Molecular subsets in the gene expression signatures of scleroderma skin

Background

Scleroderma is a clinically heterogeneous disease with a complex phenotype. The disease is characterized by vascular dysfunction, tissue fibrosis, internal organ dysfunction, and immune dysfunction resulting in autoantibody production.

Methodology and Findings

We analyzed the genome-wide patterns of gene expression with DNA microarrays in skin biopsies from distinct scleroderma subsets including 17 patients with systemic sclerosis (SSc) with diffuse scleroderma (dSSc), 7 patients with SSc with limited scleroderma (lSSc), 3 patients with morphea, and 6 healthy controls. 61 skin biopsies were analyzed in a total of 75 microarray hybridizations. Analysis by hierarchical clustering demonstrates nearly identical patterns of gene expression in 17 out of 22 of the forearm and back skin pairs of SSc patients. Using this property of the gene expression, we selected a set of ‘intrinsic’ genes and analyzed the inherent data-driven groupings. Distinct patterns of gene expression separate patients with dSSc from those with lSSc and both are easily distinguished from normal controls. Our data show three distinct patient groups among the patients with dSSc and two groups among patients with lSSc. Each group can be distinguished by unique gene expression signatures indicative of proliferating cells, immune infiltrates and a fibrotic program. The intrinsic groups are statistically significant (p<0.001) and each has been mapped to clinical covariates of modified Rodnan skin score, interstitial lung disease, gastrointestinal involvement, digital ulcers, Raynaud''s phenomenon and disease duration. We report a 177-gene signature that is associated with severity of skin disease in dSSc.

Conclusions and Significance

Genome-wide gene expression profiling of skin biopsies demonstrates that the heterogeneity in scleroderma can be measured quantitatively with DNA microarrays. The diversity in gene expression demonstrates multiple distinct gene expression programs in the skin of patients with scleroderma.     

Evidence for chronic, peripheral activation of neutrophils in polyarticular juvenile rheumatoid arthritis

Although strong epidemiologic evidence suggests an important role for adaptive immunity in the pathogenesis of polyarticular juvenile rheumatoid arthritis (JRA), there remain many aspects of the disease that suggest equally important contributions of the innate immune system. We used gene expression arrays and computer modeling to examine the function in neutrophils of 25 children with polyarticular JRA. Computer analysis identified 712 genes that were differentially expressed between patients and healthy controls. Computer-assisted analysis of the differentially expressed genes demonstrated functional connections linked to both interleukin (IL)-8- and interferon-gamma (IFN-gamma)-regulated processes. Of special note is that the gene expression fingerprint of children with active JRA remained essentially unchanged even after they had responded to therapy. This result differed markedly from our previously reported work, in which gene expression profiles in buffy coats of children with polyarticular JRA reverted to normal after disease control was achieved pharmacologically. These findings suggest that JRA neutrophils remain in an activated state even during disease quiescence. Computer modeling of array data further demonstrated disruption of gene regulatory networks in clusters of genes modulated by IFN-gamma and IL-8. These cytokines have previously been shown to independently regulate the frequency (IFN-gamma) and amplitude (IL-8) of the oscillations of key metabolites in neutrophils, including nicotinamide adenine dinucleotide (phosphate) (NAD(P)H) and superoxide ion. Using real-time, high-speed, single-cell photoimaging, we observed that 6/6 JRA patients displayed a characteristic defect in 12% to 23% of the neutrophils tested. Reagents known to induce only frequency fluctuations of NAD(P)H and superoxide ion induced both frequency and amplitude fluctuations in JRA neutrophils. This is a novel finding that was observed in children with both active (n = 4) and inactive (n = 2) JRA. A subpopulation of polyarticular JRA neutrophils are in a chronic, activated state, a state that persists when the disease is well controlled pharmacologically. Furthermore, polyarticular JRA neutrophils exhibit an intrinsic defect in the regulation of metabolic oscillations and superoxide ion production. Our data are consistent with the hypothesis that neutrophils play an essential role in the pathogenesis of polyarticular JRA.     

Identification and quantification of disease-related gene clusters

MOTIVATION: DNA microarray technology and the completion of human and mouse genome sequencing programs are now offering new avenues for the investigation of complex genetic diseases. In particular, this makes possible the study of the spatial distribution of disease-related genes within the genome. We report on the first systematic search for clustering of genes associated with a polygenic autoimmune disease. RESULTS: Using a set of cDNA microarray chip experiments in two mouse models of rheumatoid arthritis, we have identified approximately 200 genes based on their expression in inflamed joints and mapped them into the genome. We compute the spatial autocorrelation function of the selected genes and find that they tend to cluster over scales of a few megabase pairs. We then identify significant gene clusters using a friends-of-friends algorithm. This approach should aid in discovering functionally related gene clusters in the mammalian genome.     

