Nicholas Knowlton

Development of a Multi-Biomarker Disease Activity Test for Rheumatoid Arthritis

Background Disease activity measurement is a key component of rheumatoid arthritis (RA) management. Biomarkers that capture the complex and heterogeneous biology of RA have the potential to complement clinical disease activity assessment. Objectives To develop a multi-biomarker disease activity (MBDA) test for rheumatoid arthritis. Methods Candidate serum protein biomarkers were selected from extensive literature screens, bioinformatics databases, mRNA expression and protein microarray data. Quantitative assays were identified and optimized for measuring candidate biomarkers in RA patient sera. Biomarkers with qualifying assays were prioritized in a series of studies based on their correlations to RA clinical disease activity (e.g. the Disease Activity Score 28-C-Reactive Protein [DAS28-CRP], a validated metric commonly used in clinical trials) and their contributions to multivariate models. Prioritized biomarkers were used to train an algorithm to measure disease activity, assessed by correlation to DAS and area under the receiver operating characteristic curve for classification of low vs. moderate/high disease activity. The effect of comorbidities on the MBDA score was evaluated using linear models with adjustment for multiple hypothesis testing. Results 130 candidate biomarkers were tested in feasibility studies and 25 were selected for algorithm training. Multi-biomarker statistical models outperformed individual biomarkers at estimating disease activity. Biomarker-based scores were significantly correlated with DAS28-CRP and could discriminate patients with low vs. moderate/high clinical disease activity. Such scores were also able to track changes in DAS28-CRP and were significantly associated with both joint inflammation measured by ultrasound and damage progression measured by radiography. The final MBDA algorithm uses 12 biomarkers to generate an MBDA score between 1 and 100. No significant effects on the MBDA score were found for common comorbidities. Conclusion We followed a stepwise approach to develop a quantitative serum-based measure of RA disease activity, based on 12-biomarkers, which was consistently associated with clinical disease activity levels.

Erroneous augmentation of multiplex assay measurements in patients with rheumatoid arthritis due to heterophilic binding by serum rheumatoid factor

OBJECTIVE Serum rheumatoid factor (RF) and other heterophilic antibodies potentially interfere with antibody-based immunoassays by nonspecifically binding detection reagents. The purpose of this study was to assess whether these factors confound multiplex-based immunoassays, which are used with increasing frequency to measure cytokine and chemokine analytes in patients with rheumatoid arthritis (RA). METHODS We performed multiplex immunoassays using different platforms to measure analyte concentrations in RA patient samples. Samples were depleted of RF by column-based affinity absorption or were exposed to agents that block heterophilic binding activity. RESULTS In RA patients with high-titer RF, 69% of analytes demonstrated at least a 2-fold stronger multiplex signal in non-RF-depleted samples as compared to RF-depleted samples. This degree of erroneous signal amplification was less frequent in low-titer RF samples (17% of analytes; P < 0.0000001). Signal amplification by heterophilic antibodies was blocked effectively by HeteroBlock (≥ 150 μg/ml). In 35 RA patients, multiplex signals for 14 of 22 analytes were amplified erroneously in unblocked samples as compared to blocked samples (some >100-fold), but only in patients with high-titer RF (P < 0.002). Two other blocking agents, heterophilic blocking reagent and immunoglobulin-inhibiting reagent, also blocked heterophilic activity. CONCLUSION All multiplex protein detection platforms we tested exhibited significant confounding by RF or other heterophilic antibodies. These findings have broad-reaching implications in the acquisition and interpretation of data derived from multiplex immunoassay testing of RA patient serum and possibly also in other conditions in which RF or other heterophilic antibodies may be present. Several available blocking agents effectively suppressed this erroneous signal amplification in the multiplex platforms tested.

