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1.  Rat Genome Database (RGD): mapping disease onto the genome 
Nucleic Acids Research  2002;30(1):125-128.
The Rat Genome Database (RGD, http://rgd.mcw.edu) is an NIH-funded project whose stated mission is ‘to collect, consolidate and integrate data generated from ongoing rat genetic and genomic research efforts and make these data widely available to the scientific community’. In a collaboration between the Bioinformatics Research Center at the Medical College of Wisconsin, the Jackson Laboratory and the National Center for Biotechnology Information, RGD has been created to meet these stated aims. The rat is uniquely suited to its role as a model of human disease and the primary focus of RGD is to aid researchers in their study of the rat and in applying their results to studies in a wider context. In support of this we have integrated a large amount of rat genetic and genomic resources in RGD and these are constantly being expanded through ongoing literature and bulk dataset curation. RGD version 2.0, released in June 2001, includes curated data on rat genes, quantitative trait loci (QTL), microsatellite markers and rat strains used in genetic and genomic research. VCMap, a dynamic sequence-based homology tool was introduced, and allows researchers of rat, mouse and human to view mapped genes and sequences and their locations in the other two organisms, an essential tool for comparative genomics. In addition, RGD provides tools for gene prediction, radiation hybrid mapping, polymorphic marker selection and more. Future developments will include the introduction of disease-based curation expanding the curated information to cover popular disease systems studied in the rat. This will be integrated with the emerging rat genomic sequence and annotation pipelines to provide a high-quality disease-centric resource, applicable to human and mouse via comparative tools such as VCMap. RGD has a defined community outreach focus with a Visiting Scientist program and the Rat Community Forum, a web-based forum for rat researchers and others interested in using the rat as an experimental model. Thus, RGD is not only a valuable resource for those working with the rat but also for researchers in other model organisms wishing to harness the existing genetic and physiological data available in the rat to complement their own work.
PMCID: PMC99132  PMID: 11752273
2.  The Rat Genome Database 2009: variation, ontologies and pathways 
Nucleic Acids Research  2008;37(Database issue):D744-D749.
The Rat Genome Database (RGD, http://rgd.mcw.edu) was developed to provide a core resource for rat researchers combining genetic, genomic, pathway, phenotype and strain information with a focus on disease. RGD users are provided with access to structured and curated data from the molecular level through to the level of the whole organism, including the variations associated with disease phenotypes. To fully support use of the rat as a translational model for biological systems and human disease, RGD continues to curate these datasets while enhancing and developing tools to allow efficient and effective access to the data in a variety of formats including linear genome viewers, pathway diagrams and biological ontologies. To support pathophysiological analysis of data, RGD Disease Portals provide an entryway to integrated gene, QTL and strain data specific to a particular disease. In addition to tool and content development and maintenance, RGD promotes rat research and provides user education by creating and disseminating tutorials on the curated datasets, submission processes, and tools available at RGD. By curating, storing, integrating, visualizing and promoting rat data, RGD ensures that the investment made into rat genomics and genetics can be leveraged by all interested investigators.
doi:10.1093/nar/gkn842
PMCID: PMC2686558  PMID: 18996890
3.  Using Multiple Ontologies to Integrate Complex Biological Data 
Comparative and Functional Genomics  2005;6(7-8):373-378.
The strength of the rat as a model organism lies in its utility in pharmacology, biochemistry and physiology research. Data resulting from such studies is difficult to represent in databases and the creation of user-friendly data mining tools has proved difficult. The Rat Genome Database has developed a comprehensive ontology-based data structure and annotation system to integrate physiological data along with environmental and experimental factors, as well as genetic and genomic information. RGD uses multiple ontologies to integrate complex biological information from the molecular level to the whole organism, and to develop data mining and presentation tools. This approach allows RGD to indicate not only the phenotypes seen in a strain but also the specific values under each diet and atmospheric condition, as well as gender differences. Harnessing the power of ontologies in this way allows the user to gather and filter data in a customized fashion, so that a researcher can retrieve all phenotype readings for which a high hypoxia is a factor. Utilizing the same data structure for expression data, pathways and biological processes, RGD will provide a comprehensive research platform which allows users to investigate the conditions under which biological processes are altered and to elucidate the mechanisms of disease.
doi:10.1002/cfg.498
PMCID: PMC2447497  PMID: 18629202
4.  Ensemble Models of Neutrophil Trafficking in Severe Sepsis 
PLoS Computational Biology  2012;8(3):e1002422.
