IntroductionPrevalence of insulin resistance and the metabolic syndrome has been reported to be high in rheumatoid arthritis (RA) patients. Tumor necrosis factor (TNF), a pro-inflammatory cytokine with a major pathogenetic role in RA, may promote insulin resistance by inducing Ser312 phosphorylation (p-Ser312) of insulin receptor substrate (IRS)-1 and downregulating phosphorylated (p-)AKT. We examined whether anti-TNF therapy improves insulin resistance in RA patients and assessed changes in the insulin signaling cascade.MethodsProspective study of RA patients receiving anti-TNF agents (infliximab, n = 49, adalimumab, n = 11, or etanercept, n = 1) due to high disease activity score in 28 joints (DAS28 > 5.1). A complete biochemical profile was obtained at weeks 0 and 12 of treatment. Insulin resistance, insulin sensitivity and pancreatic beta cell function were measured by the Homeostasis Model Assessment (HOMA-IR), the Quantitative Insulin Sensitivity Check Index (QUICKI) and the HOMA-B respectively. Protein extracts from peripheral blood mononuclear cells were assayed by western blot for p-Ser312 IRS-1 and p-AKT. RA patients treated with abatacept (CTLA4.Ig) were used as a control group for insulin signaling studies.ResultsAt study entry, RA patients with high insulin resistance (HOMA-IR above median) had significantly higher mean DAS28 (P = 0.011), serum triglycerides (P = 0.015), and systolic blood pressure levels (P = 0.024) than patients with low insulin resistance. After 12 weeks of anti-TNF therapy, patients with high insulin resistance demonstrated significant reduction in HOMA-IR (P < 0.001), HOMA-B (P = 0.001), serum triglycerides (P = 0.039), and increase in QUICKI (P < 0.001) and serum HDL-C (P = 0.022). Western blot analysis in seven active RA patients with high insulin resistance showed reduction in p-Ser312 IRS-1 (P = 0.043) and increase in p-AKT (P = 0.001) over the study period. In contrast, the effect of CTLA4.Ig on p-Ser312 IRS-1 and p-AKT levels was variable.ConclusionsAnti-TNF therapy improved insulin sensitivity and reversed defects in the insulin signaling cascade in RA patients with active disease and high insulin resistance. The impact of these biochemical changes in modifying cardiovascular disease burden in active RA patients remains to be seen.

BackgroundGene profiling studies provide important information for key molecules relevant to a disease but are less informative of protein-protein interactions, post-translational modifications and regulation by targeted subcellular localization. Integration of genomic data and construction of functional gene networks may provide additional insights into complex diseases such as systemic lupus erythematosus (SLE).Methodology/Principal FindingsWe analyzed gene expression microarray data of bone marrow mononuclear cells (BMMCs) from 20 SLE patients (11 with active disease) and 10 controls. Gene networks were constructed using the bioinformatic tool Ingenuity Gene Network Analysis. In SLE patients, comparative analysis of BMMCs genes revealed a network with 19 central nodes as major gene regulators including ERK, JNK, and p38 MAP kinases, insulin, Ca2+ and STAT3. Comparison between active versus inactive SLE identified 30 central nodes associated with immune response, protein synthesis, and post-transcriptional modification. A high degree of identity between networks in active SLE and non-Hodgkin's lymphoma (NHL) patients was found, with overlapping central nodes including kinases (MAPK, ERK, JNK, PKC), transcription factors (NF-kappaB, STAT3), and insulin. In validation studies, western blot analysis in splenic B cells from 5-month-old NZB/NZW F1 lupus mice showed activation of STAT3, ITGB2, HSPB1, ERK, JNK, p38, and p32 kinases, and downregulation of FOXO3 and VDR compared to normal C57Bl/6 mice.Conclusions/SignificanceGene network analysis of lupus BMMCs identified central gene regulators implicated in disease pathogenesis which could represent targets of novel therapies in human SLE. The high similarity between active SLE and NHL networks provides a molecular basis for the reported association of the former with lymphoid malignancies.

Background: Gene profiling studies provide important information for key molecules relevant to a disease but are less informative of protein-protein interactions, post-translational modifications and regulation by targeted subcellular localization. Integration of genomic data and construction of functional gene networks may provide additional insights into complex diseases such as systemic lupus erythematosus (SLE).Methodology/Principal Findings: We analyzed gene expression microarray data of bone marrow mononuclear cells (BMMCs) from 20 SLE patients (11 with active disease) and 10 controls. Gene networks were constructed using the bioinformatic tool Ingenuity Gene Network Analysis. In SLE patients, comparative analysis of BMMCs genes revealed a network with 19 central nodes as major gene regulators including ERK, JNK, and p38 MAP kinases, insulin, Ca 2+ and STAT3. Comparison between active versus inactive SLE identified 30 central nodes associated with immune response, protein synthesis, and post-transcriptional modification. A high degree of identity between networks in active SLE and non-Hodgkin's lymphoma (NHL) patients was found, with overlapping central nodes including kinases (MAPK, ERK, JNK, PKC), transcription factors (NF-kappaB, STAT3), and insulin. In validation studies, western blot analysis in splenic B cells from 5month-old NZB/NZW F1 lupus mice showed activation of STAT3, ITGB2, HSPB1, ERK, JNK, p38, and p32 kinases, and downregulation of FOXO3 and VDR compared to normal C57Bl/6 mice.Conclusions/Significance: Gene network analysis of lupus BMMCs identified central gene regulators implicated in disease pathogenesis which could represent targets of novel therapies in human SLE. The high similarity between active SLE and NHL networks provides a molecular basis for the reported association of the former with lymphoid malignancies.