Genome-scale Assessment of Molecular Pathology in Systemic Autoimmune Diseases using Microarray Technology: A Potential Breakthrough Diagnostic and Individualized Therapy-design Tool

[Upcoming value of gene expression analysis in rheumatology]

Rheumatoid arthritis (RA) is a chronic inflammatory disease of unknown etiology, which involves disturbance in immune system signaling pathway functions, damage of other tissues, pain and joint destruction. Modern treatment attempts to improve pathophysiological and biochemical mechanisms damaged by the disease. However, due to the RA patient heterogeneity personalized approach to treatment is required; the choice of personalized treatment is complicated by the variability of patient's response to treatment. Gene expression analysis might serve a tool for the disease control and therapy personification for inhibition of inflammation and pain as well as for prevention of joint destruction.

A PCR based magnetic assembled sensor for ultrasensitive DNA detection

An ultrasensitive method for DNA detection based on magnetic assembly induced by polymerase chain reaction (PCR) was developed. The sensor showed a low limit of detection (LOD) of 4.26 aM with a wide range of target DNA from 0.01 fM to 10,000 fM.

Meta-analysis of differentially expressed genes in primary Sjogren's syndrome by using microarray

INTRODUCTION

The purpose of this study was to identify differentially expressed (DE) genes and biological processes associated with changes in gene expression in primary Sjogren's syndrome (pSS).

METHODS

We performed a meta-analysis using the INMEX program (integrative meta-analysis of expression data) of publicly available microarray GEO datasets of pSS. We performed Gene Ontology (GO) enrichment analyses and pathway analysis using Kyoto Encyclopedia of Genes and Genomes (KEGG).

RESULTS

Three GEO datasets including 37 cases and 33 controls were available for the meta-analysis. We identified 179 genes across the studies which were consistently DE in pSS (146 up-regulated and 33 down-regulated). The up-regulated gene with the largest effect size (ES) (ES = -2.4228) was SELL (selectin L), whose product is required for the binding and subsequent rolling of leucocytes on endothelial cells to facilitate their migration into secondary lymphoid organs and inflammation sites. The most significant enrichment was in the immune response GO category (P = 2.52 × 10(-25)). The most significant pathway in our KEGG analysis was Epstein-Barr virus infection (P = 9.91 × 10(-06)).

CONCLUSIONS

Our meta-analysis demonstrated genes that were consistently DE and biological pathways associated with gene expression changes with pSS.

Common and specific signatures of gene expression and protein-protein interactions in autoimmune diseases

The aim of this study is to understand intracellular regulatory mechanisms in peripheral blood mononuclear cells (PBMCs), which are either common to many autoimmune diseases or specific to some of them. We incorporated large-scale data such as protein-protein interactions, gene expression and demographical information of hundreds of patients and healthy subjects, related to six autoimmune diseases with available large-scale gene expression measurements: multiple sclerosis (MS), systemic lupus erythematosus (SLE), juvenile rheumatoid arthritis (JRA), Crohn's disease (CD), ulcerative colitis (UC) and type 1 diabetes (T1D). These data were analyzed concurrently by statistical and systems biology approaches tailored for this purpose. We found that chemokines such as CXCL1-3, 5, 6 and the interleukin (IL) IL8 tend to be differentially expressed in PBMCs of patients with the analyzed autoimmune diseases. In addition, the anti-apoptotic gene BCL3, interferon-γ (IFNG), and the vitamin D receptor (VDR) gene physically interact with significantly many genes that tend to be differentially expressed in PBMCs of patients with the analyzed autoimmune diseases. In general, similar cellular processes tend to be differentially expressed in PBMC in the analyzed autoimmune diseases. Specifically, the cellular processes related to cell proliferation (for example, epidermal growth factor, platelet-derived growth factor, nuclear factor-κB, Wnt/β-catenin signaling, stress-activated protein kinase c-Jun NH2-terminal kinase), inflammatory response (for example, interleukins IL2 and IL6, the cytokine granulocyte-macrophage colony-stimulating factor and the B-cell receptor), general signaling cascades (for example, mitogen-activated protein kinase, extracellular signal-regulated kinase, p38 and TRK) and apoptosis are activated in most of the analyzed autoimmune diseases. However, our results suggest that in each of the analyzed diseases, apoptosis and chemotaxis are activated via different subsignaling pathways. Analyses of the expression levels of dozens of genes and the protein-protein interactions among them demonstrated that CD and UC have relatively similar gene expression signatures, whereas the gene expression signatures of T1D and JRA relatively differ from the signatures of the other autoimmune diseases. These diseases are the only ones activated via the Fcɛ pathway. The relevant genes and pathways reported in this study are discussed at length, and may be helpful in the diagnoses and understanding of autoimmunity and/or specific autoimmune diseases.

