Involvement of human monogenic cardiomyopathy genes in experimental polygenic cardiac hypertrophy.

Hypertrophic cardiomyopathy thickens heart muscles, reducing functionality and increasing risk of cardiac disease and morbidity. Genetic factors are involved, but their contribution is poorly understood. We used the hypertrophic heart rat (HHR), a unique normotensive polygenic model of cardiac hypertrophy and heart failure, to investigate the role of genes associated with monogenic human cardiomyopathy. We selected 42 genes involved in monogenic human cardiomyopathies to study: 1) DNA variants, by sequencing the whole genome of 13-wk-old HHR and age-matched normal heart rat (NHR), its genetic control strain; 2) mRNA expression, by targeted RNA-sequencing in left ventricles of HHR and NHR at 5 ages (2 days old and 4, 13, 33, and 50 wk old) compared with human idiopathic dilated cardiomyopathy data; and 3) microRNA expression, with rat microRNA microarrays in left ventricles of 2-day-old HHR and age-matched NHR. We also investigated experimentally validated microRNA-mRNA interactions. Whole-genome sequencing revealed unique variants mostly located in noncoding regions of HHR and NHR. We found 29 genes differentially expressed in at least 1 age. Genes encoding desmoglein 2 ( Dsg2) and transthyretin ( Ttr) were significantly differentially expressed at all ages in the HHR, but only Ttr was also differentially expressed in human idiopathic cardiomyopathy. Lastly, only two microRNAs differentially expressed in the HHR were present in our comparison of validated microRNA-mRNA interactions. These two microRNAs interact with five of the genes studied. Our study shows that genes involved in monogenic forms of human cardiomyopathies may also influence polygenic forms of the disease.

Secondary Use and Analysis of Big Data Collected for Patient Care.

Objectives: To identify common methodological challenges and review relevant initiatives related to the re-use of patient data collected in routine clinical care, as well as to analyze the economic benefits derived from the secondary use of this data. Through the use of several examples, this article aims to provide a glimpse into the different areas of application, namely clinical research, genomic research, study of environmental factors, and population and health services research. This paper describes some of the informatics methods and Big Data resources developed in this context, such as electronic phenotyping, clinical research networks, biorepositories, screening data banks, and wide association studies. Lastly, some of the potential limitations of these approaches are discussed, focusing on confounding factors and data quality. Methods: A series of literature searches in main bibliographic databases have been conducted in order to assess the extent to which existing patient data has been repurposed for research. This contribution from the IMIA working group on "Data mining and Big Data analytics" focuses on the literature published during the last two years, covering the timeframe since the working group's last survey. Results and Conclusions: Although most of the examples of secondary use of patient data lie in the arena of clinical and health services research, we have started to witness other important applications, particularly in the area of genomic research and the study of health effects of environmental factors. Further research is needed to characterize the economic impact of secondary use across the broad spectrum of translational research.

How does temperature influences the development of lactococcosis? Transcriptomic and immunoproteomic in vitro approaches.

Lactococcus garvieae is the aetiological agent of lactococcosis, a haemorrhagic septicaemia that affects marine and freshwater fish, with special incidence and economic relevance in farmed rainbow trout. Water temperature is one of the most important predisposing factors in the development of lactococcosis outbreaks. Lactococcosis in trout usually occur when water temperatures rise to about 18 °C, while fish carriers remain asymptomatic at temperatures below 13 °C. The aim of this work was to analyse the differences in the complete transcriptome response of L. garvieae grown at 18 °C and at 13 °C and to identify the immunogenic proteins expressed by this bacterium at 18 °C. Our results show that water temperature influences the expression of L. garvieae genes involved in the lysis of part of the bacterial cell population and in the cold response bacterial adaptation. Moreover, the surface immunogenic protein profile at 18 °C suggests an important role of the lysozyme-like enzyme, WxL surface proteins and some putative moonlighting proteins (proteins with more than one function, usually associated with different cellular locations) as virulence factors in L. garvieae. The results of this study could provide insights into the understanding of the virulence mechanisms of L. garvieae in fish.

