Unfettered hyaluronan (HA) production is a hallmark of rheumatoid arthritis. The discovery of three genes encoding hyaluronan synthases (HASs) allows for the investigation of the signaling pathways leading to the activation of these genes. Our objective is to further understanding of the regulation of these genes as well as to find ways to prevent undesired gene activation. Human fibroblast-like synoviocytes were used in these experiments. mRNA levels of HAS were monitored by reverse transcriptase-PCR. A series of specific kinase inhibitors were used to investigate intracellular pathways leading to the up-regulation of HAS1. Our experiments, testing a series of stimuli including tumor necrosis factor ␣ (TNF␣), demonstrate that TGF-␤ is the most potent stimulus for HAS1 transcription. TGF-␤ activates HAS1 in a dose-dependent manner with a maximum effect at a concentration of 0.5-1 ng/ml. TGF-␤-induced HAS1 mRNA can be detected within 60 min and reaches maximal levels at 6 h. Furthermore, TGF-␤ treatment leads to an increase in synthase activity as determined by HA ELISA and by in vitro HA synthase assays. In contrast to the activatory effect on HAS1, TGF-␤ dosedependently suppresses HAS3 mRNA. As to the mode of action of TGF-␤-induced HAS1 mRNA activation, our experiments reveal that blocking p38 MAPK inhibited the TGF-␤ effect by 90%, blocking the MEK pathway led to an inhibition by 40%, and blocking the JNK pathway had no effect. The presented data might contribute to a better understanding of the role of TGF-␤ and of HA in the pathology of diseases.

Our data demonstrate that glucocorticoids suppress all genes encoding hyaluronan. We speculate that inhibition of HAS genes might account for the beneficial effect of glucocorticoid treatment, and also for the detrimental effects of long-term use.

It has become increasingly clear that hyaluronan is more than the simple matrix molecule it was once thought to be but instead takes part in a multitude of biological functions. Three genes encode for hyaluronan synthases (HAS). We demonstrated earlier that HAS2 and HAS3 are constitutively activated in type-B synoviocytes (fibroblast-like synoviocytes) and, furthermore, that the only gene that readily responds to stimulation with a series of proinflammatory cytokines is HAS1. Here we probe the involvement of the transcription factor NF-B in induced and noninduced HAS activation. Transforming growth factor (TGF) ␤1 as well as interleukin (IL)-1␤ are both strong inducers of HAS1 transcription. Stimulation of fibroblast-like synoviocytes with IL-1␤ resulted in rapid degradation of IB␣, an event that was preceded by IB␣ phosphorylation. Interestingly, TGF␤1 neither affected IB␣ levels, nor did it cause phosphorylation of IB␣. In addition, TGF␤1 had no effect on IB␤ and IB⑀ levels. Electrophorectic mobility shift assays demonstrate that IL-1␤ is a potent inducer of NF-B translocation; however, TGF␤1 treatment did not result in shifting bands. Two adenovirus constructs were used to further clarify differences in TGF␤1-and IL-1␤-induced HAS1 activation. Overexpressing IB␣ completely abolished the IL-1␤ effect on HAS1 but did not interfere with TGF␤1-induced HAS1 mRNA accumulation. Identical results were obtained when a dominant negative IKK was overexpressed. Interestingly, neither overexpression of IB␣ nor of IKK had any effect on HAS2 and HAS3 mRNA levels. Taken together, HAS1 can be activated by distinct pathways; IL-1␤ utilizes NF-B, and TGF␤1 does not. Furthermore, HAS2 and HAS3 are activated without the involvement of NF-B.

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Heterogeneity and multifactoriality complicate diagnostics and our understanding of pathogenesis of rheumatoid arthritis (RA). The only accepted serologic parameter (rheumatoid factor [RF]) is not disease specific, nor are any of several novel RA autoantibodies. We aimed at identifying profiles instead of individual autoreactivities allowing for unambiguous prediction of RA. Selected RA autoantigens were tested by ELISA (RF and anti-cyclic citrullinated peptide [anti-CCP]) or Western blot (heavy-chain-binding protein [BiP], heterogeneous ribonucleoprotein particle A2 [RA33/ hnRNP A2], calpastatin and calreticulin). Antibody reactivities were assayed from serum samples of 149 RA patients and 132 patients with other rheumatic diseases and from synovial fluids (SF) (58 RA, 65 non-RA). No single autoreactivity was sufficient for unambiguous prediction of RA. Frequencies of multiparameter profiles consisting of 3, 4, 5 and 6 autoreactivites were determined. Fifteen six-parameter serum profiles were exclusively expressed in RA patients, representing a cumulative sensitivity of 59%. Twelve SF profiles were exclusively expressed in 64% of RA patients. The self-learning classification algorithm CLASSIF1 was capable of accurately predicting RA when these profiles were present. Data profile analysis of RF/CCP/BiP/calpastatin/calreticulin/RA33 provided specific discrimination of 64% of RA. Most importantly, RA specific profiles were observed in 64% of patients with early disease (<12 months). For the first time, the accurate prediction of the class RA has been achieved by the use of multiparametric autoreactivity profiles. Because of early expression in disease, these profiles make it possible to start a disease-modifying therapy long before irreversible bone and joint destruction may develop. Additional RA-specific profiles are required to cover the entire group of RA patients. 2 Investigation of the reactivity patterns of antifilaggrin antibodies in sera and synovial fluids from patients with rheumatoid arthritis using citrullinated synthetic peptides