Estrogen receptor signaling promotes dendritic cell differentiation by increasing expression of the transcription factor IRF4

During inflammation, elevated granulocyte macrophage-colony-stimulating factor (GM-CSF) directs the development of new dendritic cells (DCs). This pathway is influenced by environmental factors, and we previously showed that physiologic levels of estradiol, acting through estrogen receptor alpha (ERalpha), promote the GM-CSF-mediated differentiation of a CD11b(+) DC subset from myeloid progenitors (MPs). We now have identified interferon regulatory factor 4 (IRF4), a transcription factor induced by GM-CSF and critical for CD11b(+) DC development in vivo, as a target of ERalpha signaling during this process. In MPs, ERalpha potentiates and sustains GM-CSF induction of IRF4. Furthermore, retroviral delivery of the Irf4 cDNA to undifferentiated ERalpha(-/-) bone marrow cells restored the development of the estradiol/ERalpha-dependent DC population, indicating that an elevated amount of IRF4 protein substitutes for ERalpha signaling. Thus at an early stage in the MP response to GM-CSF, ERalpha signaling induces an elevated amount of IRF4, which leads to a developmental program underlying CD11b(+) DC differentiation.

Idiopathic inflammatory myopathies, signified by distinctive peripheral cytokines, chemokines and the TNF family members B-cell activating factor and a proliferation inducing ligand

OBJECTIVE Serum cytokines play an important role in the pathogenesis of myositis by initiating and perpetuating various cellular and humoral autoimmune processes. The aim of the present study was to describe a broad spectrum of T- and B-cell cytokines, growth factors and chemokines in patients with idiopathic inflammatory myopathies (IIMs) and healthy individuals. METHODS A protein array system, denoted as multiplex cytokine assay was utilized to measure simultaneously the levels of 24 circulating cytokines, including B-cell activating factor (BAFF) and a proliferation inducing ligand (APRIL) of patients with IIMs and healthy individuals. Additionally, correlational clustering and discriminant function analysis (DFA), two multivariate, supervised analysis methods were employed to identify a subset of biomarkers in order to describe potential functional interrelationships among these pathological cytokines. RESULTS Univariate analysis demonstrated that a complex set of immune and inflammatory modulating cytokines are significantly up-regulated in patients with IIMs relative to unaffected controls including IL-10, IL-13, IFN-α, epidermal growth factor (EGF), VEGF, fibroblast growth factor (FGF), CCL3 [macrophage inflammatory protein (MIP-1α)], CCL4 (MIP-1β) and CCL11 (eotaxin), whereas G-CSF was significantly reduced in IIM patients. Correlational clustering was able to discriminate between, and hence sub-classify patients with IIMs. DFA identified EGF, IFN-α, VEGF, CCL3 (MIP-1α) and IL-12p40, as analytes with the strongest discriminatory power among various myositis patients and controls. CONCLUSIONS Our findings suggest that these factors modulate myositis pathology and help to identify differences between subsets of the disease.

Gene expression in systemic lupus erythematosus: Bone marrow analysis differentiates active from inactive disease and reveals apoptosis and granulopoiesis signatures

OBJECTIVE The cells of the immune system originate from the bone marrow, where many of them also mature. This study was undertaken to examine gene expression in the bone marrow of patients with systemic lupus erythematosus (SLE), in order to better understand the aberrant immune response in this disease. METHODS Bone marrow mononuclear cells (BMMCs) from 20 SLE patients (11 with active disease and 9 with inactive disease) and peripheral blood mononuclear cells (PBMCs) from 27 patients (16 with active disease and 11 with inactive disease) were studied; BMMCs and PBMCs from 7 healthy individuals and 3 osteoarthritis patients were studied as controls. Samples were analyzed on genome-scale DNA microarrays, with 21,329 genes represented. RESULTS We identified 102 genes involved in various biologic processes that were differentially expressed between patient and control BMMCs; 53 of them are genes that are involved in major networks, including cell death, growth, signaling, and proliferation. Comparative analysis revealed 88 genes that were differentially expressed between bone marrow and blood, the majority of which are involved in cell growth and differentiation, cellular movement and morphology, immune response, and other hematopoietic cell functions. Unsupervised clustering of highly expressed genes revealed 2 major SLE patient clusters (active disease and inactive disease) based on gene expression in bone marrow, but not in peripheral blood. The up-regulated genes in the bone marrow of patients with active disease included genes involved in cell death and granulopoiesis. CONCLUSION Microarray analysis of the bone marrow differentiated active from inactive SLE and provided further evidence of the role of apoptosis and granulocytes in the pathogenesis of the disease.

