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1.  Development of a Multi-Biomarker Disease Activity Test for Rheumatoid Arthritis 
PLoS ONE  2013;8(4):e60635.
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.
To develop a multi-biomarker disease activity (MBDA) test for rheumatoid arthritis.
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.
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.
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.
PMCID: PMC3621826  PMID: 23585841
2.  Brief FASD prevention intervention: physicians’ skills demonstrated in a clinical trial in Russia 
Alcohol consumption during pregnancy can result in a range of adverse pregnancy outcomes including Fetal Alcohol Spectrum Disorders (FASD). Risky drinking among Russian women constitutes a significant risk for alcohol-exposed pregnancies (AEP). Russian women report that obstetrics and gynecology (OB/GYN) physicians are the most important source of information about alcohol consumption during pregnancy and developing effective prevention interventions by OB/GYNs is indicated. This is the first study focused on implementation of an AEP prevention intervention at women’s clinics in Russia.
The paper describes the intervention protocol and addresses questions about the feasibility of a brief FASD prevention intervention delivered by OB/GYNs at women’s clinics in Russia. Brief physician intervention guidelines and two evidence-based FASD prevention interventions were utilized to design a brief dual-focused physician intervention (DFBPI) appropriate to Russian OB/GYN care. The questions answered were whether trained OB/GYN physicians could deliver DFBPI during women’s routine clinic visits, whether they maintained skills over time in clinical settings, and which specific intervention components were better maintained. Data were collected as part of a larger study aimed at evaluating effectiveness of DFBPI in reducing AEP risk in non-pregnant women. Methods of monitoring the intervention delivery included fidelity check lists (FCL) with the key components of the intervention completed by physicians and patients and live and audio taped observations of intervention sessions. Physicians (N = 23) and women (N = 372) independently completed FCL, and 78 audiotapes were coded.
The differences between women’s and physicians’ reports on individual items were not significant. Although the majority of physician and patient reports were consistent (N = 305), a discrepancy existed between the reports in 57 cases. Women reported more intervention components missing compared to physicians (p < 0.001). Discussing barriers was the most difficult component for physicians to implement, and OB/GYN demonstrated difficulties in discussing contraception methods.
The results supported the feasibility of the DFBPI in Russia. OB/GYN physicians trained in the DFBPI, monitored, and supported were able to implement and maintain skills during the study. In addition to the alcohol focus, DFBPI training needs to have a sufficient component to improve physicians’ skills in discussing contraception use.
PMCID: PMC3685594  PMID: 23294846
3.  Idiopathic inflammatory myopathies, signified by distinctive peripheral cytokines, chemokines and the TNF family members B-cell activating factor and a proliferation inducing ligand 
Rheumatology (Oxford, England)  2010;49(10):1867-1877.
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.
PMCID: PMC2936946  PMID: 20591831
Idiopathic inflammatory myopathies; Circulating cytokines; B-cell activating factor; A proliferation inducing ligand
4.  Oxidative Stress and Inflammation in Renal Patients and Healthy Subjects 
PLoS ONE  2011;6(7):e22360.
The first goal of this study was to measure the oxidative stress (OS) and relate it to lipoprotein variables in 35 renal patients before dialysis (CKD), 37 on hemodialysis (HD) and 63 healthy subjects. The method for OS was based on the ratio of cholesteryl esters (CE) containing C18/C16 fatty acids (R2) measured by gas chromatography (GC) which is a simple, direct, rapid and reliable procedure. The second goal was to investigate and identify a triacylglycerol peak on GC, referred to as TG48 (48 represents the sum of the three fatty acids carbon chain lengths) which was markedly increased in renal patients compared to healthy controls. We measured TG48 in patients and controls. Mass spectrometry (MS) and MS twice in tandem were used to analyze the fatty acid composition of TG48. MS showed that TG48 was abundant in saturated fatty acids (SFAs) that were known for their pro-inflammatory property. TG48 was significantly and inversely correlated with OS. Renal patients were characterized by higher OS and inflammation than healthy subjects. Inflammation correlated strongly with TG, VLDL-cholesterol, apolipoprotein (apo) C-III and apoC-III bound to apoB-containing lipoproteins, but not with either total cholesterol or LDL-cholesterol.
In conclusion, we have discovered a new inflammatory factor, TG48. It is characterized with TG rich in saturated fatty acids. Renal patients have increased TG48 than healthy controls.
