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Differences in Bone Cell Activity Between Rheumatoid Arthritis and Ankylosing Spondylitis

Differences in Bone Cell Activity Between Rheumatoid Arthritis and Ankylosing Spondylitis

Status
Completed
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT01417455
Enrollment
101
Registered
2011-08-16
Start date
2012-01-31
Completion date
2015-05-31
Last updated
2016-03-21

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Ankylosing Spondylitis, Bone Resorption, Rheumatoid Arthritis

Keywords

Rheumatoid arthritis, Ankylosing spondylitis, Osteoclasts, TNF antagonists

Brief summary

Rheumatoid arthritis (RA) and ankylosing spondylitis (AS) are characterized by chronic systemic inflammation and share common pathogenic pathways. In both diseases, cytokines like TNF (tumor necrosis factor) and interleukin (IL)-17, known for their pro-inflammatory and osteoclastogenic effects, are relevant players, however, while RA is characterized by bone erosions, AS favors bone overgrowth. Understanding this paradox may hold the key for a better management of both diseases. Our hypothesis is that there are differences in the cellular environment and intracellular signaling between AS and RA. To test this hypothesis we will evaluate the cytokine milieu, the kinetics of bone cells differentiation and their activity in untreated and immunosuppressed RA and AS patients. We will also perform the same observations in patients exposed to targeted treatments.

