In the analysis of peripheral blood gene expression, timely processing of samples is essential to ensure that measurements reflect in vivo biology, rather than ex vivo sample processing variables. The effect of processing delays on global gene expression patterns in peripheral blood mononuclear cells (PBMCs) was assessed by isolating and stabilizing PBMC-derived RNA from 3 individuals either immediately after phlebotomy or after a 4 h delay. RNA was labeled using NuGEN Ovation labeling and probed using the Affymetrix HG U133 Plus 2.0 GeneChip®. Comparison of gene expression levels (≥2-fold expression change and P < 0.05) identified 307 probe sets representing genes with increased expression and 46 indicating decreased expression after 4 h. These differentially expressed genes include many that are important to inflammatory, immunologic, and cancer pathways. Among others, CCR2, CCR5, TLR10, CD180, and IL-16 have decreased expression, whereas VEGF, IL8, SOCS2, SOCS3, CD69, and CD83 have increased expression after a 4 h processing delay. The trends in expression patterns associated with delayed processing were also apparent in an independent set of 276 arrays of RNA from human PBMC samples with varying processing times. These data indicate that the time between sample acquisition, initiation of processing, and when the RNA is stabilized should be a prime consideration when designing protocols for translational studies involving PBMC gene expression analysis.

Objective

To explore biologic correlates to age at onset in patients with juvenile idiopathic arthritis (JIA) using peripheral blood mononuclear cell (PBMC) gene expression analysis.

Methods

PBMCs were isolated from 56 healthy controls and 104 patients with recent-onset JIA (39 with persistent oligoarticular JIA, 45 with rheumatoid factor–negative polyarticular JIA, and 20 with systemic JIA). RNA was amplified and labeled using NuGEN Ovation, and gene expression was assessed with Affymetrix HG-U133 Plus 2.0 GeneChips.

Results

A total of 832 probe sets revealed gene expression differences (false discovery rate 5%) in PBMCs from children with oligoarticular JIA whose disease began before age 6 years (early-onset disease) compared with those whose disease began at or after age 6 years (late-onset disease). In patients with early-onset disease, there was greater expression of genes related to B cells and less expression of genes related to cells of the myeloid lineage. Support vector machine analyses identified samples from patients with early- or late-onset oligoarticular JIA (with 97% accuracy) or from patients with early- or late-onset polyarticular JIA (with 89% accuracy), but not from patients with systemic JIA or healthy controls. Principal components analysis showed that age at onset was the major classifier of samples from patients with oligoarticular JIA and patients with polyarticular JIA.

Conclusion

PBMC gene expression analysis reveals biologic differences between patients with early-and late-onset JIA, independent of classification based on the number of joints involved. These data suggest that age at onset may be an important parameter to consider in JIA classification. Furthermore, pathologic mechanisms may vary with age at onset, and understanding these processes may lead to improved treatment of JIA.

In the analysis of peripheral blood gene expression, timely processing of samples is essential to ensure that measurements reflect in vivo biology, rather than ex vivo sample processing variables. The effect of processing delays on global gene expression patterns in peripheral blood mononuclear cells (PBMCs) was assessed by isolating and stabilizing PBMC-derived RNA from 3 individuals either immediately after phlebotomy or after a 4 h delay. RNA was labeled using NuGEN Ovation labeling and probed using the Affymetrix HG U133 Plus 2.0 GeneChip®. Comparison of gene expression levels (≥2-fold expression change and P < 0.05) identified 307 probe sets representing genes with increased expression and 46 indicating decreased expression after 4 h. These differentially expressed genes include many that are important to inflammatory, immunologic, and cancer pathways. Among others, CCR2, CCR5, TLR10, CD180, and IL-16 have decreased expression, whereas VEGF, IL8, SOCS2, SOCS3, CD69, and CD83 have increased expression after a 4 h processing delay. The trends in expression patterns associated with delayed processing were also apparent in an independent set of 276 arrays of RNA from human PBMC samples with varying processing times. These data indicate that the time between sample acquisition, initiation of processing, and when the RNA is stabilized should be a prime consideration when designing protocols for translational studies involving PBMC gene expression analysis.

Objective

Microarray analysis was used to determine whether children with recent onset polyarticular juvenile idiopathic arthritis (JIA) exhibit biologically or clinically informative gene expression signatures in peripheral blood mononuclear cells (PBMC).

Methods

Peripheral blood samples were obtained from 59 healthy children and 61 children with polyarticular JIA prior to treatment with second-line medications, such as methotrexate or biological agents. RNA was extracted from Ficoll-isolated mononuclear cells, fluorescently labeled and hybridized to Affymetrix U133 Plus 2.0 GeneChips. Data were analyzed using ANOVA at a 5% false discovery rate threshold after Robust Multi-Array Average pre-processing and Distance Weighted Discrimination normalization.

