Microbiota Analysis to Predict Outcomes of Rheumatoid Arthritis Patients Treated With JAK-inhibitor (MARAJA)

Personalized medicine in which each patient would receive the ideal personalized treatment and regimen, holds great promise to improve patient's care. However, previous studies failed to establish validated predictors of response to disease-modifying anti-rheumatic drugs (DMARDs) in patients with rheumatoid arthritis (RA). JAK inhibitors is a new class of DMARDs with great efficacy that might be even superior to anti-TNF drugs. As there are chemicals, their production cost is much cheaper than biological therapies and they will probably be central in patient's care in the coming years. Three are currently available: upadacitinib (UPA) tofacitinib and baricitinib. Our study will focus on UPA. Clinical outcomes mainly depend on i) factors influencing drug metabolism & concentrations and ii) adequacy between drug target and the inflammation pathways involved in the patient's disease. Humans carry in their gut trillions of germs, which are now known to be key players in health and disease. Those germs possess many enzymes and strongly modulate human enzymes expression. Gut-microbiota can, indeed, directly metabolize oral drugs and control the expression of the cytochrome P450 3A4 (CYP3A4), the main enzyme metabolizing TOFA. We showed, in a preliminary mouse experiment, that modifying gut-microbiota composition changes JAKi effects on signaling pathways. We thus believe that models including gut-microbiota composition together with markers of immune activation will predict clinical outcomes in RA patients treated with UPA.

Main and secondary objectives: To build predictive models for clinical outcomes (efficacy and safety) of RA patients treated with UPA based on microbiota analysis and markers f immune activation.

Methodolgy:

This multicentric longitudinal prospective study will include 60 patients with RA and inadequate response to methotrexate. The clinical outcomes studied will be EULAR non-response at 3 months as defined by the European league against rheumatism EULAR (primary outcome), achievement of low-disease activity at 6 months or incident adverse events (secondary outcomes). Gut microbiota will be assessed at baseline and M3 from thawed fecal samples. DNA will be purified using QIAamp DNA stool mini kit (Qiagen) and qualify using Qubit and TapeStation 4200 (Agilent). Library will be prepared by amplification of V1-V2 and V3-V4 regions from the bacterial 16S rRNA genes and will be qualified by q-PCR and amplicons will be sequenced by MiSeq (Illumina). Initial bioinformatic analysis and taxonomies will be carried out using the QIIME2 software. Immune activation will be assessed through JAK-STAT pathway activation by JAK STAT signaling pathway RT² profiler PCR Array (Qiagen) which profiles expression of 84 genes related to Jak and Stat-mediated signaling. UPA concentrations will be assessed by liquid chromatography-tandem mass spectrometry (LC-MS/MS) at baseline and 3 months. Statistical classifiers (Neural network algorithm, Linear and Quadratic Discriminant Analysis, Support Vector Machine, Random forests, Shrinkage Methods, or Nearest Neighbors) incorporating microbiome, JAK STAT signaling pathway gene expression and clinical data, will be used to determine profiles associated with UPA clinical response and safety. Patients who will prematurely stop UPA (before 3 months) for adverse events or loss of follow-up will be considered as non-responders.

Study Overview

• Status: Recruiting
• Conditions: Rheumatoid Arthritis
• Intervention / Treatment: Drug: Upadacitinib <15 MG [Rinvoq]

Detailed Description

Gut microbiota is becoming an important predictor of response and tolerance with anti-cancer drugs. However, its potential of prediction in other fields has poorly been explored.

Drug metabolism and concentrations of tofacitinib depend on body mass index, liver function and cytochrome P450 activity (especially CYP3A4). Humans carry in their gut trillions of germs, which are now known to be key players in health and disease. Those germs can strongly impact drug metabolism and concentrations based on 3 mechanisms. First, gut bacteria possess a huge pool of enzymes which catalyzes drug metabolism reactions. Second, gut microbiota regulates bile acid metabolism which play critical role in drug metabolism. Third, gut microbiota modulates the expression of cytochrome P450, especially CYP3A4, the main enzyme catabolizing Tofacitinib (TOFA).

In addition to drug metabolism, gut microbiota is a key driver of immune activation. Clinical response to CTLA-4 or anti-PD-1 strongly depends on gut microbiota in different cancers. The experiments performed to decipher the mechanisms involved suggested that microbiota composition affects immune responses, which will facilitate or not anti-tumoral efficacy of checkpoints inhibitors.

RA is a heterogeneous disease with predominant inflammation pathways varying dependent on patients. Some RA seem to be more dependent on IL-6 whereas others rely more on TNF-alpha, B or T cells. Gut microbiota was shown to affect all those different targets. Assessing baseline levels of JAK STAT signaling pathway gene expression will help us to link immune activation, gut microbiota and clinical response to UPA.

We hypothesize that gut-microbiota composition impacts JAKi metabolism, immune activation, and thus clinical response and has a great potential to predict clinical outcomes in patients with RA treated with UPA.

Study objectives :

1. Main objective

   To construct a model based on gut-microbiota composition, immune activation markers (JAK-STAT signalling pathway) and clinical data to predict UPA non-response at 3 months in RA patients with inadequate response to methotrexate.

