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BRIEF DEFINITIVE REPORT |
CORRESPONDENCE Thomas Jung: thomas.jung{at}novartis.com
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IL-1
and β, which were originally described as leukocytic pyrogens (1), are important regulators of the response to tissue damage and infections and mediate symptoms of fever, fatigue, pain, arthritis, and the hepatic acute phase responses including synthesis of C-reactive protein (CRP) and serum amyloid A protein (SAA) (2). Although studies using recombinant IL-1 in cancer patients confirmed the causative role of IL-1 for many of these symptoms (3), its direct investigation in man is hampered by the inability to detect IL-1 in biological fluids. cryopyrin-associated periodic syndromes (CAPS) is a clinical disease syndrome resulting from heterozygous gain-of-function mutations in NLRP3, the gene encoding cryopyrin. These mutations are supposed to promote release of IL-1, thereby providing an excellent paradigm for studying human IL-1 in vivo (4, 5). CAPS patients present with a spectrum of autoinflammatory diseases (6–11) involving almost all organ systems. NLRP3 mutations result in overactivation of caspase 1, the enzyme which cleaves the precursors of IL-1β, IL-18, and IL-33, members of the IL-1 family of cytokines, into their active forms (12). Although pro–IL-1
is not a substrate of caspase 1, recent studies in mice indicate that secretion of bioactive IL-1
requires functional NLRP3 (13) and activated caspase-1 (14). The recombinant IL-1 receptor antagonist (IL-1Ra) anakinra and the IL-1 receptor type I (IL-1RI) fusion protein rilonacept (IL-1 trap) have both induced clinical response in CAPS, demonstrating that signaling via the IL-1RI is crucial for the pathogenesis of CAPS (15–17). This strongly implies that neither IL-18 nor IL-33 plays significant roles in the disease, as neither of these two cytokines signals via the IL-1RI, and suggests that the disease is caused by overproduction of IL-1. By administering the human anti–IL-1β antibody canakinumab to CAPS patients, we provide evidence in this paper that IL-1β is pivotal in the pathogenesis of CAPS. Treatment with the antibody allowed the detection of IL-β and the creation of a mathematical model, which indicates that the in vivo production rate of IL-1β is fivefold higher in CAPS as compared with healthy subjects. Furthermore, in vivo IL-β production could be completely restored in these patients after canakinumab treatment.
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RESULTS AND DISCUSSION
Top
ABSTRACT
RESULTS AND DISCUSSION
MATERIALS AND METHODS
REFERENCES
Four patients with active disease each received an i.v. dose of 10 mg/kg canakinumab. Within 1 d, their urticarial rashes had disappeared, and a complete clinical response was achieved within 1 wk. CRP and SAA (Fig. 1 A), as well as plasma levels of IL-6 and IL-1Ra, returned to their normal ranges (Fig. 1 B), whereas levels of IL-1
and TNF-
did not change (Fig. 1 C). Sensitive markers for neutrophil (S100A12) and monocyte/macrophage activation (S100A8/9) (18) showed a rapid decline (Fig. 1 D) along with a normalization of neutrophil counts (Fig. 1 F). Levels of soluble IL-1RII in serum were within the normal range and showed no change after treatment (Fig. 1 E). Canakinumab induced long-lasting complete clinical response; the median time until redosing after relapse was 185 d (Table I). Patients were retreated i.v. with 1 mg/kg canakinumab, resulting in clinical remissions for a median of 90.5 d. Three further patients were enrolled into the study, and all seven patients received a fixed 150-mg s.c. dose with repeat treatment on clinical disease flare. The median treatment duration in the study was 26.5 mo (range 13.5–28.5) and the median duration of clinical remission after each 150-mg s.c. dose was 127 d (range 55–230). Together, these data indicate that CAPS is solely driven by IL-1β.
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3.5 h to that of the antibody (t1/2 30 d), thereby enabling the detection of IL-1β produced in vivo. Data, including concentrations of canakinumab, complexed IL-1β levels in blood, acute phase responses, and time until disease flares, were incorporated in the creation of the model (Fig. 2 A and supplemental text). The model included the diffusion exchange of canakinumab and IL-1β between the tissue and plasma compartments, plus elimination rates for free canakinumab, free IL-1β, and the canakinumab–IL-1β complexes from plasma. Because there is a direct, although nonlinear, relationship through the binding reaction between antibody, free IL-1β, and their complex, free IL-1β concentration can be calculated from measurement of canakinumab (Fig. 2 B) and total IL-1β (Fig. 2 C) levels. Canakinumab rapidly suppressed free central and interstitial IL-1β (Fig. 2 D) to levels that were insufficient to stimulate downstream responses such as CRP, SAA, and clinical flare (Fig. 2, E–G). All these response events had similar kinetic profiles, which were ultimately dependent on the concentration of canakinumab and were well described by the model over multiple dosing cycles.