PMCID: PMC3145638  PMID: 21829457
5.  Gene Expression Profiling in Neutrophils From Children With Polyarticular Juvenile Idiopathic Arthritis 
Arthritis and rheumatism  2009;60(5):1488-1495.
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.
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.
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.
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.
PMCID: PMC3063001  PMID: 19404961
6.  The Meaning of Clinical Remission in Polyarticular Juvenile Idiopathic Arthritis: Gene Expression Profiling in Peripheral Blood Mononuclear Cells Identifies Distinct Disease States 
Arthritis and rheumatism  2009;60(3):892-900.
The development of biomarkers to predict response to therapy in polyarticular juvenile idiopathic arthritis (JIA) is an important issue in pediatric rheumatology. An critical step in this process is determining whether there is biological meaning to clinically derived terms such as “active disease” and “remission.” We used a systems biology approach to address this question.
We performed gene transcriptional profiling on children who fit criteria for specific disease states as defined by consensus criteria developed by Wallace et al. (J Rheumatol 2005). Children with active disease (AD, n=14), clinical remission on medication (CRM, n=9) and clinical remission off medication (CR, n=6) were studied, in addition to healthy control children (n=13). Transcriptional profiles in peripheral blood mononuclear cells (PBMC) were obtained using Affymetrix U133 Plus 2.0 Arrays.
Hierarchical cluster analysis and predictive modeling demonstrated that the clinically-derived criteria represent biologically-distinct states. Minimal differences were seen between children with AD and those with CRM. Thus, underlying immune/inflammatory abnormalities persist despite response to therapy. The PBMC transcriptional profiles of children in remission did not return to normal, but revealed networks of pro- and anti-inflammatory genes suggesting that “remission” is a state of homeostasis, not a return to normal.
Gene transcriptional profiling of PBMC reveals that clinically-derived criteria for JIA disease states reflect underlying biology. We also demonstrate that neither CRM nor CR states result in resolution of the underlying inflammatory process, but are more likely to be states of balanced homeostasis between pro- and anti-inflammatory mechanisms.
PMCID: PMC2758237  PMID: 19248118
7.  Gene expression in human lupus: bone marrow differentiates active from inactive patients and displays apoptosis and granulopoiesis signatures 
Arthritis and rheumatism  2008;58(11):3541-3549.
The cells of the immune system originate from the bone marrow (BM), where many of them also mature. To better understand the aberrant immune response in systemic lupus erythematosus (SLE), we examined the BM in lupus patients using DNA microarrays and compared it to the peripheral blood (PB).
Patients and 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 active/ 11 inactive); BMMCs and PBMCs from 7 healthy individuals and 3 osteoarthritis patients served as controls. Samples were analyzed on genome-scale microarrays with 21,329 genes represented.
We found 102 differentially expressed genes between patients’ and controls’ BMMCs (unpaired student t-test), involved in various biologic processes; 53 of them are involved in major networks including cell death, growth, signaling and proliferation. Comparative analysis between BM and PB of patients identified 88 genes differentially expressed; 61 out of 88 participate in cell growth and differentiation, cellular movement and morphology, immune response and other hematopoietic cell functions. Unsupervised clustering of highly expressed genes revealed two major SLE patient clusters (active and inactive) in BM, but not in PB. The upregulated genes in the bone marrow of active patients included genes involved in cell death and granulopoiesis.
Microarray analysis of the bone marrow differentiates active from inactive lupus patients and provides further evidence for the role of apoptosis and granulocytes in the pathogenesis of the disease.
PMCID: PMC2760826  PMID: 18975309
8.  Disease-associated pathophysiologic structures in pediatric rheumatic diseases show characteristics of scale-free networks seen in physiologic systems: implications for pathogenesis and treatment 
While standard reductionist approaches have provided some insights into specific gene polymorphisms and molecular pathways involved in disease pathogenesis, our understanding of complex traits such as atherosclerosis or type 2 diabetes remains incomplete. Gene expression profiling provides an unprecedented opportunity to understand complex human diseases by providing a global view of the multiple interactions across the genome that are likely to contribute to disease pathogenesis. Thus, the goal of gene expression profiling is not to generate lists of differentially expressed genes, but to identify the physiologic or pathogenic processes and structures represented in the expression profile.