2. Secondary objectives

   • To construct a model based on gut-microbiota composition, immune activation markers (JAK-STAT signalling pathway) and clinical data to predict low-disease activity at 6 months of UPA in RA patients with inadequate response to methotrexate.

   • To compare responders and non-responders and patients with or without adverse effects on UPA in terms of:

     • baseline gut-microbiota
     • UPA concentrations at 3 months
     • baseline JAK-STAT signalling pathway gene expression profile
     • baseline clinical data

   • To correlate changes in disease activity score based on 28 joint evaluation (DAS28, see annex for calculation) between month-3 and baseline with:

     • changes in gut microbiota
     • UPA concentrations
     • changes in JAK-STAT signaling

• Study Type: Observational
• Enrollment (Estimated): 60

Contacts and Locations

• Study Contact: Name: Claire I DAIEN, Prof; Phone Number: +33 467338710; Email: c-daien@chu-montpellier.fr
• Study Contact Backup: Name: Alban POUVREAU; Phone Number: +33 4 67 33 24 82; Email: a-boissin@chu-montpellier.fr

Study Locations

• France
  • Montpellier, France, 34295
    • Recruiting
    • CHU de Montpellier
    • Contact: Claire Daien

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years and older (Adult, Older Adult)
• Accepts Healthy Volunteers: N/A

• Sampling Method: Non-Probability Sample

Study Population

Patients with RA fulfilling American College of Rheumatology (ACR)/ European league against rheumatism (EULAR) 2010 criteria with inadequate response to MTX for who a treatment with UPA will be prescribed in standard care to control disease activity

Description

Inclusion Criteria:

• Patients with RA fulfilling American College of Rheumatology (ACR)/ European league against rheumatism (EULAR) 2010 criteria
• Patients with inadequate response to MTX
• Patients receiving MTX as adjuvant therapy or will receive UPA as monotherapy

Exclusion Criteria:

• Patients with contraindication to upadacitinib
• Patients previously treated with biological DMARDs or JAK inhibitors
• Patients treated with ≥ 10 mg/day of glucocorticoids
• Use of IV glucocorticoids in the previous month
• Previous use of biological DMARDs (TNF inhibitors, rituximab, abatacept, tocilizumab) or JAK inhibitors
• Absence of informed consent
• Pregnancy planned for the duration of the study, Women pregnant or breastfeeding women
• Major protected by law or patient under guardianship

Study Plan

How is the study designed?

Design Details

• Observational Models: Other
• Time Perspectives: Prospective

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
EULAR response	Response will be defined following European league against rheumatism EULAR definition that is a decrease >0.6 points of Disease-Activity-Score 28-joints (DAS28-CRP) and a DAS28-CRP≤5.1 at 3 months . Patients who will prematurely stop UPA (before 3 months) for adverse events, RA flair or loss of follow-up will be considered as non-responders.	3 months

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
EULAR good response	EULAR good-response at 3 and 6 months: DAS28-CRP≤3.2 and deltaDAS28 (M0-M3)>1.2	3 and 6 months
Achievement of low-disease activity:	DAS28-CRP at 6 months <3.2 and/or DAS28-ESR at 6 months <3.2	6 months
Adverse events	Incidence, relatedness, and severity of treatment-emergent SUSARs, SAEs, ARs and AEs will be evaluated continuously. Patients with adverse events occurring between study visits will be asked to contact the study center for AE reporting.	during the 6 month follow-up
Baseline gut-microbiota	microbiota will be described in terms of alpha and beta diversity, phylum, genus, OTU.	baseline, 3 and 6 months
UPA concentrations		0, 3 and 6 months
Baseline JAK-STAT signalling pathway gene expression profile	gene expression profile will include the level of expression of 84 genes	baseline
Baseline clinical data	DAS28-CRP, body-mass index, age and gender	baseline

Collaborators and Investigators

• Sponsor: University Hospital, Montpellier
• Investigators: Principal Investigator: Claire DAIEN, Prof, Montpellier Hospital and University

Study record dates

Study Major Dates

• Study Start (Actual): January 7, 2021
• Primary Completion (Estimated): April 1, 2024
• Study Completion (Estimated): October 1, 2024

Study Registration Dates

• First Submitted: August 24, 2020
• First Submitted That Met QC Criteria: August 24, 2020
• First Posted (Actual): August 28, 2020

Study Record Updates

• Last Update Posted (Actual): September 14, 2023
• Last Update Submitted That Met QC Criteria: September 13, 2023
• Last Verified: September 1, 2023

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Immune System Diseases; Autoimmune Diseases; Joint Diseases; Musculoskeletal Diseases; Rheumatic Diseases; Connective Tissue Diseases; Arthritis; Arthritis, Rheumatoid; Molecular Mechanisms of Pharmacological Action; Enzyme Inhibitors; Antirheumatic Agents; Protein Kinase Inhibitors; Janus Kinase Inhibitors; Upadacitinib
• Other Study ID Numbers: RECHMPL19_0224-UF7806

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No
• product manufactured in and exported from the U.S.: No