PRediction Of Flares In Lupus With autoantibodiEs and Chemokines (PROFILE)

May 17, 2022 updated by: Maarten Limper, UMC Utrecht

Rationale: Systemic lupus erythematosus (SLE) is a chronic relapsing-remitting autoimmune disease with a wide range of clinical manifestations affecting several organs. Although the management of lupus patients has improved in the last years, accurate models for predicting disease progression are lacking.

Objective: To prospectively evaluate the predictive value of a combination of chemokines, MMPs/TIMPs, and autoantibody levels for predicting flares in patients with SLE Study design: prospective, observational single centre cohort study, conducted at the department of Rheumatology and Clinical Immunology of the UMC Utrecht Study population: Adult patients with SLE (according to EULAR/ACR criteria) under control in the UMC Utrecht.

Intervention (if applicable): n/a

Main study parameters/endpoints:

  • Profile of autoantibodies and chemokines in visits previous to recorded flares, compared to visits previous to no recorded flares. Risk calculations will be made using areas under the curve (AUC) for both individual markers as multivariate analysis
  • Changes in the profile of autoantibodies and chemokines in patients with lower reported quality of life measured by LupusQoL questionnaire, compared to previous visits of the same patient.
  • Changes in titer levels of autoantibodies before and after start of biological treatment.

Nature and extent of the burden and risks associated with participation, benefit and group relatedness: this is an observational study; the burden for patients is esteemed to be low. For some patients who regularly attend the outpatient clinic yearly, the four-times a year visits during two years will be more frequent, including more frequent blood sampling, compared to standard care. Furthermore, more blood will be drawn per sampling, compared to standard care.

Study Overview

Status

Recruiting

Detailed Description

Systemic lupus erythematosus (SLE) is a chronic relapsing-remitting autoimmune disease with a wide range of clinical manifestations affecting several organs. Although the management of lupus patients has improved in the last years, accurate models for predicting disease progression are lacking.

In clinical practice, SLE patients can be categorized into three groups:

  1. A large group of patients has 'quiescent' disease; after diagnosis of SLE and possibly a short induction treatment with corticosteroids, patients remain in a state of remission for years with hydroxychloroquine treatment only.
  2. A substantial group of patients has relapsing-and-remitting disease, with mostly cutaneous inflammation but without further organ involvement.
  3. A smaller group of patients has severe inflammation with extensive organ involvement, including lupus nephritis and neuropsychiatric SLE (npSLE) as the most threatening complications.

This stratification of patients is reflected by the frequency of hospital visits. Patients with more severe disease activity have a higher frequency of visits to the outpatient clinic and more frequently receive biologicals.(1) In the UMC Utrecht, patients in group 1. normally visit the outpatient clinic on a yearly basis, patients in group 2. visit 2-4 times a year and patients in group 3. are seen more frequently. However, some patients with quiescent disease for years can still present with an SLE exacerbation, and patients with frequent bouts of inflammation can eventually reach a remission state.

It would be of great value to be able to distinguish these patient categories early after diagnosis. This would aid the clinician in identifying those patients who can safely visit the outpatient clinic only once a year, and conversely, it would be possible to point out which patients should be monitored more closely. Ideally, this early distinction would also correspond with treatment decisions, that is, intensifying treatment when a flare is suspected, or tapering medication when there is a low risk profile. The ultimate goal would be to enable clinicians to identify high risk patients and to treat them with immunomodulating therapy before any inflammatory damage has occurred, for instance with the combination of rituximab and belimumab as is being studied right now.(2,3) The pathogenesis of SLE is highly complex. Genetic predispositions, proinflammatory and anti-inflammatory cytokines, autoantibodies, lymphocyte subset abnormalities as well as defects in the complement systems all have putative roles in the development of SLE. At present, tools that enable early patient stratification are lacking. Furthermore - except for a possible association of rise in anti-dsDNA-antibodies and the development of lupus nephritis - factors that can predict SLE flares have not been identified.

Active disease has a large impact on the life of SLE patients, since it is known to result in a lower health-related quality of life.(4) Fatigue is an important factor in patient reported quality of life, but interestingly, disease activity is not associated with fatigue.(5) This can lead to a discrepancy, where the clinician assesses the patient's disease activity to be under control, where the patient is still experiencing a large burden of disease. Due to lack of objective parameters correlating with patient reported outcomes, this discrepancy is difficult to interpret for physicians.