Gene expression profiling in autoimmune noninfectious uveitis disease

Noninfectious uveitis is a predominantly T cell-mediated autoimmune, intraocular inflammatory disease. To characterize the gene expression profile from patients with noninfectious uveitis, PBMCs were isolated from 50 patients with clinically characterized noninfectious uveitis syndrome. A pathway-specific cDNA microarray was used for gene expression profiling and real-time PCR array for further confirmation. Sixty-seven inflammation- and autoimmune-associated genes were found differentially expressed in uveitis patients, with 28 of those genes being validated by real-time PCR. Several genes previously unknown for autoimmune uveitis, including IL-22, IL-19, IL-20, and IL-25/IL-17E, were found to be highly expressed among uveitis patients compared with the normal subjects with IL-22 expression highly variable among the patients. Furthermore, we show that IL-22 can affect primary human retinal pigment epithelial cells by decreasing total tissue resistance and inducing apoptosis possibly by decreasing phospho-Bad level. In addition, the microarray data identified a possible uveitis-associated gene expression pattern, showed distinct gene expression profiles in patients during periods of clinical activity and quiescence, and demonstrated similar expression patterns in related patients with similar clinical phenotypes. Our data provide the first evidence that a subset of IL-10 family genes are implicated in noninfectious uveitis and that IL-22 can affect human retinal pigment epithelial cells. The results may facilitate further understanding of the molecular mechanisms of autoimmune uveitis and other autoimmune originated inflammatory diseases.     

Insight into Genotype-Phenotype Associations through eQTL Mapping in Multiple Cell Types in Health and Immune-Mediated Disease

Genome-wide association studies (GWAS) have transformed our understanding of the genetics of complex traits such as autoimmune diseases, but how risk variants contribute to pathogenesis remains largely unknown. Identifying genetic variants that affect gene expression (expression quantitative trait loci, or eQTLs) is crucial to addressing this. eQTLs vary between tissues and following in vitro cellular activation, but have not been examined in the context of human inflammatory diseases. We performed eQTL mapping in five primary immune cell types from patients with active inflammatory bowel disease (n = 91), anti-neutrophil cytoplasmic antibody-associated vasculitis (n = 46) and healthy controls (n = 43), revealing eQTLs present only in the context of active inflammatory disease. Moreover, we show that following treatment a proportion of these eQTLs disappear. Through joint analysis of expression data from multiple cell types, we reveal that previous estimates of eQTL immune cell-type specificity are likely to have been exaggerated. Finally, by analysing gene expression data from multiple cell types, we find eQTLs not previously identified by database mining at 34 inflammatory bowel disease-associated loci. In summary, this parallel eQTL analysis in multiple leucocyte subsets from patients with active disease provides new insights into the genetic basis of immune-mediated diseases.     

C1q-containing immune complexes purified from sera of juvenile rheumatoid arthritis patients mediate IL-8 production by human synoviocytes: role of C1q receptors.

Immune complexes that vary in size and composition are present in the sera and synovial fluid of juvenile rheumatoid arthritis (JRA) patients. They are believed to be potent inducers of the ongoing inflammatory process in JRA. However, the precise composition and role of these complexes in the pathophysiology of JRA remain unclear. We hypothesized that circulating ICs have the potential to interact with resident joint synovial fibroblasts (synoviocytes) and induce the expression of inflammatory cytokines. To test this hypothesis, cultures of synoviocytes from healthy individuals were treated with ICs isolated from the sera of JRA patients. Studies reported in this work demonstrate that IgM affinity-purified ICs from the sera of JRA patients contain IgM, C1q, IgG, and C3 to a variable extent. These ICs induce IL-8 mRNA and protein production in normal synoviocytes. Our data indicate that C1q in these ICs mediates, in part, IL-8 induction in synoviocytes. This is based on our findings of C1q-binding proteins for collagen stalks (cC1qR) and globular heads (gC1q-binding protein) of C1q in synoviocytes. In addition, collagen stalk and to some extent globular head fragments of C1q inhibit IC-mediated IL-8 induction in synoviocytes. Together, these findings provide evidence for a novel mechanism of IL-8 production by synoviocytes, which could play a key role in inflammation by recruiting leukocytes to synovial tissue and fluid-and subsequently contributing to joint disease.     

