| 1. |
- Lindberg, Johan, 1977-, et al.
(författare)
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Effect of infliximab on mRNA expression profiles in synovial tissue of rheumatoid arthritis patients
- 2006
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Ingår i: Arthritis Research & Therapy. - : Springer Science and Business Media LLC. - 1478-6362 .- 1478-6354. ; 8:6, s. R179-
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Tidskriftsartikel (refereegranskat)abstract
- We examined the gene expression profiles in arthroscopic biopsies retrieved from 10 rheumatoid arthritis patients before and after anti-TNF treatment with infliximab to investigate whether such profiles can be used to predict responses to the therapy, and to study effects of the therapy on the profiles. Responses to treatment were assessed using European League Against Rheumatism response criteria. Three patients were found to be good responders, five patients to be moderate responders and two patients to be nonresponders. The TNF-alpha status of the biopsies from each of the patients before treatment was also investigated immunohistochemically, and it was detected in biopsies from four of the patients, including all three of the good responders. The gene expression data demonstrate that all patients had unique gene expression signatures, with low intrapatient variability between biopsies. The data also revealed significant differences between the good responding and nonresponding patients (279 differentially expressed genes were detected, with a false discovery rate < 0.025). Among the identified genes we found that MMP-3 was significantly upregulated in good responders (log(2) fold change, 2.95) compared with nonresponders, providing further support for the potential of MMP-3 as a marker for good responses to therapy. An even more extensive list of 685 significantly differentially expressed genes was found between patients in whom TNF-alpha was found and nonresponders, indicating that TNF-alpha could be an important biomarker for successful infliximab treatment. Significant differences were also observed between biopsies taken before and after anti-TNF treatment, including 115 differentially expressed genes in the good responding group. Interestingly, the effect was even stronger in the group in which TNF-a was immunohistochemically detected before therapy. Here, 1,058 genes were differentially expressed, including many that were novel in this context (for example, CXCL3 and CXCL14). Subsequent Gene Ontology analysis revealed that several 'themes' were significantly over-represented that are known to be affected by anti-TNF treatment in inflammatory tissue; for example, immune response (GO:0006955), cell communication (GO:0007154), signal transduction (GO:0007165) and chemotaxis (GO:0006935). No genes reached statistical significance in the moderately responding or nonresponding groups. In conclusion, this pilot study suggests that further investigation is warranted on the usefulness of gene expression profiling of synovial tissue to predict and monitor the outcome of rheumatoid arthritis therapies.
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| 2. |
- Lindberg, Johan, 1977-
(författare)
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Transcriptional patterns in inflammatory disease
- 2008
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- In the studies this thesis is based upon, microarrays were applied to profilemRNA populations in biological samples to gain insights into transcriptionalpatterns and their relation to inflammatory disease.Rheumatoid arthritis (RA) is a chronic inflammatory disease, which leads todegradation of cartilage and bone. RA is characterized by synovial inflammationwith varying levels of tissue heterogeneity. This was confirmed by microarrayanalyses of multiple biopsies from the joints of 13 patients, which showed interindividualvariation in transcript populations to be higher than intra‐individualvariationTherapeutic antibodies targeting TNF‐α have revolutionized treatment of RA,although some patients do not respond well. Identification of non‐responders isimportant, not only because anti‐TNF treatment elevates the risk of infections,but also because of the cost of treatment. A proof‐of‐concept study to investigatetranscriptional effects of anti‐TNF treatment demonstrated that differencesbetween response groups could be identified and that these differences revealedbiological themes related to inflammatory disease.A subsequent study was therefore initiated with a larger cohort of 62 patients toinvestigate gene expression patterns in the synovium prior to anti‐TNFtreatment. Here, the heterogeneity was even more pronounced, thetranscriptional patterns were confounded by the presence of synovial aggregatesand only a weak therapy‐correlated signature was detected. The presence oflymphocyte aggregates was found to correlate to response to therapy, which isconsistent with previous findings indicating a higher level of inflammation ingood responding patients.Periodontitis is an inflammatory disease with many similarities to RA. Both areincurable chronic auto‐immune diseases, characterized by tissue destructionwith common genetic associations. Individuals with RA are at higher risk ofaccumulating significant periodontal problems than the general population. PGE2(prostaglandin E2) is known to stimulate inflammation and bone resorption inperiodontitis. In further studies, microarrays were applied in a time seriesdesign on human gingival fibroblats to explore the signal transduction pathwayscontrolling TNF‐α induced PGE2 synthesis in order to identify novel therapeutictargets. The JNK and NF‐kb pathways were identified as being differentiallyaffected by TNF‐a treatment. The transcriptional patterns were further verifiedusing antibodies against phosphorylated JNK/NF‐kb molecules and specificinhibitors of the JNK and NF‐kb signaling cascades.
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| 3. |
- Lindberg, Johan, 1977-, et al.
(författare)
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Variability in synovial inflammation in rheumatoid arthritis investigated by microarray technology
- 2006
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Ingår i: Arthritis Research & Therapy. - : Springer Science and Business Media LLC. - 1478-6362 .- 1478-6354. ; 8:2
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Tidskriftsartikel (refereegranskat)abstract
- In recent years microarray technology has been used increasingly to acquire knowledge about the pathogenic processes involved in rheumatoid arthritis. The present study investigated variations in gene expression in synovial tissues within and between patients with rheumatoid arthritis. This was done by applying microarray technology on multiple synovial biopsies obtained from the same knee joints. In this way the relative levels of intra-patient and inter-patient variation could be assessed. The biopsies were obtained from 13 different patients: 7 by orthopedic surgery and 6 by rheumatic arthroscopy. The data show that levels of heterogeneity varied substantially between the biopsies, because the number of genes found to be differentially expressed between pairs of biopsies from the same knee ranged from 6 to 2,133. Both arthroscopic and orthopedic biopsies were examined, allowing us to compare the two sampling methods. We found that the average number of differentially expressed genes between biopsies from the same patient was about three times larger in orthopedic than in arthroscopic biopsies. Using a parallel analysis of the tissues by immunohistochemistry, we also identified orthopedic biopsies that were unsuitable for gene expression analysis of synovial inflammation due to sampling of non-inflamed parts of the tissue. Removing these biopsies reduced the average number of differentially expressed genes between the orthopedic biopsies from 455 to 171, in comparison with 143 for the arthroscopic biopsies. Hierarchical clustering analysis showed that the remaining orthopedic and arthroscopic biopsies had gene expression signatures that were unique for each patient, apparently reflecting patient variation rather than tissue heterogeneity. Subsets of genes found to vary between biopsies were investigated for overrepresentation of biological processes by using gene ontology. This revealed representative 'themes' likely to vary between synovial biopsies affected by inflammatory disease.
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