Discriminators of mouse bladder response to intravesical Bacillus Calmette-Guerin (BCG)

BackgroundIntravesical Bacillus Calmette-Guerin (BCG) is an effective treatment for bladder superficial carcinoma and it is being tested in interstitial cystitis patients, but its precise mechanism of action remains poorly understood. It is not clear whether BCG induces the release of a unique set of cytokines apart from its pro-inflammatory effects. Therefore, we quantified bladder inflammatory responses and alterations in urinary cytokine protein induced by intravesical BCG and compared the results to non-specific pro-inflammatory stimuli (LPS and TNF-α). We went further to determine whether BCG treatment alters cytokine gene expression in the urinary bladder.MethodsC57BL/6 female mice received four weekly instillations of BCG, LPS, or TNF-α. Morphometric analyses were conducted in bladders isolated from all groups and urine was collected for multiplex analysis of 18 cytokines. In addition, chromatin immune precipitation combined with real-time polymerase chain reaction assay (CHIP/Q-PCR) was used to test whether intravesical BCG would alter bladder cytokine gene expression.ResultsAcute BCG instillation induced edema which was progressively replaced by an inflammatory infiltrate, composed primarily of neutrophils, in response to weekly administrations. Our morphological analysis suggests that these polymorphonuclear neutrophils are of prime importance for the bladder responses to BCG. Overall, the inflammation induced by BCG was higher than LPS or TNF-α treatment but the major difference observed was the unique granuloma formation in response to BCG. Among the cytokines measured, this study highlighted the importance of IL-1β, IL-2, IL-3, IL-4, IL-6, IL-10, IL-17, GM-CSF, KC, and Rantes as discriminators between generalized inflammation and BCG-specific inflammatory responses. CHIP/Q-PCR indicates that acute BCG instillation induced an up-regulation of IL-17A, IL-17B, and IL-17RA, whereas chronic BCG induced IL-17B, IL-17RA, and IL-17RB.ConclusionTo the best of our knowledge, the present work is the first to report that BCG induces an increase in the IL-17 family genes. In addition, BCG induces a unique type of persisting bladder inflammation different from TNF-α, LPS, and, most likely, other classical pro-inflammatory stimuli.

Gene Expression Profiling in Neutrophils From Children With Polyarticular Juvenile Idiopathic Arthritis

OBJECTIVE We have previously reported a defect in neutrophil activation in children with polyarticular juvenile idiopathic arthritis (JIA). The current study was undertaken to determine whether gene expression abnormalities persist in JIA in remission and to use systems biology analysis to elucidate pathologic pathways in polyarticular JIA. METHODS We performed gene expression profiling on neutrophils from children with polyarticular JIA. Children were grouped according to disease status. We studied 14 children with active disease who were taking medication, 8 children with clinical remission of disease who were taking medication (CRM status), and 6 children with clinical remission of disease who were not taking medication (CR status). We also studied 13 healthy children whose age ranges overlapped those of the patients. RESULTS Neutrophil abnormalities persisted in children with polyarticular JIA even after disease remission was achieved. Children with active disease and those with CRM status showed no differences in expression of specific genes, although they could be separated on cluster analysis. A comparison of children with CR status and healthy control children revealed networks of pro- and antiinflammatory genes that suggested that remission is a state of homeostasis and balance rather than a return to normal immune function. Furthermore, gene overexpression in patients with CR status supports the hypothesis that neutrophils play a role in regulating adaptive immunity in this disease. CONCLUSION Neutrophil gene profiling in polyarticular JIA suggests important roles for neutrophils in disease pathogenesis. These findings suggest the presence of complex interactions between innate and adaptive immunity, that are not easily modeled in conventional, linear, reductionist systems.