A network-based analysis of traditional Chinese medicine cold and hot patterns in rheumatoid arthritis

OBJECTIVE

Rheumatoid arthritis (RA) is a heterogeneous disease, and traditional Chinese medicine (TCM) can be used to classify RA into different patterns such as cold and hot based on its clinical manifestations. The aim of this study was to investigate potential network-based biomarkers for RA with either a cold or a hot pattern.

METHOD

Microarray technology was used to reveal gene expression profiles in CD4(+) T cells from 21 RA patients with cold pattern and 12 with hot pattern. A T-test was used to identify significant differences in gene expression among RA patients with either cold or hot pattern. Cytoscape software was used to search the existing literature and databases for protein-protein interaction information for genes of interest that were identified from this analysis. The IPCA algorithm was used to detect highly connected regions for inferring significant complexes or pathways in this protein-protein interaction network. Significant pathways and functions were extracted from these subnetworks by the Biological Network Gene Ontology tool.

RESULT

Four genes were expressed at higher levels in RA patients with cold pattern than in patients with hot pattern, and 21 genes had lower levels of expression. Protein-protein interaction network analysis for these genes showed that there were four highly connected regions. The most relevant functions and pathways extracted from these subnetwork regions were involved in small G protein signaling pathways, oxidation-reduction in fatty acid metabolism and T cell proliferation.

CONCLUSION

Complicated network based pathways appear to play a role in the different pattern manifestations in patients with RA, and our results suggest that network-based pathways might be the scientific basis for TCM pattern classification.

Correlation between cold and hot pattern in traditional Chinese medicine and gene expression profiles in rheumatoid arthritis

Clinical manifestations of rheumatoid arthritis (RA) are diversified, and based on the manifestations, the patients with RA could be classified into different patterns under traditional Chinese medicine. These patterns decide the selection of herbal prescription, and thus they can help find a subset of rheumatoid arthritis patients for a type of therapy. In the present study, we combine genome-wide expression analysis with methods of systems biology to identify the functional gene networks for the sets of clinical symptoms that comprise the major information for pattern classification. Clinical manifestations in rheumatoid arthritis were clustered with factor analysis, and two factors (similar to cold and hot patterns in traditional Chinese medicine) were found. Microarray technology was used to reveal gene expression profiles in CD4(+) T cells from 21 rheumatoid arthritis patients. Protein-protein interaction information for these genes from databases and literature data was searched. The highly-connected regions were detected to infer significant complexes or pathways in this protein-protein interaction network. The significant pathways and function were extracted from these subnetworks using the Biological Network Gene Ontology tool. The genes significantly related to hot and cold patterns were identified by correlations analysis. MAPK signalling pathway, Wnt signaling pathway, and insulin signaling pathway were found to be related to hot pattern. Purine metabolism was related to both hot and cold patterns. Alanine, aspartate, and tyrosine metabolism were related to cold pattern, and histindine metabolism and lysine degradation were related to hot pattern. The results suggest that cold and hot patterns in traditional Chinese medicine were related to different pathways, and the network analysis might be used for identifying the pattern classification in other diseases.

Gene expression profiles of systemic lupus erythematosus and rheumatoid arthritis

Gene expression profiling using microarray technology is being employed to define specific molecular mediators and pathways involved in immunobiology, to understand the intricate interplay of genes participating in the pathogenesis, and to develop biomarkers of disease activity in both systemic lupus erythematosus (SLE) and rheumatoid arthritis (RA). This review summarizes the latest information on the pathogenesis of SLE and RA and describes the utilization of microarray technology in these systemic autoimmune diseases.

Cytokines and cytokine profiles in human autoimmune diseases and animal models of autoimmunity

The precise pathomechanisms of human autoimmune diseases are still poorly understood. However, a deepened understanding of these is urgently needed to improve disease prevention and early detection and guide more specific treatment approaches. In recent years, many new genes and signalling pathways involved in autoimmunity with often overlapping patterns between different disease entities have been detected. Major contributions were made by experiments using DNA microarray technology, which has been used for the analysis of gene expression patterns in chronic inflammatory and autoimmune diseases, among which were rheumatoid arthritis, systemic lupus erythematosus, psoriasis, systemic sclerosis, multiple sclerosis, and type-1 diabetes. In systemic lupus erythematosus, a so-called interferon signature has been identified. In psoriasis, researchers found a particular immune signalling cluster. Moreover the identification of a new subset of inflammatory T cells, so-called Th17 T cells, secreting interleukin (IL)-17 as one of their major cytokines and the identification of the IL-23/IL-17 axis of inflammation regulation, have significantly improved our understanding of autoimmune diseases. Since a plethora of new treatment approaches using antibodies or small molecule inhibitors specifically targeting cytokines, cellular receptors, or signalling mechanisms has emerged in recent years, more individualized treatment for affected patients may be within reach in the future.