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8 wk for IL-1β production to fully normalize in CAPS patients, despite the observed rapid clinical remission and normalization of CRP and SAA levels, suggesting that some level of inflammatory response was still ongoing. Although the mechanism is unclear, there was also complete normalization of S100A12 and S100A8/9 over a similar 8–10-wk period among CAPS patients who were treated with canakinumab, which had not occurred during long-term treatment with anakinra (H. Wittkowski, posters at The fifth International Congress on FMF and Systemic Autoinflammatory Diseases, Rome, 2008, and 15th Pediatric Rheumatology European Society Congress, London, UK, 2008). The similarities in the kinetics of S100A8/9 and IL-1β production suggest that S100A8/9 may serve as a sensitive marker for subclinical inflammation in CAPS (18). Whether IL-1β stimulates the production of S100A8/9 or S100A8/9 stimulates the production of IL-1β has not yet been fully elucidated. Although IL-1β has been shown to induce S100A8/9 production in human monocytes in vitro (22), engagement of TLR-4 by S100A8 stimulated the production of IL-1β (23).
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In summary, a targeted medicine approach using the anti–IL-1β antibody canakinumab in the rare monogenetic disease CAPS, along with data generated in healthy human subjects, has generated novel insights into in vivo IL-1β regulation. Modeling and simulation data indicated that the majority of elevated IL-1β in CAPS is produced by its own production and is completely restored after canakinumab treatment. Constitutive IL-1β in healthy subjects is IL-1β independent and not targeted by canakinumab. Further evolution of this mechanism-based concept should also allow new insights into more heterogeneous and complex chronic inflammatory diseases.
| MATERIALS AND METHODS |
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Determination of canakinumab and IL-1β in plasma.
Levels of canakinumab in human serum were determined using a competitive ELISA. A purified sheep antiidiotype anti-canakinumab antibody, generated in house, was immobilized on microtiter plates and serum samples were incubated in parallel with biotin-labeled canakinumab. Bound biotinylated canakinumab was detected by horseradish peroxidase–conjugated streptavidin with O-phenylendiamine dihydrochloride as substrate. The lowest level of quantification was 42.6 pg/ml, the intraday accuracy was 89.1–117%, and the interday accuracy was 100.6–105%. IL-1β levels in serum were detected using the Quantikine HS Human IL-1β immunoassay (R&D Systems), which had been validated in house for use even in the presence of large amounts of canakinumab. This assay detected total IL-1β, i.e., the sum of IL-1β complexed with canakinumab and any remaining free IL-1β. The limit of detection was 0.1 pg/ml in human serum. In an attempt to measure free IL-1β in the presence of canakinumab, all canakinumab–IL-1β complexes were removed from human serum by affinity chromatography using a Protein G column. The mean retention of IgG was calculated to be 97% of the total load in five experiments. Eluted free IL-1β was then measured using the Quantikine immunoassay.
Biomarkers.
The proteins IL-6, sIL-1Ra, TNF-
, IL-1
, and sIL-1RII were measured in plasma samples using kits obtained from R&D Systems. Normal ranges for healthy volunteers given by the manufacturer are the following: IL-6, 1.5 (0.4–9.9) pg/ml; sIL-1Ra, 230 (105–1,062) pg/ml; TNF-
, 1.0 (nd–2.1) pg/ml in EDTA plasma; IL-1
, <3.9 pg/ml (in serum); and sIL-1RII, 11 (6–21) ng/ml. S100 proteins were measured as previously described (26). The normal upper limit of A8/9 is 450 ng/ml and of S100A12 is 150 ng/ml in serum. CRP was measured in serum using a high-sensitivity automated microparticle-enhanced latex turbidimetric immunoassay (COBAS MIRA; Roche). The lower limit of detection was 0.2 mg/liter with an interassay coefficient of variant of 4.2% at 4 mg/liter and 6.3% at 1 mg/liter. SAA was measured in serum by latex nephelometry (BNII autoanalyzer; Dade Behring). The lower limit of detection was 0.7 mg/liter, with an interassay coefficient of variant of 2.6% at 15 mg/liter and 3.7% at 80 mg/liter. Standardization of both CRP and SAA assays is based on the respective World Health Organization International Reference Standards.
Mathematical models.