EHR Big Data Deep Phenotyping. Contribution of the IMIA Genomic Medicine Working Group.

OBJECTIVES: Given the quickening speed of discovery of variant disease drivers from combined patient genotype and phenotype data, the objective is to provide methodology using big data technology to support the definition of deep phenotypes in medical records. METHODS: As the vast stores of genomic information increase with next generation sequencing, the importance of deep phenotyping increases. The growth of genomic data and adoption of Electronic Health Records (EHR) in medicine provides a unique opportunity to integrate phenotype and genotype data into medical records. The method by which collections of clinical findings and other health related data are leveraged to form meaningful phenotypes is an active area of research. Longitudinal data stored in EHRs provide a wealth of information that can be used to construct phenotypes of patients. We focus on a practical problem around data integration for deep phenotype identification within EHR data. The use of big data approaches are described that enable scalable markup of EHR events that can be used for semantic and temporal similarity analysis to support the identification of phenotype and genotype relationships. CONCLUSIONS: Stead and colleagues' 2005 concept of using light standards to increase the productivity of software systems by riding on the wave of hardware/processing power is described as a harbinger for designing future healthcare systems. The big data solution, using flexible markup, provides a route to improved utilization of processing power for organizing patient records in genotype and phenotype research.

Polymorphism in cathelicidin gene (CAMP) that alters Hypoxia-inducible factor (HIF-1α::ARNT) binding is not associated with tuberculosis.

Polymorphisms in the CAMP gene (cathelicidin) have not been tested in tuberculosis susceptibility. We tested polymorphisms rs9844812 (HIF-1α::ARNT binding site) and rs56122065 (CAMP) plus rs1800972 (DEFB1). SNP rs1800972 was associated with extrapulmonary tuberculosis (EPTB) in a codominant model (genotype CG, P = 0.037, OR 4.82; 95% CI: 0.92-47.42; statistical power, 82%), but not PTB (P = 0.101) in a Mexican population.

Nanoinformatics: developing new computing applications for nanomedicine.

Nanoinformatics has recently emerged to address the need of computing applications at the nano level. In this regard, the authors have participated in various initiatives to identify its concepts, foundations and challenges. While nanomaterials open up the possibility for developing new devices in many industrial and scientific areas, they also offer breakthrough perspectives for the prevention, diagnosis and treatment of diseases. In this paper, we analyze the different aspects of nanoinformatics and suggest five research topics to help catalyze new research and development in the area, particularly focused on nanomedicine. We also encompass the use of informatics to further the biological and clinical applications of basic research in nanoscience and nanotechnology, and the related concept of an extended "nanotype" to coalesce information related to nanoparticles. We suggest how nanoinformatics could accelerate developments in nanomedicine, similarly to what happened with the Human Genome and other -omics projects, on issues like exchanging modeling and simulation methods and tools, linking toxicity information to clinical and personal databases or developing new approaches for scientific ontologies, among many others.

Intubated patients developing tracheobronchitis or pneumonia have distinctive complement system gene expression signatures in the pre-infection period: A pilot study

Introduction: It remains unknown why some intubated patients remain infection-free while others develop tracheobronchitis (VAT) or pneumonia (VAP). Objective: To identify and compare VAP/VAT gene expression "signatures" using genome-wide oligonucleotide microarrays. Material and methods: A prospective translational study of gene expression profiles of VAP and VAT groups was carried out, establishing comparisons in both pre-infection and infection phases. Pathway and functional analyses were performed with Ingenuity Pathway Analysis (IPA). Data analysis and hierarchical clustering of the genes involved in the signalling pathways expressed differentially in the two groups were performed with GeneSpring GX 11.0. Results: Eight patients developing respiratory infections (3 VAP and 5 VAT) after 4 days of mechanical ventilation were assessed. Comparison of gene expression profiles in the pre-infection period revealed 5595 genes expressed differentially between VAP and VAT (p<0.01, fold change >2). Comparative IPA analysis identified a significant depression of the complement system signalling pathway in the VAP group, affecting the classical pathway along with the final common pathway (p<0.05). In addition, the cAMP and calcium signalling pathways were also significantly depressed in the VAP group during the pre-infection phase also. Conclusion: Intubated patients complicated with pneumonia developed immune impairment in the pre-infection period, manifesting as a relatively lower expression of genes involved in the complement system that differed from patients developing tracheobronchitis. These findings suggest that a significant proportion of VAP episodes cannot be prevented, but might be treatable through pre-emptive therapy (AU)