A hallmark of severe sepsis is systemic inflammation which activates leukocytes and can result in their misdirection. This leads to both impaired migration to the locus of infection and increased infiltration into healthy tissues. In order to better understand the pathophysiologic mechanisms involved, we developed a coarse-grained phenomenological model of the acute inflammatory response in CLP (cecal ligation and puncture)-induced sepsis in rats. This model incorporates distinct neutrophil kinetic responses to the inflammatory stimulus and the dynamic interactions between components of a compartmentalized inflammatory response. Ensembles of model parameter sets consistent with experimental observations were statistically generated using a Markov-Chain Monte Carlo sampling. Prediction uncertainty in the model states was quantified over the resulting ensemble parameter sets. Forward simulation of the parameter ensembles successfully captured experimental features and predicted that systemically activated circulating neutrophils display impaired migration to the tissue and neutrophil sequestration in the lung, consequently contributing to tissue damage and mortality. Principal component and multiple regression analyses of the parameter ensembles estimated from survivor and non-survivor cohorts provide insight into pathologic mechanisms dictating outcome in sepsis. Furthermore, the model was extended to incorporate hypothetical mechanisms by which immune modulation using extracorporeal blood purification results in improved outcome in septic rats. Simulations identified a sub-population (about of the treated population) that benefited from blood purification. Survivors displayed enhanced neutrophil migration to tissue and reduced sequestration of lung neutrophils, contributing to improved outcome. The model ensemble presented herein provides a platform for generating and testing hypotheses in silico, as well as motivating further experimental studies to advance understanding of the complex biological response to severe infection, a problem of growing magnitude in humans.
Author Summary
The pathophysiology of sepsis is complex and our mechanistic understanding remains incomplete. Mathematical models of the inflammatory response have been providing intellectual frameworks to reason about the complexity of sepsis. Due to an incompletely understood system along with very limited data, our approach focuses on building simplified, falsifiable and predictive models, and offers a means to quantify parametric uncertainty. Based on the construct that deterministic ensemble models exhibit population-like behavior, we developed a population-based computational framework that incorporates dysregulated neutrophil hyperactivity as a cellular dysfunction in septic processes. We hypothesize that probability distributions of physiological parameters conditional on population observations can characterize the range of possible physiologic responses in a population. Comparing the parameter ensembles from different phenotypes reveals some factors that play an important role in the expression of such phenotypes, such as sepsis survival. This framework can serve as an effective tool to gain insight into the pathophysiology of severe sepsis and generate testable hypotheses that guide future experiments. Our approach holds promise as a tool for integrating domain knowledge and experimental data into a quantitative assessment of population dynamics.
doi:10.1371/journal.pcbi.1002422
PMCID: PMC3297568  PMID: 22412365
5.  A self-evaluation tool for integrated care services: the Development Model for Integrated Care applied in practice 
Purpose
The purpose of the workshop is to show the applications of the Development Model for Integrated Care (DMIC) in practice. This relatively new and validated model, can be used by integrated care practices to evaluate their integrated care, to assess their phase of development and reveal improvement areas. In the workshop the results of the use of the model in three types of integrated care settings in the Netherlands will be presented. Participants are offered practical instruments based on the validated DMIC to use in their own setting and will be introduced to the webbased tool.
Context
To integrate care from multiple providers into a coherent and streamlined client-focused service, a large number of activities and agreements have to be implemented like streamlining information flows and adequate transfers of clients. In the large range of possible activities it is often not clear what essential activities are and where to start or continue. Also, knowledge about how to further develop integrated care services is needed. The Development Model for Integrated Care (DMIC), based on PhD research of Mirella Minkman, describes nine clusters containing in total 89 elements that contribute to the integration of care. The clusters are named: ‘client-centeredness’, ‘delivery system’, ‘performance management’, ‘quality of care’, ‘result-focused learning’, ‘interprofessional teamwork’, ‘roles and tasks’, ‘commitment’, and ‘transparant entrepreneurship’ [1–3]. In 2011 a new digital webbased self-evolution tool which contains the 89 elements grouped in nine clusters was developed. The DMIC also describes four phases of development [4]. The model is empirically validated in practice by assessing the relevance and implementation of the elements and development phases in 84 integrated care services in The Netherlands: in stroke, acute myocardial infarct (AMI), and dementia services. The validation studies are recently published [5, 6]. In 2011 also other integrated care services started using the model [7]. Vilans developed a digital web-based self-evaluation tool for integrated care services based on the DMIC. A palliative care network, four diabetes services, a youth care service and a network for autism used the self-evaluation tool to evaluate the development of their integrated care service. Because of its generic character, the model and tool are believed to be also interesting internationally.