When considering factors that can be relevant for patient risk stratification, the role of (novel) autoantibodies in the pathogenesis of SLE should not be overlooked. Several autoantibodies have been shown to be of diagnostic value for SLE (anti-dsDNA, anti-SmD, anti-Rib-P, anti-PCNA, anti-Chromatin, anti-complement (C1q)) and changes in the level of autoantibodies can reflect disease activity.(6) However, dynamics of antibody levels on their own are insufficient to be used as predictors of lupus activity in individual patients. Moreover, some types of treatment, such as B-cell targeted therapy, are known to influence the dynamics of antibody levels, making them harder to interpret.

Some chemokines and matrix metalloproteases (MMPs) and their inhibitors (TIMPs) have been shown to provide an indication of subclinical injury or inflammation in other inflammatory diseases and in renal inflammation.(7-9) For example, urinary CXCL9 levels were found to be associated with risk of acute rejection of renal transplants and a decline in renal function.(10) In addition, serum levels of CXCL10 have been shown to correlate with lupus activity in patients with SLE.(11) Furthermore, urinary levels of CXCL10 have shown very promising results in the early detection of allograft rejection in kidney transplants. Currently, an international randomized controlled trial is investigation if early treatment of rejection, detected by urinary CXCL10, will improve outcomes. (12) As of yet, these urinary markers have not been studied in the context of SLE and lupus nephritis. Dynamic levels of these urine markers and the relation to their corresponding serum levels could serve as early indicators of nephritis.

The primary objective of this study will be to prospectively evaluate the predictive value of a combination of chemokines, MMPs/TIMPs, and autoantibody levels for predicting flares in patients with SLE. This approach allows identification of the markers with the best predictive value.

As a secondary objective, this study will investigate whether dynamic changes in autoantibody- and chemokine levels differ between patients treated with or without anti-B-cell therapy (for instance, with rituximab or belimumab). In patients treated with anti-B-cell therapy lower autoantibody levels are observed, which could influence the combination of markers being studied. Until now, it is unclear whether the degree of lowering autoantibody levels after treatment is correlated with treatment efficacy and whether changes in autoantibody levels in SLE patients treated with anti-B-cell therapy can be indicative of lupus flares. This study will give insight into this relationship.

The relationship of these biomarkers with patient reported quality of life and fatigue will be assessed. These markers might provide the physicians extra tools on how to interpret the discrepancy between objective measurements by the physician and patient reported outcomes.

This study will be conducted in the department of Rheumatology and Clinical Immunology in the UMC Utrecht, a tertiary care center with approximately 400 patients with SLE in care. This department is very experienced and successful in conducting large clinical and translational trials in the field of autoimmunity.(13-18) Together with two other Dutch academic hospitals, the Dutch SLE registry was founded, including not only all patients who are treated with belimumab, but at present almost 1000 Dutch SLE patients who are being followed clinically at least once a year. The department actively takes part in the current multi-center international BLISS-BELIVE study.(2) The proposed number of patients to be included in this study is 100, making it a large prospective cohort study in SLE related research.

Main hypothesis: A combination of levels of autoantibodies and chemokines can be used to predict flares in SLE patients.

Study Type

Observational

Enrollment (Anticipated)

100

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Locations

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

18 years and older (Adult, Older Adult)

Accepts Healthy Volunteers

No

Genders Eligible for Study

All

Sampling Method

Probability Sample

Study Population

Adult patients with SLE under control in the UMC Utrecht. Approximately 400 patients with SLE are under control in the UMC Utrecht, of which 100 are to be included in this study. Patients will be contacted by their treating physician and informed about the study. They will be asked for permission for one of the researcher of the PROFILE-study to contact them. If interested, they will receive the patient information about the study and informed consent will be obtained by one of the researchers.