Introducción: Seguimos sin saber por qué algunos pacientes intubados no sufren infecciones mientras que otros presentan traqueobronquitis (TAV) o neumonía (NAV). Objetivo: Identificar y comparar los patrones de la expresión genética de la NAV/TAV usando micromatrices multigénicas oligonucleotídicas. Material y métodos: Se realizó un estudio aplicado prospectivo de los patrones de la expresión genética de los grupos con NAV y TAV, estableciendo comparaciones tanto en la fase previa a la infección como en la fase infecciosa. Se realizaron análisis de vías y funcionales con Ingenuity Pathway (IPA). Los análisis de datos y el agrupamiento jerárquico de los genes implicados en las vías de señalización expresados de forma diferenciada en ambos grupos se realizaron con GeneSpring GX 11.0. Resultados: Se evaluaron ocho pacientes que presentaron infecciones respiratorias (3 NAV y 5 TAV) después de 4 días con la ventilación mecánica. La comparación de los perfiles de la expresión genética durante el período previo a la infección reveló 5.595 genes expresados de forma diferenciada entre la NAV y la TAV (p<0,01, cambio múltiplo>2). Los análisis comparativos de los IPA identificaron una depresión importante de la vía de señalización del sistema del complemento en el grupo con NAV, que afectó a la vía clásica además de a la vía común final (p<0,05). Por otra parte, el monofosfato cíclico de adenosina y las vías de señalización del calcio también se vieron muy deprimidos en el grupo (..)(AU)

Intubated patients developing tracheobronchitis or pneumonia have distinctive complement system gene expression signatures in the pre-infection period: a pilot study.

INTRODUCTION: It remains unknown why some intubated patients remain infection-free while others develop tracheobronchitis (VAT) or pneumonia (VAP). OBJECTIVE: To identify and compare VAP/VAT gene expression "signatures" using genome-wide oligonucleotide microarrays. MATERIAL AND METHODS: A prospective translational study of gene expression profiles of VAP and VAT groups was carried out, establishing comparisons in both pre-infection and infection phases. Pathway and functional analyses were performed with Ingenuity Pathway Analysis (IPA). Data analysis and hierarchical clustering of the genes involved in the signalling pathways expressed differentially in the two groups were performed with GeneSpring GX 11.0. RESULTS: Eight patients developing respiratory infections (3 VAP and 5 VAT) after 4 days of mechanical ventilation were assessed. Comparison of gene expression profiles in the pre-infection period revealed 5595 genes expressed differentially between VAP and VAT (p<0.01, fold change >2). Comparative IPA analysis identified a significant depression of the complement system signalling pathway in the VAP group, affecting the classical pathway along with the final common pathway (p<0.05). In addition, the cAMP and calcium signalling pathways were also significantly depressed in the VAP group during the pre-infection phase also. CONCLUSION: Intubated patients complicated with pneumonia developed immune impairment in the pre-infection period, manifesting as a relatively lower expression of genes involved in the complement system that differed from patients developing tracheobronchitis. These findings suggest that a significant proportion of VAP episodes cannot be prevented, but might be treatable through pre-emptive therapy.

Training health professionals in bioinformatics. Experiences and lessons learned.