Data sources
In the workshop we will present the results of three studies in integrated diabetes, youth and palliative care. The three projects consist of multiple steps, see below. Workshop participants could also work with the DMIC following these steps.
One: Preparation of the digital self-evolution tool for integrated care services
Although they are very different, the three integrated care services all wanted to gain insight in their development and improvement opportunities. We tailored the digital self-evaluation tool for each specific integrated care services, but for all the basis was the DMIC. Personal accounts for the digital DMIC self-evalution survey were sent to multiple partners working in each integrated care service (4–16 partners).
Two: Use of the online self-evaluation tool each partner of the local integrated care setting evaluated the integrated care by filling in the web-based questionnaire. The tool consists of three parts (A-C) named: general information about the integrated care practice (A); the clusters and elements of the DMIC (B); and the four phases of development (C). The respondents rated the relevance and presence of each element in their integrated care practice. Respondents were asked to estimate in which phase of development their thought their service was.
Three: Analysing the results
Advisers from Vilans, the Centre of excellence for long-term care in the Netherlands, analysed the self-evolution results in cooperation with the integrated care coordinators. The results show the total amount of implemented integrated care elements per cluster in spider graphs and the development phase as calculated by the DMIC model. Suggestions for further development of the integrated care services were analysed and reported.
Four: Discussing the implications for further development
In a workshop with the local integrated care partners the results of the self-evaluation were presented and discussed. We noticed remarkable results and highlight elements for further development. In addition, we gave advice for further development appropriate to the development phase of the integrated care service. Furthermore, the professionals prioritized the elements and decided which elements to start working on. This resulted in a (quality improvement) plan for the further development of the integrated care service.
Five: Reporting results
In a report all the results of the survey (including consensus scores) and the workshops came together. The integrated care coordinators stated that the reports really helped them to assess their improvement strategy. Also, there was insight in the development phase of their service which gave tools for further development.
Case description
The three cases presented are a palliative network, an integrated diabetes services and an integrated care network for youth in the Netherlands. The palliative care network wanted to reflect on their current development, to build a guiding framework for further development of the network. About sixteen professionals within the network worked with the digital self-evaluation tool and the DMIC: home care organisations, welfare organizations, hospice centres, health care organisations, community organizations.
For diabetes care, a Dutch health care insurance company wished to gain insight in the development of the contracted integrated care services to stimulate further development of the services. Professionals of three diabetes integrated care services were invited to fill in the digital self-evaluation tool. Of each integrated care service professionals like a general practitioner, a diabetes nurse, a medical specialist, a dietician and a podiatrist were invited. In youth care, a local health organisation wondered whether the DMIC could be helpful to visualize the results of youth integrated care services at process- and organisational level. The goal of the project was to define indicators at a process- and organisational level for youth care services based on the DMIC. In the future, these indicators might be used to evaluate youth care integrated care services and improve the quality of youth care within the Netherlands.
Conclusions and discussion
It is important for the quality of integrated care services that the involved coordinators, managers and professionals are aware of the development process of the integrated care service and that they focus on elements which can further develop and improve their integrated care. However, we noticed that integrated care services in the Netherlands experience difficulties in developing their integrated care service. It is often not clear what essential activities are to work on and how to further develop the integrated care service. A guiding framework for the development of integrated care was missing. The DMIC model has been developed for that reason and offers a useful tool for assessment, self-evaluation or improvement of integrated care services in practice. The model has been validated for AMI, dementia and stroke services. The latest new studies in diabetes, palliative care and youth care gave further insight in the generic character of the DMIC. Based on these studies it can be assumed that the DMIC can be used for multiple types of integrated care services. The model is assumed to be interesting for an international audience. Improving integrated care is a complex topic in a large number of countries; the DMIC is also based on the international literature. Dutch integrated care coordinators stated that the DMIC helped them to assess their integrated care development in practice and supported them in obtaining ideas for expanding and improving their integrated care activities.
The web-based self-evaluation tool focuses on a process- and organisational level of integrated care. Also, the self assessed development phase can be compared to the development phase as calculated by the DMIC tool. The cases showed this is fruitful input for discussions. When using the tool, the results can also be used in quality policy reports and improvement plans. The web-based tool is being tested at this moment in practice, but in San Marino we can present the latest webversion and demonstrate with a short video how to use the tool and model. During practical exercises in the workshop the participants will experience how the application of the DMIC can work for them in practice or in research. For integrated care researchers and policy makers, the DMIC questionnaire and tool is a promising method for further research and policy plans in integrated care.
