Inflammatory macrophage memory in nonsteroidal anti-inflammatory drug-exacerbated respiratory disease.

BACKGROUND: Nonsteroidal anti-inflammatory drug-exacerbated respiratory disease (N-ERD) is a chronic inflammatory condition, which is driven by an aberrant arachidonic acid metabolism. Macrophages are major producers of arachidonic acid metabolites and subject to metabolic reprogramming, but they have been neglected in N-ERD. OBJECTIVE: This study sought to elucidate a potential metabolic and epigenetic macrophage reprogramming in N-ERD. METHODS: Transcriptional, metabolic, and lipid mediator profiles in macrophages from patients with N-ERD and healthy controls were assessed by RNA sequencing, Seahorse assays, and LC-MS/MS. Metabolites in nasal lining fluid, sputum, and plasma from patients with N-ERD (n = 15) and healthy individuals (n = 10) were quantified by targeted metabolomics analyses. Genome-wide methylomics were deployed to define epigenetic mechanisms of macrophage reprogramming in N-ERD. RESULTS: This study shows that N-ERD monocytes/macrophages exhibit an overall reduction in DNA methylation, aberrant metabolic profiles, and an increased expression of chemokines, indicative of a persistent proinflammatory activation. Differentially methylated regions in N-ERD macrophages included genes involved in chemokine signaling and acylcarnitine metabolism. Acylcarnitines were increased in macrophages, sputum, nasal lining fluid, and plasma of patients with N-ERD. On inflammatory challenge, N-ERD macrophages produced increased levels of acylcarnitines, proinflammatory arachidonic acid metabolites, cytokines, and chemokines as compared to healthy macrophages. CONCLUSIONS: Together, these findings decipher a proinflammatory metabolic and epigenetic reprogramming of macrophages in N-ERD.

OntoCR: A CEN/ISO-13606 clinical repository based on ontologies.

OBJECTIVE: To design a new semantically interoperable clinical repository, based on ontologies, conforming to CEN/ISO 13606 standard. MATERIALS AND METHODS: The approach followed is to extend OntoCRF, a framework for the development of clinical repositories based on ontologies. The meta-model of OntoCRF has been extended by incorporating an OWL model integrating CEN/ISO 13606, ISO 21090 and SNOMED CT structure. RESULTS: This approach has demonstrated a complete evaluation cycle involving the creation of the meta-model in OWL format, the creation of a simple test application, and the communication of standardized extracts to another organization. DISCUSSION: Using a CEN/ISO 13606 based system, an indefinite number of archetypes can be merged (and reused) to build new applications. Our approach, based on the use of ontologies, maintains data storage independent of content specification. With this approach, relational technology can be used for storage, maintaining extensibility capabilities. CONCLUSIONS: The present work demonstrates that it is possible to build a native CEN/ISO 13606 repository for the storage of clinical data. We have demonstrated semantic interoperability of clinical information using CEN/ISO 13606 extracts.

Knowledge retrieval from PubMed abstracts and electronic medical records with the Multiple Sclerosis Ontology.

BACKGROUND: In order to retrieve useful information from scientific literature and electronic medical records (EMR) we developed an ontology specific for Multiple Sclerosis (MS). METHODS: The MS Ontology was created using scientific literature and expert review under the Protégé OWL environment. We developed a dictionary with semantic synonyms and translations to different languages for mining EMR. The MS Ontology was integrated with other ontologies and dictionaries (diseases/comorbidities, gene/protein, pathways, drug) into the text-mining tool SCAIView. We analyzed the EMRs from 624 patients with MS using the MS ontology dictionary in order to identify drug usage and comorbidities in MS. Testing competency questions and functional evaluation using F statistics further validated the usefulness of MS ontology. RESULTS: Validation of the lexicalized ontology by means of named entity recognition-based methods showed an adequate performance (F score = 0.73). The MS Ontology retrieved 80% of the genes associated with MS from scientific abstracts and identified additional pathways targeted by approved disease-modifying drugs (e.g. apoptosis pathways associated with mitoxantrone, rituximab and fingolimod). The analysis of the EMR from patients with MS identified current usage of disease modifying drugs and symptomatic therapy as well as comorbidities, which are in agreement with recent reports. CONCLUSION: The MS Ontology provides a semantic framework that is able to automatically extract information from both scientific literature and EMR from patients with MS, revealing new pathogenesis insights as well as new clinical information.

OWLing Clinical Data Repositories With the Ontology Web Language.