Detailed description

Objectives: 1. Assess the influence of immune system cells in the modulation of bone turnover in patients with RA, AS and healthy donors (Task 2). 2. Analyze the osteoclast precursors and their differentiation into fully functional osteoclasts in a subgroup of patients with RA, AS and healthy donors (Task 3, 4 and 6). 3. Study osteoblast differentiation potential and activity in a subgroup of patients with RA and AS (Task 5 and 6) 4. Assess the effect of the therapy on bone cell differentiation and function in a subgroup of patients with RA and AS treated with TNF-blockers (Task 2, 3, 4 and 5). Work program and timetable Starting date: July 2011. Finishing date: July 2013 Task 1 - Patients Patients with RA diagnosis (according to the revised American Rheumatism Association criteria, 1988) and AS diagnosis (according to the European Spondyloarthropathy Study Group criteria, 1991) followed up in the Rheumatology and Bone and Metabolic Diseases Department of Hospital de Santa Maria (HSM) will be recruited for this study. Twenty-five patients with active RA (Disease Activity Score 28 (DAS28)\>3.2) and 25 patients with active AS (Bath Ankylosing Spondylitis Disease Activity Index (BASDAI)\>4) will be included in the study. Fifteen healthy donors, sex and age matched, will be recruited and used as a control group. Patients will be submitted to a clinical protocol that includes information on sex, age, disease duration, previous therapies, presence of rheumatoid factor and anti cyclic-citrullinated peptide antibodies, Human Leukocyte Antigen (HLA)-B27 status, DAS28 score and Health Assessment Questionnaire - HAQ (Health Assessment Questionnaire, for RA patients), BASDAI, Maastricht Ankylosing Spondylitis Enthesitis Score (MASES), Bath Ankylosing Spondylitis Functional Index - BASFI (for AS patients) and Ankylosing Spondylitis Disease Activity Score (ASDAS). Blood will be collected from patients before starting treatment with glucocorticoids and disease-modifying anti-rheumatic drugs (DMARDs: methotrexate, sulphasalazine and leflunomide) and 3 months after reaching a stable dose of these drugs. For those that latter on start TNF-blockers blood samples will be collected after 6 months of starting therapy. Because it is expected that only a minority of this initial cohort will need to be treated with TNF antagonists, a second group of 25 RA and 25 AS patients, selected for starting TNF antagonists, will be assessed before starting the drug and 6 months later. Written informed consent will be obtained from all patients prior to any protocol-specific procedure and this study will be conducted in accordance with the regulations governing clinical trials such as the Declaration of Helsinki, as amended in Tokyo (2004). This study was approved by HSM Ethics Committee. All the procedures in the following tasks will be performed in RA and AS patients (serum and blood) and healthy donors (serum), unless stated differently. Task 2 - Study of the inflammatory stimuli and bone turnover markers Sub-populations of immune system cells (neutrophils, B and T cell subpopulations, including Th17 cells) will be analysed for surface RANKL expression by flow cytometry. Pro-inflammatory cytokines like IL-1β, IL-6, IL-17A, IL-20, IL-23, TNF and bone modulating proteins (OPG, sRANKL, sclerostin and dickkopf-1) will be quantified by ELISA. Bone degradation enzymes like tartrate-resistant acid phosphatase (TRAP)5b and bone turnover markers like type I collagen carboxyterminal cross-linked telopeptide (ICTP) and procollagen type 1 amino-terminal propeptide (P1NP) will also be studied. The data obtained from flow cytometry experiments and protein quantification will be compared between diseases before and after treatment and with healthy donors. This will allow us to understand the disease-specific differences in the systemic and local inflammatory environment in untreated patients and the effect of the different therapies over this same environment. Task 3 - Analysis of osteoclast precursors and their differentiation into functional osteoclasts Circulating CD14+ cells will be characterized by analysing markers like HLA-DR, cluster of differentiation (CD)16, CD86, CD11b and CD62L, as well as osteoclast differentiation-associated proteins, such as the surface integrin CD51/CD61 (αVβ3 integrin), RANK (receptor activator of nf-kappa beta) and the calcitonin receptor by flow cytometry. In order to fully characterize the osteoclasts precursors, the expression of osteoclast-related genes like DC-STAMP, MITF (microphthalmia-associated transcription factor), CTSK (cathepsin K), TRACP and ATP6v0d2 in CD14+ cells will be assessed by real time quantitative polymerase chain reaction (RT-qPCR). The results obtained will be normalized with the housekeeping genes beta glucuronidase (GUSB) and phosphomannomutase-1 (PMM1). Data obtained from flow cytometry and gene expression experiments will be compared between treated and untreated patients and with healthy donors. This task will provide us quantitative information on the disease-specific changes of the CD14+ monocytes subpopulation and it will allow us to understand the effect of therapy in the circulating precursor cells. Task 4 - Function and cellular dynamics of the differentiated osteoclasts The isolated CD14+ monocytes will be cultured for 21 days in the presence of M-CSF (macrophage colony stimulating factor) and hrRANKL (human recombinant receptor activator of nf-kappa beta ligand) at 37º, 5% CO2 in multiwell culture plates. Osteoclasts will be analyzed at days 7, 14 and 21 of culture to assess cellular dynamics. Expression of osteoclast-specific genes will be analyzed at these time-points by RT-qPCR (see Task 3). Flow cytometry analysis will be performed to assess the CD51/CD61 and RANK surface expression. Data obtained during time points (days 7, 14 and 21) from patients and healthy controls will be compared with the same data obtained from the precursor cells. At the 21st culture day cells will be used in two functional assays: TRAP staining and resorption assay. In the TRAP staining assay we will assess the number of osteoclasts formed in culture by counting TRAP-positive multinucleated cells with more than 3 nuclei (osteoclasts). Comparison of this value with nuclei count in CD14+ monocytes in culture plates will allow us to determine the fusion index of these precursors. The resorption assay is carried by culturing monocytes over bone slices and allows us to measure the resorption activity of functional osteoclasts. This will be measured by image analysis of the bone slices stained with toluidine-blue where the resorbed area acquires a blue to purple color. The analysis of the fusion rate of precursors and of the osteoclast resorbed area will allow us to identify differences in osteoclast function between RA and AS patients and healthy donors. Both monocytes and osteoclasts will be studied regarding the RANK/RANKL and the αVβ3 integrin and c-fms signalling pathways that lead to the recruitment and activation of TRAF6, tyrosine kinase Src and extracellular signal-regulated kinase (ERK)1/2 activating NF-kB and other transcription factors. These signalling pathways will be studied using the Luminex xMAP platform with EpiQuant Cell Signalling Assays (Millipore). Comparison of the results from untreated patients and controls will allow us to understand if there is an impairment in osteoclast differentiation/activation classical pathways in AS as compared to RA. The results obtained from treated and untreated patients will provide insight on the action of the therapies on osteoclast differentiation and function. Comparing overall results from untreated patients and healthy donors will allow us to understand key differences between osteoclast differentiation and activation in these pathologies. Task 5 - Function and cellular dynamics of osteoblasts In a subgroup of RA and AS patients submitted either to hip replacement or cervical surgery osteoblast differentiation will be studied. Immediately after surgery, a small piece of trabecular bone (1cm3) will be extracted from the sample in order to isolate the osteoblasts. After isolation, osteoblasts will be cultured in Dulbecco's minimal essential medium (DMEM) supplemented with vitaminD3 (10-8M) and cells will be studied at 80% confluence. Osteoblasts' function will be studied in vitro by methylthiazole tetrazolium (MTT) assay (cell proliferation), alkaline phosphatase staining and mineralization nodules formation. Cells will be also used for RNA extraction and gene expression analysis Specific genes that encode proteins such as osteopontin, collagen type I, osteocalcin, alkaline phosphatase, RANKL, osteoprotegerin, runx2 and osterix will be analyzed to characterize the isolated cells. These results will allow us to understand the differences in osteoblast differentiation and activity between diseases. Task 6 - Bone gene expression assays In a subgroup of RA and AS patients submitted either to hip replacement or cervical surgery we will frozen bone samples at -80ºC. With the bone still frozen, a small sample of trabecular bone will be reduced to fine powder in a cryogenic mill and the RNA extraction will be performed using TRIzol reagent. The resulting RNA will be assessed for its integrity and quantified in a Bioanalyser. Therefore, the RNA extracted will be the total of RNA present in bone, from blood, osteoblasts, osteoclasts, osteocytes, adipocytes and bone marrow cells. The gene expression both in the bone microenvironment and in the cells from the in vitro studies will be evaluated by RT-PCR. Specific genes that encode proteins both from osteoblasts and osteoclasts such as osteopontin, collagen type I, osteocalcin, alkaline phosphatase, RANKL, osteoprotegerin, runx2, osterix, cathepsin K, beta3 integrin subunit, calcitonin receptor, ATPase subunit d2, TRAF6, RANK, TRAP, the co-receptors OSCAR and TREM-2, among others, will be studied. Osteocytes' activity will also be assessed by the expression of specific genes, SOST, Dkk1, DMP-1, Phex, E11 antigen, MEPE and CD44. The genes that code the inflammatory cytokines IL-1, IL-6, IL-17 and TNF will also be studied. In order to assess the PCR efficiency, standard curves will be built from RNA extracted from frozen bone samples from individuals with normal bone mineral density and with no other disease that could have influence in bone metabolism. The osteoclast, osteoblast and osteocyte genes of interest will be quantified by the standard curve method. The RNA expression study on the bone samples will allow us to understand the local cell activity and it characterize bone cells and their function in a disease context.