Results

Initial analysis revealed 873 probe sets for genes that were differentially expressed between polyarticular JIA and controls. Hierarchical clustering of these probe sets distinguished three subgroups within polyarticular JIA. Prototypical subjects within each subgroup were identified and used to define subgroup-specific gene expression signatures. One of these signatures was associated with monocyte markers, another with transforming growth factor β-inducible genes, and a third with immediate-early genes. Correlation of gene expression signatures with clinical and biological features of JIA subgroups suggests relevance to aspects of disease activity and supports the division of polyarticular JIA into distinct subsets.

Conclusions

PBMC gene expression signatures in recent onset polyarticular JIA reflect discrete disease processes and offer a molecular classification of disease.

The BrkA protein of Bordetella pertussis inhibits killing by the antibody-dependent classical pathway of complement; however, susceptibility to complement can be highly variable. Log-phase bacteria grown in Stainer-Scholte (SS) broth plated on Bordet-Gengou (BG) agar were about 500 times more sensitive to killing by complement than stationary-phase SS-BG cultures. While always more susceptible to complement than the wild-type strain, a BrkA mutant displayed a similar growth phase variation in susceptibility to complement. Growth phase susceptibility to complement was also observed for a mutant constitutive for Bvg activation of BrkA, suggesting that modulation of virulence factor expression was not responsible for sensitivity to complement. Susceptibility was not due to differential antigenic expression, since serum adsorbed with complement-resistant, stationary-phase SS-BG cultures lacked bactericidal activity against B. pertussis harvested at all times during the growth cycle. These results suggest that log-phase susceptibility to complement is not due to variable expression of BrkA or antigenic differences and may be an inherent property of rapidly growing cultures. Implications for vaccine development are discussed.

Bordetella pertussis produces a 73-kDa protein, BrkA (Bordetella resistance to killing), which inhibits the bactericidal activity of complement. In this study we characterized the step in the complement cascade where BrkA acts, using three strains: a wild-type strain, a strain containing an insertional disruption of brkA, and a strain containing two copies of the brkA locus. Following incubation with 10% human serum, killing was greatest for the BrkA mutant, followed by that for the wild-type strain, while the strain with two copies of brkA was the most resistant. Complement activation was monitored by enzyme-linked immunosorbent assay (ELISA) or Western blotting. ELISAs for SC5b-9, the soluble membrane attack complex, showed that production of SC5b-9 was greatest with the brkA mutant, less with the wild type, and least with the strain containing two copies of brkA. Deposition of complement proteins on the bacteria was monitored by Western blotting. A decrease in deposition on the bacteria of C4, C3, and C9 corresponded with decreased complement sensitivity. Deposition of C1, however, was not affected by the presence of BrkA. These studies show that BrkA inhibits the classical pathway of complement activation and prevents accumulation of deposited C4.

Introduction

Previous observations suggest that active systemic juvenile idiopathic arthritis (sJIA) is associated with a prominent erythropoiesis gene-expression signature. The aim of this study was to determine the association of this signature with peripheral blood mononuclear cell (PBMC) subpopulations and its specificity for sJIA as compared with related conditions.

Methods

The 199 patients with JIA (23 sJIA and 176 non-sJIA) and 38 controls were studied. PBMCs were isolated and analyzed for multiple surface antigens with flow cytometry and for gene-expression profiles. The proportions of different PBMC subpopulations were compared among sJIA, non-sJIA patients, and controls and subsequently correlated with the strength of the erythropoiesis signature. Additional gene-expression data from patients with familial hemophagocytic lymphohistiocytosis (FHLH) and from a published sJIA cohort were analyzed to determine whether the erythropoiesis signature was present.

Results

Patients with sJIA had significantly increased proportions of immature cell populations, including CD34+ cells, correlating highly with the strength of the erythropoiesis signature. The erythropoiesis signature strongly overlapped with the gene-expression pattern in purified immature erythroid precursors. The expansion of immature cells was most prominently seen in patients with sJIA and anemia, even in the absence of reticulocytosis. Patients with non-sJIA and anemia did not exhibit the erythropoiesis signature. The erythropoiesis signature was found to be prominent in patients with FHLH and in a published cohort of patients with active sJIA, but not in patients with inactive sJIA.

Conclusions

An erythropoiesis signature in active sJIA is associated with the expansion of CD34+ cells, also is seen in some patients with FHLH and infection, and may be an indicator of ineffective erythropoiesis and hemophagocytosis due to hypercytokinemia.