Microarray Data Analysis Toolbox (MDAT): for normalization, adjustment and analysis of gene expression data

SUMMARY We introduce a novel Matlab toolbox for microarray data analysis. This toolbox uses normalization based upon a normally distributed background and differential gene expression based on five statistical measures. The objects in this toolbox are open source and can be implemented to suit your application. AVAILABILITY MDAT v1.0 is a Matlab toolbox and requires Matlab to run. MDAT is freely available at http://microarray.omrf.org/publications/2004/knowlton/MDAT.zip.

Statistical monitoring of weak spots for improvement of normalization and ratio estimates in microarrays

BackgroundSeveral aspects of microarray data analysis are dependent on identification of genes expressed at or near the limits of detection. For example, regression-based normalization methods rely on the premise that most genes in compared samples are expressed at similar levels and therefore require accurate identification of nonexpressed genes (additive noise) so that they can be excluded from the normalization procedure. Moreover, key regulatory genes can maintain stringent control of a given response at low expression levels. If arbitrary cutoffs are used for distinguishing expressed from nonexpressed genes, some of these key regulatory genes may be unnecessarily excluded from the analysis. Unfortunately, no accurate method for differentiating additive noise from genes expressed at low levels is currently available.ResultsWe developed a multistep procedure for analysis of mRNA expression data that robustly identifies the additive noise in a microarray experiment. This analysis is predicated on the fact that additive noise signals can be accurately identified by both distribution and statistical analysis.ConclusionsIdentification of additive noise in this manner allows exclusion of noncorrelated weak signals from regression-based normalization of compared profiles thus maximizing the accuracy of these methods. Moreover, genes expressed at very low levels can be clearly identified due to the fact that their expression distribution is stable and distinguishable from the random pattern of additive noise.

Analysis of the interaction of extracellular matrix and phenotype of bladder cancer cells.

BackgroundThe extracellular matrix has a major effect upon the malignant properties of bladder cancer cells both in vitro in 3-dimensional culture and in vivo. Comparing gene expression of several bladder cancer cells lines grown under permissive and suppressive conditions in 3-dimensional growth on cancer-derived and normal-derived basement membrane gels respectively and on plastic in conventional tissue culture provides a model system for investigating the interaction of malignancy and extracellular matrix. Understanding how the extracellular matrix affects the phenotype of bladder cancer cells may provide important clues to identify new markers or targets for therapy.MethodsFive bladder cancer cell lines and one immortalized, but non-tumorigenic, urothelial line were grown on Matrigel, a cancer-derived ECM, on SISgel, a normal-derived ECM, and on plastic, where the only ECM is derived from the cells themselves. The transcriptomes were analyzed on an array of 1186 well-annotated cancer derived cDNAs containing most of the major pathways for malignancy. Hypervariable genes expressing more variability across cell lines than a set expressing technical variability were analyzed further. Expression values were clustered, and to identify genes most likely to represent biological factors, statistically over-represented ontologies and transcriptional regulatory elements were identified.ResultsApproximately 400 of the 1186 total genes were expressed 2 SD above background. Approximately 100 genes were hypervariable in cells grown on each ECM, but the pattern was different in each case. A core of 20 were identified as hypervariable under all 3 growth conditions, and 33 were hypervariable on both SISgel and Matrigel, but not on plastic. Clustering of the hypervariable genes showed very different patterns for the same 6 cell types on the different ECM. Even when loss of cell cycle regulation was identified, different genes were involved, depending on the ECM. Under the most permissive conditions of growth where the malignant phenotype was fully expressed, activation of AKT was noted. TGFβ1 signaling played a major role in the response of bladder cancer cells to ECM. Identification of TREs on genes that clustered together suggested some clustering was driven by specific transcription factors.ConclusionThe extracellular matrix on which cancer cells are grown has a major effect on gene expression. A core of 20 malignancy-related genes were not affected by matrix, and 33 were differentially expressed on 3-dimensional culture as opposed to plastic. Other than these genes, the patterns of expression were very different in cells grown on SISgel than on Matrigel or even plastic, supporting the hypothesis that growth of bladder cancer cells on normal matrix suppresses some malignant functions. Unique underlying regulatory networks were driving gene expression and could be identified by the approach outlined here.