Description

Inclusion Criteria:

  • In order to be eligible to participate in this study, a subject must meet all of the following criteria:

    • Have a diagnosis of SLE according to EULAR/ACR criteria
    • Age ≥ 18 years

Exclusion Criteria:

  • A potential subject who meets any of the following criteria will be excluded from participation in this study:

    • Subjects participating in another study in which the subject receives immunosuppressant medication

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Observational Models: Cohort
  • Time Perspectives: Prospective

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Autoantibody and chemokine profile in patients who suffer from a lupus flare as measured by a SLE Disease Activity Index (SLEDAI) of > 6 in comparison with the profiles of patients who do not have a lupus flare
Time Frame: after last visit last patient; anticipated three years after first inclusion, i.e. August 2024

Profile of autoantibodies and chemokines in visits previous to recorded flares, compared to visits previous to no recorded flares. Autoantibodies will be both measured in a qualitative and a (semi-)quantitative way, expressed as present/non-present and as IU/mL. Chemokines will be quantitavely measured and expressed in the appropriate units

Autoantibody assessment The following assays will be used to evaluate the presence of autoantibodies and chemokines

  • Anti-double stranded DNA (anti-dsDNA)
  • Anti-Smith protein D (anti-SmD)
  • Anti-Ribosomal P protein (anti-Rib-P)
  • Anti-Proliferating cell nuclear antigen (anti-PCNA)
  • Anti-Chromatin
  • Anti-complement component 1q (anti-C1q)
  • B-Lymphocyte Stimulator (BLyS, or B-cell activating factor/BAFF)
  • CXCL2
  • CXCL9
  • CXCL10

Urine markers

  • CXCL2
  • CXCL9
  • CXCL10
  • MMP-1
  • MMP-7
  • TIMP-1
after last visit last patient; anticipated three years after first inclusion, i.e. August 2024

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
autoantibody profiles in correlation with patient reported outcomes
Time Frame: after last visit last patient; anticipated three years after first inclusion, i.e. August 2024
Changes in the profile of autoantibodies and chemokines in patients with lower reported quality of life measured by LupusQoL questionnaire, compared to previous visits of the same patient; changes in the profile of autoantibodies and chemokines in patients with more reported fatigue, measured by Fatigue severity scale questionnaire, compared to previous visits of the same patient.
after last visit last patient; anticipated three years after first inclusion, i.e. August 2024
Autoantibodies after start biological treatment
Time Frame: after last visit last patient; anticipated three years after first inclusion, i.e. August 2024

Changes in titer levels of autoantibodies before and after start of biological treatment

Autoantibody assessment The following assays will be used to evaluate the presence of autoantibodies and chemokines

  • Anti-double stranded DNA (anti-dsDNA)
  • Anti-Smith protein D (anti-SmD)
  • Anti-Ribosomal P protein (anti-Rib-P)
  • Anti-Proliferating cell nuclear antigen (anti-PCNA)
  • Anti-Chromatin
  • Anti-complement component 1q (anti-C1q)
  • B-Lymphocyte Stimulator (BLyS, or B-cell activating factor/BAFF)
  • CXCL2
  • CXCL9
  • CXCL10

Urine markers

  • CXCL2
  • CXCL9
  • CXCL10
  • MMP-1
  • MMP-7
  • TIMP-1
after last visit last patient; anticipated three years after first inclusion, i.e. August 2024
Profile of autoantibodies and chemokines between different risk groups.
Time Frame: after last visit last patient; anticipated three years after first inclusion, i.e. August 2024
Profile of autoantibodies and chemokines between different risk groups. Patients will be stratified to different risk groups, based on the frequency of previous flares and use of immunosuppressant drugs. Autoantibodies will be both measured in a qualitative and a (semi-)quantitative way, expressed as present/non-present and as IU/mL. Chemokines will be quantitavely measured and expressed in the appropriate units
after last visit last patient; anticipated three years after first inclusion, i.e. August 2024

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Investigators

  • Principal Investigator: Maarten Limper, MD PhD, UMC Utrecht

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

September 15, 2021

Primary Completion (Anticipated)

August 1, 2023

Study Completion (Anticipated)

August 1, 2024

Study Registration Dates

First Submitted

May 18, 2021

First Submitted That Met QC Criteria

June 25, 2021

First Posted (Actual)

July 6, 2021

Study Record Updates

Last Update Posted (Actual)

May 24, 2022

Last Update Submitted That Met QC Criteria

May 17, 2022

Last Verified

May 1, 2022

More Information

Terms related to this study

Other Study ID Numbers

  • NL75276.041.21

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

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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