Recent development of nano-materials used in DNA biosensors

As knowledge of the structure and function of nucleic acid molecules has increased, sequence-specific DNA detection has gained increased importance. DNA biosensors based on nucleic acid hybridization have been actively developed because of their specificity, speed, portability, and low cost. Recently, there has been considerable interest in using nano-materials for DNA biosensors. Because of their high surface-to-volume ratios and excellent biological compatibilities, nano-materials could be used to increase the amount of DNA immobilization; moreover, DNA bound to nano-materials can maintain its biological activity. Alternatively, signal amplification by labeling a targeted analyte with nano-materials has also been reported for DNA biosensors in many papers. This review summarizes the applications of various nano-materials for DNA biosensors during past five years. We found that nano-materials of small sizes were advantageous as substrates for DNA attachment or as labels for signal amplification; and use of two or more types of nano-materials in the biosensors could improve their overall quality and to overcome the deficiencies of the individual nano-components. Most current DNA biosensors require the use of polymerase chain reaction (PCR) in their protocols. However, further development of nano-materials with smaller size and/or with improved biological and chemical properties would substantially enhance the accuracy, selectivity and sensitivity of DNA biosensors. Thus, DNA biosensors without PCR amplification may become a reality in the foreseeable future.

Periodontitis associates with a type 1 IFN signature in peripheral blood neutrophils

Peripheral blood neutrophils from periodontitis patients exhibit a hyperreactive and hyperactive phenotype (collectively termed hyperresponsivity) in terms of production of reactive oxygen species (ROS). The molecular basis for this phenomenon, however, has yet to be determined. Our objectives were to identify genes differentially expressed in hyperresponsive peripheral blood neutrophils from chronic periodontitis patients relative to periodontally healthy controls and use these data to identify potential contributory pathways to the hyperresponsive neutrophil phenotype. Using microarray technology we demonstrated differential expression of 163 genes (149 increased, 14 decreased) representing a range of ontological classes. There was increased expression of a significant number of IFN-stimulated genes (ISG). RT-PCR analysis of ISG transcripts in individual and pooled samples further corroborated these data, and indicated that levels decreased to near those of controls following successful therapy. Significantly enhanced FcgammaR-stimulated ROS production was subsequently achieved by priming control neutrophils with IFN-alpha/-beta/-gamma, but not LPS, and gene expression analysis indicated that exposure to the type I IFN (in particular IFN-alpha) better replicated the mRNA profile observed in vivo. Further studies demonstrated that plasma levels of IFN-alpha were significantly higher in samples from patients relative to unaffected controls. Following successful periodontitis treatment, plasma IFN-alpha levels, neutrophil ISG expression, and FcgammaR-stimulated neutrophil ROS output of patients, all decreased to levels comparable with those of controls. In conclusion, although chronic periodontitis is a complex disease, raised IFN-alpha may be one determinant of the distinct molecular phenotype and hyperresponsivity exhibited by patients' peripheral blood neutrophils.

Genomics and proteomics: a new approach for assessing thrombotic risk in autoimmune diseases

Several systemic autoimmune conditions, including rheumatoid arthritis, systemic lupus erythematosus and antiphospholipid syndrome, are characterised by enhanced atherosclerosis and, consequently, higher cardiovascular morbidity and mortality rates. The association of these diseases with atherosclerosis suggests a common pathogenic mechanism. Genomic and proteomic studies performed on atherosclerotic plaques have further confirmed the presence of a gene and protein profile similar to that observed in autoimmune diseases with cardiovascular risks. Human sera and body fluids have been analysed and have resulted in the identification of auto-antibodies that can be used as diagnostic markers in specific autoimmune diseases, and proteomic fingerprints of blood cells, tissues and body fluids have resulted in the identification of individual proteins or patterns of protein expression that are deregulated. The information provided by these proteomic studies is of diagnostic and therapeutic potential. In this review, we discuss new approaches available for assessing thrombotic risk in autoimmune diseases, focusing in the genomic and proteomic methods now available to deep into the origin of the mechanisms associated with vascular involvement in systemic autoimmune diseases. The increasing data available suggests that when treating patients with these autoimmune disorders, paying attention to the increased risk of cardiovascular disease is essential.