BACKGROUND: The health sciences are based upon information. Clinical information is usually stored and managed by physicians with precarious tools, such as spreadsheets. The biomedical domain is more complex than other domains that have adopted information and communication technologies as pervasive business tools. Moreover, medicine continuously changes its corpus of knowledge because of new discoveries and the rearrangements in the relationships among concepts. This scenario makes it especially difficult to offer good tools to answer the professional needs of researchers and constitutes a barrier that needs innovation to discover useful solutions. OBJECTIVE: The objective was to design and implement a framework for the development of clinical data repositories, capable of facing the continuous change in the biomedicine domain and minimizing the technical knowledge required from final users. METHODS: We combined knowledge management tools and methodologies with relational technology. We present an ontology-based approach that is flexible and efficient for dealing with complexity and change, integrated with a solid relational storage and a Web graphical user interface. RESULTS: Onto Clinical Research Forms (OntoCRF) is a framework for the definition, modeling, and instantiation of data repositories. It does not need any database design or programming. All required information to define a new project is explicitly stated in ontologies. Moreover, the user interface is built automatically on the fly as Web pages, whereas data are stored in a generic repository. This allows for immediate deployment and population of the database as well as instant online availability of any modification. CONCLUSIONS: OntoCRF is a complete framework to build data repositories with a solid relational storage. Driven by ontologies, OntoCRF is more flexible and efficient to deal with complexity and change than traditional systems and does not require very skilled technical people facilitating the engineering of clinical software systems.

Microarray and deep sequencing cross-platform analysis of the mirRNome and isomiR variation in response to epidermal growth factor.

BACKGROUND: Epidermal Growth Factor (EGF) plays an important function in the regulation of cell growth, proliferation, and differentiation by binding to its receptor (EGFR) and providing cancer cells with increased survival responsiveness. Signal transduction carried out by EGF has been extensively studied at both transcriptional and post-transcriptional levels. Little is known about the involvement of microRNAs (miRNAs) in the EGF signaling pathway. miRNAs have emerged as major players in the complex networks of gene regulation, and cancer miRNA expression studies have evidenced a direct involvement of miRNAs in cancer progression. RESULTS: In this study, we have used an integrative high content analysis approach to identify the specific miRNAs implicated in EGF signaling in HeLa cells as potential mediators of cancer mediated functions. We have used microarray and deep-sequencing technologies in order to obtain a global view of the EGF miRNA transcriptome with a robust experimental cross-validation. By applying a procedure based on Rankprod tests, we have delimited a solid set of EGF-regulated miRNAs. After validating regulated miRNAs by reverse transcription quantitative PCR, we have derived protein networks and biological functions from the predicted targets of the regulated miRNAs to gain insight into the potential role of miRNAs in EGF-treated cells. In addition, we have analyzed sequence heterogeneity due to editing relative to the reference sequence (isomiRs) among regulated miRNAs. CONCLUSIONS: We propose that the use of global genomic miRNA cross-validation derived from high throughput technologies can be used to generate more reliable datasets inferring more robust networks of co-regulated predicted miRNA target genes.

Multiple platform assessment of the EGF dependent transcriptome by microarray and deep tag sequencing analysis.

BACKGROUND: Epidermal Growth Factor (EGF) is a key regulatory growth factor activating many processes relevant to normal development and disease, affecting cell proliferation and survival. Here we use a combined approach to study the EGF dependent transcriptome of HeLa cells by using multiple long oligonucleotide based microarray platforms (from Agilent, Operon, and Illumina) in combination with digital gene expression profiling (DGE) with the Illumina Genome Analyzer. RESULTS: By applying a procedure for cross-platform data meta-analysis based on RankProd and GlobalAncova tests, we establish a well validated gene set with transcript levels altered after EGF treatment. We use this robust gene list to build higher order networks of gene interaction by interconnecting associated networks, supporting and extending the important role of the EGF signaling pathway in cancer. In addition, we find an entirely new set of genes previously unrelated to the currently accepted EGF associated cellular functions. CONCLUSIONS: We propose that the use of global genomic cross-validation derived from high content technologies (microarrays or deep sequencing) can be used to generate more reliable datasets. This approach should help to improve the confidence of downstream in silico functional inference analyses based on high content data.

Anti-peripherin B lymphocytes are positively selected during diabetogenesis.

Rearrangement analysis of immunoglobulin genes is an exceptional opportunity to look back at the B lymphocyte differentiation during ontogeny and the subsequent immune response, and thus to study the selective pressures involved in autoimmune disorders. In a recent study to characterize the antigenic specificity of B lymphocytes during T1D progression, we generated hybridomas of islet-infiltrating B lymphocytes from NOD mice and other related strains developing insulitis, but with different degrees of susceptibility to T1D. We found that a sizable proportion of hybridomas produced monoclonal antibodies reactive to peripherin, an intermediate filament protein mainly found in the peripheral nervous system. Moreover, we found that anti-peripherin antibody-producing hybridomas originated from B lymphocytes that had undergone immunoglobulin class switch recombination, a characteristic of secondary immune response. Therefore, in the present study we performed immunoglobulin VL and VH analysis of these hybridomas to ascertain whether they were derived from B lymphocytes that had undergone antigen-driven selection. The results indicated that whereas some anti-peripherin hybridomas showed signs of oligoclonality, somatic hypermutation and/or secondary rearrangements (receptor edition and receptor revision), others seemed to directly derive from the preimmune repertoire. In view of these results, we conclude that anti-peripherin B lymphocytes are positively selected and primed in the course of T1D development in NOD mice, and reinforce the idea that peripherin is a relevant autoantigen targeted during T1D development in this animal model.

Peripherin is a relevant neuroendocrine autoantigen recognized by islet-infiltrating B lymphocytes.