Gene expression profiling of coronary artery disease and its relation with different severities

Global gene expression profiling is a powerful tool enabling the understanding of pathophysiology and subsequent management of diseases. This study aims to explore functionally annotated differentially expressed genes (DEGs); their biological processes for coronary artery disease (CAD) and its different severities of atherosclerotic lesions. This study also aims to identify the change in expression patterns of DEGs in atherosclerotic lesions of single-vessel disease (SVD) and triple-vessel disease (TVD). The weight of different severities of lesion was estimated using a modified Gensini score. The gene expression profiling was performed using the Affymetrix microarray platform. The functional annotation for CAD was performed using DAVID v6.8. The biological network gene ontology tool (BiNGO) and ClueGO were used to explore the biological processes of functionally annotated genes of CAD. The changes in gene expression from SVD to TVD were determined by evaluating the fold change. Functionally annotated genes were found in an unique set and could be distinguishing two distinct severities of CAD. The biological processes such as cellular migration, locomotion, cell adhesion, cytokine production, positive regulation of cell death etc. enriched the functionally annotated genes in SVD, whereas, wound healing, negative regulation of cell death, blood coagulation, angiogenesis and fibrinolysis were enriched significantly in TVD patients. The genes THBS1 and CAPN10 were functionally annotated for CAD in both SVD and TVD. The 61 DEGs were identified, those have changes their expression with different severities of atherosclerotic lesions, in which 13 genes had more than two-fold change in expression between SVD and TVD. The consistent findings were obtained on validation of microarray gene expression of selected 10 genes in a separate cohort using real-time PCR. This study identified putative candidate genes and their biological processes predisposing toward and affecting the severity of CAD.     

DNA methylation and expression profiles of the brain-derived neurotrophic factor (BDNF) and dopamine transporter (DAT1) genes in patients with schizophrenia

Methylation and expression profile of CpG islands were examined in the promoters of the brain-derived neurotrophic factor (BDNF) and dopamine transporter (DAT1) genes. These are well known to be involved in the pathophysiology of psychiatric disorders such as schizophrenia. Genomic DNA was extracted from peripheral blood of 80 patients with schizophrenia and 71 healthy controls. Methylation pattern was studied by Methylation-Specific PCR. RNA expression analysis was done on extracted RNA from blood samples from patients suffering from schizophrenia (n?=?17) and healthy controls (n?=?17). Frequency of the BDNF gene methylation was highlighted as a statistically significant relationship between cases and controls regarding decreased risk of disease in comparison to unmethylated patterns (OR?=?0.24; 95?% CI?=?1.11–0.50; P?=?0.00007). For the DAT1 gene, this relationship was insignificant in 61 cases (76.25?%) and 52 controls (73.23?%) (OR?=?1.17; 95?% CI?=?0.53–2.61). Estimates of relative gene expression revealed a statistically significant association of the BDNF gene between schizophrenic patients and healthy controls (Mean?±?SD: 13.3920?±?15.19 and 0.437?±?0.328, P?=?0.0001) respectively; however, it was not significant for the DAT1 gene. This first hand evidence, regarding BDNF and DAT1 gene methylation and their expression profile with risk of schizophrenia, indicated a significant function for the BDNF gene in the development of schizophrenia. However, further populations with large sample sizes need to be studied to verify the exact role of BDNF in mental disorders such as schizophrenia.     

Systems-Based Analyses of Brain Regions Functionally Impacted in Parkinson's Disease Reveals Underlying Causal Mechanisms

Detailed analysis of disease-affected tissue provides insight into molecular mechanisms contributing to pathogenesis. Substantia nigra, striatum, and cortex are functionally connected with increasing degrees of alpha-synuclein pathology in Parkinson''s disease. We undertook functional and causal pathway analysis of gene expression and proteomic alterations in these three regions, and the data revealed pathways that correlated with disease progression. In addition, microarray and RNAseq experiments revealed previously unidentified causal changes related to oligodendrocyte function and synaptic vesicle release, and these and other changes were reflected across all brain regions. Importantly, subsets of these changes were replicated in Parkinson''s disease blood; suggesting peripheral tissue may provide important avenues for understanding and measuring disease status and progression. Proteomic assessment revealed alterations in mitochondria and vesicular transport proteins that preceded gene expression changes indicating defects in translation and/or protein turnover. Our combined approach of proteomics, RNAseq and microarray analyses provides a comprehensive view of the molecular changes that accompany functional loss and alpha-synuclein pathology in Parkinson''s disease, and may be instrumental to understand, diagnose and follow Parkinson''s disease progression.     

Identifying functional relationships within sets of co-expressed genes by combining upstream regulatory motif analysis and gene expression information

Background

Existing clustering approaches for microarray data do not adequately differentiate between subsets of co-expressed genes. We devised a novel approach that integrates expression and sequence data in order to generate functionally coherent and biologically meaningful subclusters of genes. Specifically, the approach clusters co-expressed genes on the basis of similar content and distributions of predicted statistically significant sequence motifs in their upstream regions.

Results

We applied our method to several sets of co-expressed genes and were able to define subsets with enrichment in particular biological processes and specific upstream regulatory motifs.