RNA was separately extracted from peripheral blood neutrophils and mononuclear leukocytes, labeled, and hybridized to genome level microarrays to generate expression profiles of children with polyarticular juvenile idiopathic arthritis, juvenile dermatomyositis relative to childhood controls. Statistically significantly differentially expressed genes were identified from samples of each disease relative to controls. Functional network analysis identified interactions between products of these differentially expressed genes.
In silico models of both diseases demonstrated similar features with properties of scale-free networks previously described in physiologic systems. These networks were observable in both cells of the innate immune system (neutrophils) and cells of the adaptive immune system (peripheral blood mononuclear cells).
Genome-level transcriptional profiling from childhood onset rheumatic diseases suggested complex interactions in two arms of the immune system in both diseases. The disease associated networks showed scale-free network patterns similar to those reported in normal physiology. We postulate that these features have important implications for therapy as such networks are relatively resistant to perturbation.
PMCID: PMC2649160  PMID: 19236715
9.  A Template-Driven Gene Selection Procedure * 
Systems biology  2006;153(1):4-12.
The hierarchical clustering and statistical techniques usually used to analyze microarray data do not inherently represent the underlying biology. Herein we present a hybrid approach involving characteristics of both supervised and unsupervised learning. This approach is based on template matching in which the interaction of the variables of inherent malignancy and the ability to express the malignant phenotype are modelled. Immortalized normal urothelial cells and bladder cancer cells of different malignancy were grown in conventional two-dimensional tissue culture and in three dimensions on extracellular matrices that were either permissive or restrictive for expression of the malignant phenotype. The transcriptome represents the effects of two variables--inherent malignancy and the modulatory effect of extracellular matrix. By assigning values to each of the biological variables of inherent malignancy and the ability to express the malignant phenotype, a template was constructed that encapsulated the interaction between them. Gene expression correlating both positively and negatively with the template were observed, but when iterative correlations were carried out, the different models for the template converged to the same actual template. A subset of 21 genes was identified that correlated with two a priori models or an optimized model above the 95% confidence limits identified in a bootstrap resampling with 5,000 permutations of the data set. The correlation coefficients of expression of several genes were > 0.8. Analysis of upstream transcriptional regulatory elements (TREs) confirmed these genes were not a randomly selected set of genes. Several TREs were identified as significantly over-expressed in the sample of 20 genes for which TREs were identified, and the high correlations of several genes were consistent with transcriptional co-regulation. We suggest the template method can be used to identify a unique set of genes for further investigation.
PMCID: PMC1618795  PMID: 16983830
Bladder cancer; phenotype; transcriptomics; extracellular matrix; malignancy; SIS-small intestine submucosa; ECM-extracellular matrix; TCC-transitional cell carcinoma
10.  Discriminators of mouse bladder response to intravesical Bacillus Calmette-Guerin (BCG) 
BMC Immunology  2007;8:6.
Intravesical 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.
C57BL/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.
Acute 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.
To 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.
PMCID: PMC1891101  PMID: 17506885
11.  Analysis of the interaction of extracellular matrix and phenotype of bladder cancer cells 
BMC Cancer  2006;6:12.
The 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.
Five 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.
Approximately 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.
The 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.
PMCID: PMC1360102  PMID: 16412233
12.  Hypervariable genes—experimental error or hidden dynamics 
Nucleic Acids Research  2004;32(19):e147.
In a homogeneous group of samples, not all genes of high variability stem from experimental errors in microarray experiments. These expression variations can be attributed to many factors including natural biological oscillations or metabolic processes. The behavior of these genes can tease out important clues about naturally occurring dynamic processes in the organism or experimental system under study. We developed a statistical procedure for the selection of genes with high variability denoted hypervariable (HV) genes. After the exclusion of low expressed genes and a stabilizing log-transformation, the majority of genes have comparable residual variability. Based on an F-test, HV genes are selected as having a statistically significant difference from the majority of variability stabilized genes measured by the ‘reference group’. A novel F-test clustering technique, further noted as ‘F-means clustering’, groups HV genes with similar variability patterns, presumably from their participation in a common dynamic biological process. F-means clustering establishes, for the first time, groups of co-expressed HV genes and is illustrated with microarray data from patients with juvenile rheumatoid arthritis and healthy controls.
PMCID: PMC528822  PMID: 15514108
13.  Statistical monitoring of weak spots for improvement of normalization and ratio estimates in microarrays 
BMC Bioinformatics  2004;5:53.
Several 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.
We 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.
Identification 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.
PMCID: PMC415561  PMID: 15128432

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