Two mathematical models were used to analyze the data from the Muckle-Wells patients, full details of which are given in the supplemental text. In the mechanism-based model, two binding reactions were written for canakinumab binding IL-1β, one for the plasma compartment and the other for the peripheral tissue interstitium. These were represented as differential equations. Hyperbolic equations of the Hill form were used for CRP, SAA, absolute neutrophil count, and the probability of flare, parameterized with stimulation constants, Kd, and Hill coefficients. They were all controlled by the concentration of IL-1β in the peripheral compartment. A first-order rate constant ka was used to describe the absorption of drug from the subcutaneous injection site. PSD was the permeability–surface area coefficient for exchange of monoclonal antibody and IL-1β–antibody complex between the plasma and tissue. PSL was the same for the ligand. VS and VP were the volumes for the systemic circulation and peripheral compartments. CLD, CLL, and CLDL were the clearances for drug, ligand, and drug–ligand complex. RL,ind was that part of the rate of ligand input (i.e., the expression level of IL-1β) that was independent of IL-1β–stimulated positive feedback (i.e., was dependent on other processes). RL,dep was the rate of IL-1β input dependent on IL-1β receptor modulation. Kd,R was the stimulation constant for the concentration of free IL-1β in the peripheral compartment affecting the modulator system. kM was the turnover rate constant for the modulator system, explaining delays between changes in the driving force, IL-1β, and observed responses. Although implemented in this model as a direct feedback of IL-1β stimulating its own production, it is realized that there may be a chain or network of interlinked responses resulting in the up-regulation of the cytokine, perhaps including some of those measured. However, without serial data on network entities, it is not possible to deduce the structure and dependencies; therefore, the most parsimonious model representation was chosen.
The simpler PK-flare model specified a two-compartment pharmacokinetic for canakinumab, linked directly to a probability function for the reoccurrence of disease symptoms. The probability function was a transformation of the statistical logistic equation into the form familiar to pharmacologists, the hyperbolic Hill equation. Beyond the conventional pharmacokinetic parameters, which are the same as those for the drug in the mechanistic binding model, the Hill equation specifies an inhibition constant, Ki, which is the concentration of canakinumab where there is a 50:50 probability of a flare occurring. The variance describing the range of canakinumab concentrations over which the flare probability changes from zero to one is the inverse of the Hill coefficient.
Real-time RT-PCR of IL-1β.
Peripheral blood samples were collected into PAXgene Blood RNA tubes (PreAnalytiX). Samples were stored at –80°C until analysis. Total RNA was extracted according to the manufacturer's instructions (QIAGEN). The integrity of the RNA samples was confirmed by 1% agarose gel electrophoresis, and the RNA concentration was determined spectrophotometrically. Real-time PCR was conducted using a 7900HT Sequence Detection System (SDS) and TaqMan assays (Applied Biosystems; Table I). For each measurement, an aliquot of
1 ng cDNA template was amplified. The following amplification conditions were used: 50°C for 2 min, 95°C for 10 min, and then 40 cycles of 95°C for 15 s, followed by 60°C for 1 min each. The fluorescence signals were processed using the SDS software (version 2.2). The cycle at which the fluorescence from a sample crosses the threshold is called the cycle threshold (Ct). The measured Ct value of the IL-1β transcript (TaqMan Assay Identifier Hs01555413_m1) was subtracted by the geometric mean of the Ct values of three reference genes, ACTG1 (TaqMan Assay Identifier Hs02340971_gH), GAPDH (TaqMan Assay Identifier Hs99999905_m1), and TINF2 (TaqMan Assay Identifier Hs00173291.m1) in the same sample to normalize between different samples. The samples were measured in duplicates and the averaged results were expressed as marker abundance normalized to the geometric mean of the three reference genes 2–
Ct.
Online supplemental material.
Supplemental text shows patient histories and describes in detail the derivation of pharmacokinetic and pharmacodynamic equations to build the model. Fig. S1 shows quantitative mRNA data for IL-1β as a function of time over 1 yr for individual patients. Table S1 shows the parameter values for the mechanistic pharmacokinetic, biomarker, and clinical response model. Table S2 shows the population parameter values for the PK-flare model. Online supplemental material is available at http://www.jem.org/cgi/content/full/jem.20082481/DC1.
| Acknowledgments |
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The authors Philip Lowe, Sandra Daniela Felix, Christiane Rordorf, Stephan Bek, Nicole Hartmann, Sophie Bosset, and Thomas Jung are employees of Novartis and were or are involved in the preclinical or clinical development of canakinumab. The other authors have no conflicting financial interests.
Submitted: 3 November 2008
Accepted: 12 March 2009
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