Interventions

None listed

Sponsors

Merck Sharp & Dohme LLC
CollaboratorINDUSTRY
Instituto de Medicina Molecular João Lobo Antunes
Lead SponsorOTHER

Study design

Time perspective
PROSPECTIVE

Eligibility

Sex/Gender
ALL
Age
18 Years to 90 Years
Healthy volunteers
Yes

Inclusion criteria

* Patients with RA diagnosis (according to the revised American Rheumatism Association criteria, 1988) and AS diagnosis (according to the European Spondyloarthropathy Study Group criteria, 1991) followed up in the Rheumatology and Bone and Metabolic Diseases Department of Hospital de Santa Maria (HSM) will be recruited for this study. Patients have to have active RA (Disease Activity Score 28 (DAS28)\>3.2) or active AS (Bath Ankylosing Spondylitis Disease Activity Index (BASDAI)\>4).

Exclusion criteria

* Inactive disease

Design outcomes

Primary

MeasureTime frameDescription
Osteoclast Differentiation Ex-vivoat baseline and at 6 monthsOsteoclasts will be differentiated from untreated patients and patients under several TNF blockers.
Osteoclast Activity Ex-vivoat baseline and at 6 monthsTotal area resorbed by osteoclasts as percentage of total area analyzed

Countries

Portugal

Participant flow

Recruitment details

Patients with RA and AS were recruited from the Rheumatology and Bone Metabolic Disease Department, Hospital de Santa Maria, Lisbon Academic Medical Centre, Portugal from May 2011 to May 2014. Healthy donors were recruited among the Hospital and research centre personnel.

Pre-assignment details

Aparent discrepancy of Enrollment number (101) and Participant Flow module (147) derive from patient follow-up. Patients enrolled were 101. 16 RA were followed up on the RA with DMARDs cohort. 17 RA baseline for TNF-blockers were followed up in the RA with TNF blockers. 13 AS baseline for TNF-blockers were followed up in the AS with TNF blockers.

Participants by arm

ArmCount
Rheumatoid Arthritis
Active Rheumatoid Arthritis patients
16
Rheumatoid Arthritis With DMARDs
Patients that started DMARD therapy after the Baseline collection
16
Rheumatoid Arthritis Baseline for TNF-blockers
RA patients naive to TNF blockers recruited before the first administration of a TNF-blocker
17
Rheumatoid Arthritis With TNF-blockers
RA patients recruited at least 6 months after the start of a TNF-blocker
17
Ankylosing Spondylitis
Active Ankylosing Spondylitis
30
Ankylosing Spondylitis Baseline for TNF Blocker
Patients with Ankylosing spondylitis naive to TNF-blockers, before the first TNF-block administration
13
Ankylosing Spondylitis With TNF-blockers
Ankylosing spondylitis recruited after a minimum of 6 months after the start of a TNF-blocker.
13
Controls
Healthy donors age and sex matched to the patients
25
Total147