Conclusions

These results show the potential of our technique for functional prediction and regulatory motif identification from microarray data.

     

Phenotypic and functional distinctions between the TH2+ and JRA+ T cell subsets in man.

Prior work has demonstrated the existence of distinct human peripheral blood T cell subsets by utilizing heterologous as well as autoimmune antisera. In the present study, the relationship between the TH2+ and JRA+ T cell subsets was examined. T cells were purified with Sephadex G-200 anti-F(ab)2' affinity chromatography and E-rosetting technique, and subsequently fractionated into TH2+ and TH2- subsets by utilizing indirect immunofluorescence on FACS. Approximately 40 to 45% of the TH2- subset was shown to be JRA+, whereas less than 5% of the TH2+ subset was JRA+. In reciprocal studies, T cells were fractionated into JRA+ and JRA- subsets and reacted with heterologous antisera with anti-TH2+ specificity and indirect immunofluorescence. FACS analysis demonstrated that the JRA+ population contained no TH2+ T cells. In contrast, the JRA- population contained TH2+ T cells and accounted for the entire TH2+ subset found in the unfractionated T cell population. Functional studies showed that the TH2+ subset, and not the JRA+ subset, contain the effector population for cell-mediated lympholysis. It is concluded that the TH2+ and JRA+ T cell subsets define distinct and different T cell populations in man.     

Integrated analysis of gene expression and copy number data on gene shaving using independent component analysis

DNA microarray gene expression and microarray-based comparative genomic hybridization (aCGH) have been widely used for biomedical discovery. Because of the large number of genes and the complex nature of biological networks, various analysis methods have been proposed. One such method is "gene shaving," a procedure which identifies subsets of the genes with coherent expression patterns and large variation across samples. Since combining genomic information from multiple sources can improve classification and prediction of diseases, in this paper we proposed a new method, "ICA gene shaving" (ICA, independent component analysis), for jointly analyzing gene expression and copy number data. First we used ICA to analyze joint measurements, gene expression and copy number, of a biological system and project the data onto statistically independent biological processes. Next, we used these results to identify patterns of variation in the data and then applied an iterative shaving method. We investigated the properties of our proposed method by analyzing both simulated and real data. We demonstrated that the robustness of our method to noise using simulated data. Using breast cancer data, we showed that our method is superior to the Generalized Singular Value Decomposition (GSVD) gene shaving method for identifying genes associated with breast cancer.     

Multivariate exploratory tools for microarray data analysis

The ultimate success of microarray technology in basic and applied biological sciences depends critically on the development of statistical methods for gene expression data analysis. The most widely used tests for differential expression of genes are essentially univariate. Such tests disregard the multidimensional structure of microarray data. Multivariate methods are needed to utilize the information hidden in gene interactions and hence to provide more powerful and biologically meaningful methods for finding subsets of differentially expressed genes. The objective of this paper is to develop methods of multidimensional search for biologically significant genes, considering expression signals as mutually dependent random variables. To attain these ends, we consider the utility of a pertinent distance between random vectors and its empirical counterpart constructed from gene expression data. The distance furnishes exploratory procedures aimed at finding a target subset of differentially expressed genes. To determine the size of the target subset, we resort to successive elimination of smaller subsets resulting from each step of a random search algorithm based on maximization of the proposed distance. Different stopping rules associated with this procedure are evaluated. The usefulness of the proposed approach is illustrated with an application to the analysis of two sets of gene expression data.     

Genotypic analysis of the TGF beta-509 allele in patients with systemic lupus erythematosus and Sjogren's syndrome

Transforming growth factor beta (TGFbeta) is a secreted protein present in the circulation and is a critical regulator of the body's immune system. TGFbeta is believed to control several components of the immune system and inhibit autoimmune reactions. Systemic lupus erythematosus (SLE) and Sjogren's syndrome (SS) are prototypical human autoimmune diseases characterized by the circulating autoantibodies directed against nuclear antigens and immune complex deposition in various tissues leading to target organ inflammation and damage. Although the etiology of SLE is unknown, it has been observed that patients with SLE have lower levels of circulating TGFbeta than healthy individuals. In addition, mice lacking the TGFbeta1 gene develop a severe autoimmune disease that has features of both SS and SLE. Polymorphisms in the TGFbeta1 gene may alter the mRNA expression levels and influence the plasma protein concentration. Of the known TGFbeta 1 polymorphisms, only the C-509T polymorphism in the promoter region has been shown to be significantly associated with the plasma concentrations of TGFbeta 1. In this study, we have conducted a blinded study to determine if the -509 TGFbeta1 gene polymorphism is associated with SS or SLE. Genomic PCR and RFLP analysis of a 441 bp sequence encompassing the -509 polymorphism of the TGFbeta gene indicated that there were no statistically significant clinical correlations.