Title: Optimising Psoriatic Arthritis Therapy with Immunological Methods to Increase Standard Evaluation (OPTIMISE)
Funder: Medical Research Council

Abstract: AIM_x000D_ Psoriatic arthritis (PsA) is a type of arthritis that develops in some people with the skin condition psoriasis. It causes joints to become swollen and painful. PsA is a long-term condition that can get progressively worse. Our aim is to test whether we can predict, using blood tests, if people with PsA will respond to a type of drugs (called a biologic) leading to a reduction in inflamed joints and pain._x000D_ _x000D_ First, we will test if high levels of a type of blood cells called Th17 cells predicts response to biologic drugs. Secondly, does combining this blood result with other blood tests or an individual’s pattern of arthritis improve the prediction? We will use statistical tests to estimate how effective the tests are to select the best biologic drug for each person. This approach could ensure that patients receive their best drug first, ensuring their disease is controlled quickly improving quality of life._x000D_ _x000D_ BACKGROUND_x000D_ PsA develops in ~15% of people with psoriasis affecting around 150,000 people in the UK. For patients who do not respond to standard arthritis drugs, two different types of biologic drugs are available (called TNF or IL-17 blockers). In patients given one of these, only about 50% will find the drug relieves their symptoms, however importantly 50% will find no relief. Trying each drug takes time and then patients have to wait to see if another drugs works. _x000D_ _x000D_ Doctors do not currently know how to predict in advance which patient will respond best to each drug. A recent small study in Japan suggested that choosing the biologic drug based on patients’ blood Th17 cells could give better results than the doctors’ choice. However they only tested this in 28 people so we need to run a large study._x000D_ _x000D_ DESIGN/METHODS_x000D_ Patients with PsA about to start their first biologic will be invited to join the study. They will have a blood sample taken to measure their Th17 cells. The patients with high and low levels will be allocated equally to receive either TNF or IL-17 blockers. We will measure how well they respond to the drug after 6 months and test whether the initial blood result could have predicted their response. We will also combine this test with other blood results and the clinical pattern of a patient’s arthritis to see if this improves our ability to predict the best drug for each patient. _x000D_ _x000D_ If the test is able to predict the response, we will use statistical tests to estimate how effective it would be if this blood test was used to choose therapy in routine NHS care. If successful this could save money for the NHS if patients were given the best drug for them first and most importantly would improve patients’ quality of life earlier._x000D_ _x000D_ PPI_x000D_ Patients involved in research as part of the British PsA consortium patient communication group reviewed the project and advised on the study design. Patients will continue to advise throughout the project, including reviewing study information for patients, recruitment methods and questionnaires used, interpreting the results alongside the study team and aiding dissemination of results to patient organisations._x000D_ _x000D_ DISSEMINATION_x000D_ Our results will be presented at international research meetings and published in medical and scientific journals so that they can then be incorporated into international treatment recommendations. Results will be communicated to doctors and nurses via educational meetings and to patients via local and national patient support groups.

Lay abstract: Research Question: Can peripheral immunophenotype predict response to biologics in psoriatic arthritis (PsA)?_x000D_ _x000D_ Background: PsA is an inflammatory arthritis occurring in ~15% of people with psoriasis, affecting ~150,000 people in the UK. The current treatment of PsA follows a ‘step up’ approach using different conventional disease-modifying drugs followed by biologics if patients do not respond. Around 50% of patients require biologics. The current first line biologics for PsA target two main immunological pathways: tumour necrosis factor (TNF) or interleukin-17 (IL-17). Response rates for both are similar with the target of treatment achieved in ~50% of patients; however response cannot currently be predicted. A recent proof of concept study in PsA suggested that using peripheral immunophenotype to choose therapy could improve clinical outcomes over standard care._x000D_ _x000D_ Aims and objectives: In workstream (WS) 1, we will test the hypothesis, within a biomarker-stratified randomised controlled trial, that the baseline CD4 T cell activated Th17 immunophenotype predicts response to IL-17 and/or TNF inhibitors in PsA. We will validate the biomarker and optimal threshold (activated Th17>1.58%) for selecting therapy. In WS 2, additional analyses will identify if the model can be optimised by combining clinical (disease duration, psoriasis, enthesitis) and immunophenotypical (intracellular CD4 Th17 frequency, CD8 Tc17 frequency, MAIT cell frequency, immune transcriptomics) factors. We will use statistical modelling to predict the likely effectiveness of these precision medicine approaches compared to standard of care. In WS 3, we aim to further elucidate the mechanistic basis of psoriatic disease and the differential response to biologics by examining surface, intracellular and transcriptomic signatures in whole blood and immune subsets and establish a biobank for future mechanistic studies._x000D_ _x000D_ Methods: Patients with PsA eligible to start their first biologic will be recruited and baseline blood tests taken to assess their peripheral immunophenotype. They will be stratified equally by Th17 levels and randomised 1:1 to receive either TNF or IL-17 inhibitors. The primary analysis will establish the interaction between baseline immunophenotype and treatment on the primary outcome (proportion achieving the minimal disease activity criteria at week 24). Statistical modelling will be used to estimate how effective this approach could be in routine clinical practice. In secondary analysis, modelling will identify if this prediction model can be optimised further incorporating clinical phenotypes of disease and additional immunophenotyping techniques._x000D_ _x000D_ Timelines for delivery: The grant is proposed to start in April 2020 with first patient first visit by 1st January 2021 and all centres recruiting by 1st April 2021. Recruitment will be over 18 months with 6 months follow up, allowing 1 year for analysis, including statistical modelling and a final 3 months for publication and dissemination._x000D_ _x000D_ Anticipated impact and dissemination: The analysis will model the likely effectiveness of a precision medicine approach and could impact on future care rapidly as both drug classes are already approved in this indication. The proven biomarkers will be developed as a companion diagnostic to enable delivery in clinical practice. Dissemination will be via conference presentations and peer reviewed publications, potentially impacting on treatment guidelines.

Research activity codes: 4.1 DISCOVERY AND PRECLINICAL TESTING OF MARKERS AND TECHNOLOGIES;4.2 EVALUATION OF MARKERS AND TECHNOLOGIES;5.1 PHARMACEUTICALS;6.1 PHARMACEUTICALS
Health categories: INFLAMMATORY AND IMMUNE SYSTEM