Baseline characteristics

CharacteristicRheumatoid ArthritisRheumatoid Arthritis With DMARDsRheumatoid Arthritis Baseline for TNF-blockersRheumatoid Arthritis With TNF-blockersAnkylosing SpondylitisAnkylosing Spondylitis Baseline for TNF BlockerAnkylosing Spondylitis With TNF-blockersControlsTotal
Age, Continuous50 years50 years50 years50 years40 years37 years37 years45 years45 years
CRP (mg/dl)0.3 mg/dl0.2 mg/dl1.4 mg/dl0.3 mg/dl0.8 mg/dl1.4 mg/dl0.1 mg/dlNA mg/dlNA mg/dl
Disease activity4.7 units on a scale2.4 units on a scale5.7 units on a scale2.9 units on a scale5.8 units on a scale3.8 units on a scale1.7 units on a scaleNA units on a scaleNA units on a scale
ESR (mm/hr)22 mm/hr13 mm/hr25 mm/hr21 mm/hr23 mm/hr30 mm/hr7 mm/hrNA mm/hrNA mm/hr
Sex: Female, Male
Female
11 Participants11 Participants12 Participants12 Participants12 Participants5 Participants5 Participants12 Participants80 Participants
Sex: Female, Male
Male
5 Participants5 Participants5 Participants5 Participants18 Participants8 Participants8 Participants13 Participants67 Participants
Symptoms duration (years)0.8 years1.3 years6 years7 years11 years10 years11 yearsNA yearsNA years

Adverse events

Event typeEG000
affected / at risk
EG001
affected / at risk
EG002
affected / at risk
EG003
affected / at risk
EG004
affected / at risk
EG005
affected / at risk
EG006
affected / at risk
EG007
affected / at risk
deaths
Total, all-cause mortality
— / —— / —— / —— / —— / —— / —— / —— / —
other
Total, other adverse events
0 / 160 / 160 / 170 / 170 / 300 / 130 / 130 / 0
serious
Total, serious adverse events
0 / 160 / 160 / 170 / 170 / 300 / 130 / 130 / 0

Outcome results

Primary

Osteoclast Activity Ex-vivo

Total area resorbed by osteoclasts as percentage of total area analyzed

Time frame: at baseline and at 6 months

ArmMeasureValue (MEDIAN)
Rheumatoid ArthritisOsteoclast Activity Ex-vivo39 percentage of resorbed area
Rheumatoid Arthritis With DMARDsOsteoclast Activity Ex-vivo11 percentage of resorbed area
Rheumatoid Arthritis Baseline for TNF-blockersOsteoclast Activity Ex-vivo4 percentage of resorbed area
Rheumatoid Arthritis With TNF-blockersOsteoclast Activity Ex-vivo0.6 percentage of resorbed area
Ankylosing SpondylitisOsteoclast Activity Ex-vivo16 percentage of resorbed area
Ankylosing Spondylitis Baseline for TNF BlockerOsteoclast Activity Ex-vivo2 percentage of resorbed area
Ankylosing Spondylitis With TNF-blockersOsteoclast Activity Ex-vivo10 percentage of resorbed area
ControlsOsteoclast Activity Ex-vivo10 percentage of resorbed area
Primary

Osteoclast Differentiation Ex-vivo

Osteoclasts will be differentiated from untreated patients and patients under several TNF blockers.

Time frame: at baseline and at 6 months

ArmMeasureValue (MEDIAN)
Rheumatoid ArthritisOsteoclast Differentiation Ex-vivo8 OC/mm2
Rheumatoid Arthritis With DMARDsOsteoclast Differentiation Ex-vivo12 OC/mm2
Rheumatoid Arthritis Baseline for TNF-blockersOsteoclast Differentiation Ex-vivo11 OC/mm2
Rheumatoid Arthritis With TNF-blockersOsteoclast Differentiation Ex-vivo5 OC/mm2
Ankylosing SpondylitisOsteoclast Differentiation Ex-vivo9 OC/mm2
Ankylosing Spondylitis Baseline for TNF BlockerOsteoclast Differentiation Ex-vivo3 OC/mm2
Ankylosing Spondylitis With TNF-blockersOsteoclast Differentiation Ex-vivo5 OC/mm2
ControlsOsteoclast Differentiation Ex-vivo19 OC/mm2

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026