Molecular genetic studies of gene identification for osteoporosis

This review comprehensively summarizes the most important and representative molecular genetics studies of gene identification for osteoporosis published up to the end of September 2007. It is intended to constitute a sequential update of our previously published reviews covering the available data up to the end of 2004. Evidence from candidate gene-association studies, genome-wide linkage and association studies, as well as functional genomic studies (including gene-expression microarray and proteomics) on osteogenesis and osteoporosis, are reviewed separately. Studies of transgenic and knockout mice models relevant to osteoporosis are summarized. The major results of all studies are tabulated for comparison and ease of reference. Comments are made on the most notable findings and representative studies for their potential influence and implications on our present understanding of genetics of osteoporosis. The format adopted by this review should be ideal for accommodating future new advances and studies.

Profiling meta-analysis reveals primarily gene coexpression concordance between systemic lupus erythematosus and rheumatoid arthritis

Consensus gene expression profiling by meta-analysis of 4,500 cDNA sequence microarray data obtained from patients with systemic lupus erythematosus (SLE) and rheumatoid arthritis (RA) was assembled and systematically analyzed. The normalized data were statistically analyzed by the significance analysis of microarray (SAM) program (false discovery rate <or= 0.01). Patient data input was realized together, in the Cluster and Tree-View program, using the unsupervised function. Individual expression signatures permitted a hierarchical clustering of samples, separately identifying SLE and RA patients and the transcriptome profiling featured modules of the specifically induced or repressed and the comodulated genes. Gene expression profiling meta-analysis showed that patients with SLE or RA share gene modulation but also present genes whose expression patterns are exclusive (induced or repressed) in corroboration with their clinical features. Among the genes that were differentially expressed, we found those that could play specific roles in these two diseases. This approach permits a clearer understanding of the molecular basis of SLE and RA concordance/divergence.

Sjögren's syndrome--a plethora of clinical and immunological phenotypes with a complex genetic background

Primary Sjögren's syndrome is a complex autoimmune disorder, considered to represent an ideal disease with which to study the mechanisms underlying autoimmunity because its manifestations are both organ specific and systemic in nature. The characteristic histologic finding in target organs is a progressive focal infiltration of mononuclear lymphoid cells, replacing glandular epithelium (lymphoepithelial lesion). This involvement has been re-emphasized in the 2002 revised EU criteria for Sjögren's syndrome. Moreover, ectopic secondary lymphoid follicles in Sjögren's syndrome contain all elements of relevance for driving an autoimmune response. A number of cytokines and chemokines are involved and particularly B cell activating factor seems to direct the lifespan of infiltrating B cells by enhancing their proliferation and maturation. The recent discovery of clinical benefit after B cell depletion also highlights the pivotal role of B cells in Sjögren's syndrome. A major challenge in Sjögren's syndrome will be to stratify the disease process including genetic and environmental triggers. Identification of novel genetic and molecular markers may lead to the development of better diagnostic and prognostic tools in Sjögren's syndrome including its systemic complications. This minor review will cover the current knowledge on classification, pathogenesis, multiplex findings, potential candidate genes, gene profiling results, and novel therapy approaches. New hypotheses behind the complexity of Sjögren's syndrome are expected to follow.

Autoimmune Diseases and Sjogren's Syndrome: An Autoimmune Exocrinopathy

Autoimmune diseases include a diverse group of over 80 conditions. Sjögren's syndrome is the second most common autoimmune rheumatic disease, with an estimated prevalence in the United States of 2-4 million persons. There are prominent and consistent oral and dental findings in Sjögren's syndrome related to the autoimmune-mediated loss of normal salivary function. Additionally, nonoral clinical manifestations of Sjögren's syndrome include: dry eyes (with specific ocular surface changes termed keratoconjunctivitis sicca); other xeroses, such as dryness of the nose, throat, skin, and vagina; peripheral (and less frequently central) neuropathies; myalgias and arthralgias; thyroid disorders (particularly autoimmune thyroiditis); pulmonary disorders; renal disorders; and lymphoma. There is a significant (20- to 40-fold) increase in the incidence of malignant lymphoma, particularly in primary Sjögren's syndrome. Establishing the diagnosis of Sjögren's syndrome has been difficult in the light of its nonspecific symptoms (dry eyes and mouth), disagreement on diagnostic criteria, and a lack of both sensitive and specific laboratory markers. Many serum and salivary biomarkers for Sjögren's syndrome have been proposed although, to date, none has proven to be sufficiently specific for diagnostic purposes or has been well correlated with disease activity measures. Investigators have recently begun to apply modern genomic and proteomic approaches to identify candidate biomarkers in Sjögren's syndrome. The results of these investigations promise to provide a wealth of information on candidate biomarkers and possible etiopathological mechanisms underlying this disorder. Further, this information will improve clinical outcomes by fostering the design of new rational therapeutics and assisting in the monitoring of clinical disease.