Most of our knowledge of the antigenic repertoire of autoreactive B lymphocytes in type 1 diabetes (T1D) comes from studies on the antigenic specificity of both circulating islet-reactive autoantibodies and peripheral B lymphocyte hybridomas generated from human blood or rodent spleen. In a recent study, we generated hybridoma cell lines of infiltrating B lymphocytes from different mouse strains developing insulitis, but with different degrees of susceptibility to T1D, to characterize the antigenic specificity of islet-infiltrating B lymphocytes during progression of the disease. We found that many hybridomas produced mAbs restricted to the peripheral nervous system (PNS), thus indicating an active B lymphocyte response against PNS elements in the pancreatic islet during disease development. The aim of this study was to identify the autoantigen recognized by these anti-PNS mAbs. Our results showed that peripherin is the autoantigen recognized by all anti-PNS mAbs, and, therefore, a relevant neuroendocrine autoantigen targeted by islet-infiltrating B lymphocytes. Moreover, we discovered that the immune dominant epitope of this B lymphocyte immune response is found at the C-terminal end of Per58 and Per61 isoforms. In conclusion, our study strongly suggests that peripherin is a major autoantigen targeted during T1D development and poses a new question on why peripherin-specific B lymphocytes are mainly attracted to the islet during disease.

Phenotype and functional characteristics of islet-infiltrating B-cells suggest the existence of immune regulatory mechanisms in islet milieu.

B-cells participate in the autoimmune response that precedes the onset of type 1 diabetes, but how these cells contribute to disease progression is unclear. In this study, we analyzed the phenotype and functional characteristics of islet-infiltrating B-cells in the diabetes-prone NOD mouse and in the insulitis-prone but diabetes-resistant (NOD x NOR)F1 mouse. The results indicate that B-cells accumulate in the islets of both mice influenced by sex traits. Phenotypically and functionally, these B-cells are highly affected by the islet inflammatory milieu, which may keep them in a silenced status. Moreover, although islet-infiltrating B-cells seem to be antigen experienced, they can only induce islet-infiltrating T-cell proliferation when they act as accessory cells. Thus, these results strongly suggest that islet-infiltrating B-cells do not activate islet-infiltrating T-cells in situ, although they may affect the progression of the disease otherwise.

Islet-infiltrating B-cells in nonobese diabetic mice predominantly target nervous system elements.

B-cells accumulate in pancreatic islets during the autoimmune response that precedes the onset of type 1 diabetes. However, the role and antigenic specificity of these cells remain a mystery. To elucidate the antigenic repertoire of islet-infiltrating B-cells in type 1 diabetes, we generated hybridoma cell lines of islet-infiltrating B-cells from nonobese diabetic (NOD) mice and NOD mice expressing a diabetogenic T-cell receptor (8.3-NOD). Surprisingly, characterization of the tissue specificity of the antibodies secreted by these cells revealed that a predominant fraction of these hybridomas produce antibodies specific for the pancreatic nervous system. Similar results were obtained with B-cell hybridomas derived from mild insulinic lesions of diabetes-resistant (NOD x NOR)F1 and 8.3-(NOD x NOR)F1 mice. Immunoglobulin class analyses further indicated that most islet-derived hybridomas had arisen from B-cells that had undergone immunoglobulin class switch recombination, suggesting that islet-associated B-cells are involved in active, T-helper-driven immune responses against local antigenic targets. This is the first evidence showing the existence of a predominant active B-cell response in situ against pancreatic nervous system elements in diabetogenesis. Our data are consistent with the idea that this B-cell response precedes the progression of insulitis to overt diabetes, thus strongly supporting the idea that pancreatic nervous system elements are early targets in type 1 diabetes.

IFN beta accelerates autoimmune type 1 diabetes in nonobese diabetic mice and breaks the tolerance to beta cells in nondiabetes-prone mice.

Genetic and environmental factors are decisive in the etiology of type 1 diabetes. Viruses have been proposed as a triggering environmental event and some evidences have been reported: type I IFNs exist in the pancreata of diabetic patients and transgenic mice expressing these cytokines in beta cells develop diabetes. To determine the role of IFNbeta in diabetes, we studied transgenic mice expressing human IFNbeta in the beta cells. Autoimmune features were found: MHC class I islet hyperexpression, T and B cells infiltrating the islets and transfer of the disease by lymphocytes. Moreover, the expression of beta(2)-microglobulin, preproinsulin, and glucagon in the thymus was not altered by IFNbeta, thus suggesting that the disease is caused by a local effect of IFNbeta, strong enough to break the peripheral tolerance to beta cells. This is the first report of the generation of NOD (a model of spontaneous autoimmune diabetes) and nonobese-resistant (its homologous resistant) transgenic mice expressing a type I IFN in the islets: transgenic NOD and nonobese-resistant mice developed accelerated autoimmune diabetes with a high incidence of the disease. These results indicate that the antiviral cytokine IFNbeta breaks peripheral tolerance to beta cells, influences the insulitis progression and contributes to autoimmunity in diabetes and nondiabetes- prone mice.