will be on RA and lupus, with the flexibility to expand in the future to related autoimmune diseases.

Scientists in the AMP RA/Lupus Network share their expertise in:

  • basic, clinical, and translational research;
  • technology invention, development, and implementation;
  • unique bioinformatics and statistical methodology.

They also have extensive interactions with biotechnology companies, pharmaceutical industry partners, disease foundations, and academic institutions. All of this is accomplished through an integrated governance structure that enables the best-informed contributions to science from all participants. In this partnership, all partners have agreed to make the AMP data and analyses publicly accessible to the broad biomedical community.



  • The overall goal of the AMP RA/Lupus Network is to identify relevant targets for diagnostics and treatment of RA, lupus, and related autoimmune diseases by defining shared and disease-specific biological pathways.
  • The more immediate goal is to test high impact ideas by using a collaborative trans-disciplinary, integrated team science approach that will:
    • Lay the foundation for a comprehensive understanding of mechanisms driving these diseases;
    • Stimulate early and applied research on cutting-edge technologies;
    • Advance the research enterprise by accelerating the discovery of disease pathways involved in autoimmune diseases.


  • Extensive profiling of gene expression and signaling in immune and tissue-resident cells in RA and systemic lupus erythematosus (SLE) to develop an integrated dataset of abnormalities at the molecular level.
  • An in-depth analysis of pathways active in target tissues, as well as blood, in RA synovium and SLE kidney tissue and skin, including identification of likely causative pathways in RA through the analysis of early disease populations.
  • Characterization of immune modules and how they can be used to understand differences between autoimmune diseases, between early and established disease, between responders and non-responders, and that may predict impending disease flare.
  • Identification of changes in circulating cells in blood reflecting activation of specific pathways in the tissues that can be used to improve targeting and serve as surrogate biomarkers.
  • Identification of changes in circulating cells that predict response to specific therapies, using the responder/non-responder comparison, as an enrichment strategy.
  • Development of the computational tools to permit the systematic approach to integrating the datasets into pathways, which would not otherwise be available.
  • Creating a roadmap for how to apply contemporary molecular technology to similarly assess therapeutic strategies in additional autoimmune diseases of interest.
  • Initial “de-risking” of the molecular markers and networks that are dysregulated as disease progresses, or that correlate with sensitivity and response to treatment.


Researchers in the AMP RA/Lupus Network analyze tissue and blood samples from people with RA, lupus, and eventually other autoimmune diseases to pinpoint relevant genes, proteins, pathways, and networks at a single cell level. This type of modular, molecular analysis allows comparisons across the diseases and provides insights into key aspects of the disease process. Scientists in the Network are also identifying differences between those RA patients who respond to therapies and those who do not, as well as providing a better systems level understanding of disease mechanisms in both RA and lupus. This knowledge is essential for the development of targeted therapies and for the application of existing and future therapies to appropriate patient populations.

The AMP RA/Lupus Network uses the following approaches:

  • Integrating new or developing technologies to analyze single cells and groups of cells involved in autoimmunity in novel ways.
  • Collecting tissue samples, including synovium from people with RA, and skin and kidney tissue from lupus patients, for molecular analysis.
  • Developing and implementing computational tools to integrate different data types to characterize molecular pathways.
  • Making the data available to the broad research community for further analysis.



The AMP RA/Lupus Network aims to address relevant challenges for rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE). The goal of this Network is to identify relevant drug targets for the treatment of autoimmune diseases by defining shared and disease-specific biological pathways. Projects in the AMP RA/Lupus Network are expected to progress in three phases: Research Phase 0 and Research Phase I will be conducted during the UH2 (Exploratory) funding period; Research Phase II will be conducted during the UH3 (Implementation) funding period.

AMP Research Phases:

Research Phase 0

  • Start-up activities and organization.
  • Initial testing of techniques for preparation and analysis of tissue and development of SOPs as a collaborative group.
  • Development of clinical, sample tracking, and assay databases.
  • Optimization of protocols, staining panels, dissociation methods, with a goal to minimize sources of non-biological variability.
  • Select methods for Phase I implementation, with most focus on RNA-Seq and CyToF.

Research Phase I

  • Enrollment of human subjects with RA and SLE, and analysis of blood and tissue of the initial clinical study cohort.
  • Systems analysis of data from initial cohorts to define pivotal disease pathways.
  • Pilot and Nested Studies to test emerging technologies, unique tissues, or cohort subsets.

Research Phase II

  • Defining within disease comparative cohorts and analytic approaches for scale-up.
  • Generation of all the profiling data on the fully enrolled cohorts.
  • Bioinformatics analysis for molecular stratification of patients and potential target identification.
  • Initial validation of targets for drug discovery research.
  • Reporting and roll-out of data access through a data interrogation portal.