BACKGROUND: Genomic technologies and particularly bioinformatics have significantly changed biomedical research along the last decade and are being recognized as potential methods for application also in medical practice and public health. There exists a growing need for different collectives of the healthcare sector to receive training in the methods, tools and databases related with these new areas. OBJECTIVES: This paper describes the teaching experience of our department during the last ten years and analyzes past activities designed for teaching bioinformatics to different groups of health professionals. We aim to illustrate the main lessons learned and offer useful clues to other groups interested in setting up training initiatives in bioinformatics for health professionals. METHODS: The group selected several methodologies for the training activities ("face-to-face", online/e-learning) on the basis of three criteria: 1) the target collective, 2) the contents of the course, and 3) its length. Courses were evaluated and the results are hereby presented and discussed. RESULTS: National and international training courses on bioinformatics, biomedical informatics and genomics were developed according to specific requirements defined by the profile of each of the targeted health professional group. These activities provided the students with the necessary skills for better understanding the use of bioinformatics tools and databases and the appropriate way of applying them into specific health domains. CONCLUSIONS: The increasing demand of training courses in new technologies related to genomics and bioinformatics by health professionals provides a good opportunity for the development of tailored courses based on their specific needs, expectations and demands geared to bridge the gap between research and practice and facilitating their everyday work.

Analysis and management of HIV peptide microarray experiments.

OBJECTIVES: To develop a tool for then easy and user-friendly management of peptide microarray experiments and for the use of the results of these experiments for the study the immune response against HIV virus infection in clinical samples. METHODS: Applying bioinformatics and statistics for the analysis of data coming from microarray experiments as well as implementing a MIAME (Minimum Information About a Microarray Experiment) compliant database for managing and annotating experiments, results and samples. RESULTS: We present a new tool for managing not only nucleic acid microarray experiments but also protein microarray experiments. From the analysis of experimental data, we can detect different profiles in the reactivity of the sera with different genotypes. CONCLUSIONS: We have developed a new tool for managing microarray data including clinical annotations for the samples as well as the capability of annotating other microarray formats different to those based on nucleic acids. The use of peptide microarrays and bioinformatics analysis opens a new scope for the characterization of the immune response, and analyzing and identifying the humoral response of viruses with different genotypes.

Oligonucleotide array for simultaneous detection of respiratory viruses using a reverse-line blot hybridization assay.

The interest in developing new diagnostic methods based on arrays of multiple probes to detect and type simultaneously a wide range of different infectious agents is increasing. This becomes a necessity in the case of infectious agents such as respiratory viruses that cause diseases with very similar signs and symptoms. Such tools will permit rapid and accurate diagnosis of different agents causing respiratory infection leading to the most adequate prevention and/or treatment measures. In this article a reverse-line blot hybridization (RLB) assay for the detection of a wide range of respiratory viruses is presented and evaluated for its usefulness in routine diagnosis. This assay employs an array of 18 oligonucleotide probes immobilized on a nylon membrane. Biotin-labeled PCR products obtained with two multiplex reverse transcription (RT)-polymerase chain reaction (PCR) assays described previously, which allow for the detection of fourteen different groups of respiratory viruses, were hybridized to the oligonucleotide array. Detection was performed using a chemiluminescent method. The standardization of the method showed that the RLB assay could be an alternative to the nested PCR assay for enhancing the sensitivity in the detection of the amplified products, avoiding the problem of cross-over contamination, increasing the specificity, and therefore simplifying the method. This is of main interest in laboratories with few facilities. The feasibility and accuracy of the RT-PCR-RLB assay for detecting respiratory viruses proves that such approach could be a first stage to develop a microarray assay for routine diagnosis of infectious diseases.

Integrating genomics into health information systems.

OBJECTIVE: To outline the main issues related to the impact of the data generated by the Human Genome Project on health information systems. A major challenge for medical informatics is identified, consisting of adapting traditional systems to new genetic-based diagnostic and therapeutic tools. METHODS: Reviewing and analysing the different health information levels from an organisational complexity point of view. A model is proposed to explain the interactions between health informatics, bioinformatics and molecular medicine. RESULTS: We suggest a new framework that integrates genetic data into health information systems. Using this model, new topics for future research and development are identified. CONCLUSIONS: We are witnessing the birth of a new era (post-genomics). In this era technological advancements in genomics offer new opportunities for clinical applications. Medical informaticians should play an important role in this new endeavour.