PMCID: PMC3617779
development model for integrated care; development of integrated care services; implementation and improvement of integrated care; self evaluation
6.  Eurocan plus report: feasibility study for coordination of national cancer research activities 
Summary
The EUROCAN+PLUS Project, called for by the European Parliament, was launched in October 2005 as a feasibility study for coordination of national cancer research activities in Europe. Over the course of the next two years, the Project process organized over 60 large meetings and countless smaller meetings that gathered in total over a thousand people, the largest Europe–wide consultation ever conducted in the field of cancer research.
Despite a strong tradition in biomedical science in Europe, fragmentation and lack of sustainability remain formidable challenges for implementing innovative cancer research and cancer care improvement. There is an enormous duplication of research effort in the Member States, which wastes time, wastes money and severely limits the total intellectual concentration on the wide cancer problem. There is a striking lack of communication between some of the biggest actors on the European scene, and there are palpable tensions between funders and those researchers seeking funds.
It is essential to include the patients’ voice in the establishment of priority areas in cancer research at the present time. The necessity to have dialogue between funders and scientists to establish the best mechanisms to meet the needs of the entire community is evident. A top priority should be the development of translational research (in its widest form), leading to the development of effective and innovative cancer treatments and preventive strategies. Translational research ranges from bench–to–bedside innovative cancer therapies and extends to include bringing about changes in population behaviours when a risk factor is established.
The EUROCAN+PLUS Project recommends the creation of a small, permanent and independent European Cancer Initiative (ECI). This should be a model structure and was widely supported at both General Assemblies of the project. The ECI should assume responsibility for stimulating innovative cancer research and facilitating processes, becoming the common voice of the cancer research community and serving as an interface between the cancer research community and European citizens, patients’ organizations, European institutions, Member States, industry and small and medium enterprises (SMEs), putting into practice solutions aimed at alleviating barriers to collaboration and coordination of cancer research activities in the European Union, and dealing with legal and regulatory issues. The development of an effective ECI will require time, but this entity should be established immediately. As an initial step, coordination efforts should be directed towards the creation of a platform on translational research that could encompass (1) coordination between basic, clinical and epidemiological research; (2) formal agreements of co–operation between comprehensive cancer centres and basic research laboratories throughout Europe and (3) networking between funding bodies at the European level.
The European Parliament and its instruments have had a major influence in cancer control in Europe, notably in tobacco control and in the implementation of effective population–based screening. To make further progress there is a need for novelty and innovation in cancer research and prevention in Europe, and having a platform such as the ECI, where those involved in all aspects of cancer research can meet, discuss and interact, is a decisive development for Europe.
Executive Summary
Cancer is one of the biggest public health crises facing Europe in the 21st century—one for which Europe is currently not prepared nor preparing itself. Cancer is a major cause of death in Europe with two million casualties and three million new cases diagnosed annually, and the situation is set to worsen as the population ages.
These facts led the European Parliament, through the Research Directorate-General of the European Commission, to call for initiatives for better coordination of cancer research efforts in the European Union. The EUROCAN+PLUS Project was launched in October 2005 as a feasibility study for coordination of national cancer research activities. Over the course of the next two years, the Project process organized over 60 large meetings and countless smaller meetings that gathered in total over a thousand people. In this respect, the Project became the largest Europe-wide consultation ever conducted in the field of cancer research, implicating researchers, cancer centres and hospitals, administrators, healthcare professionals, funding agencies, industry, patients’ organizations and patients.
The Project first identified barriers impeding research and collaboration in research in Europe. Despite a strong tradition in biomedical science in Europe, fragmentation and lack of sustainability remain the formidable challenges for implementing innovative cancer research and cancer care improvement. There is an enormous duplication of research effort in the Member States, which wastes time, wastes money and severely limits the total intellectual concentration on the wide cancer problem. There is a striking lack of communication between some of the biggest actors on the European scene, and there are palpable tensions between funders and those researchers seeking funds.
In addition, there is a shortage of leadership, a multiplicity of institutions each focusing on its own agenda, sub–optimal contact with industry, inadequate training, non–existent career paths, low personnel mobility in research especially among clinicians and inefficient funding—all conspiring against efficient collaboration in cancer care and research. European cancer research today does not have a functional translational research continuum, that is the process that exploits biomedical research innovations and converts them into prevention methods, diagnostic tools and therapies. Moreover, epidemiological research is not integrated with other types of cancer research, and the implementation of the European Directives on Clinical Trials 1 and on Personal Data Protection 2 has further slowed the innovation process in Europe. Furthermore, large inequalities in health and research exist between the EU–15 and the New Member States.
The picture is not entirely bleak, however, as the European cancer research scene presents several strengths, such as excellent basic research and clinical research and innovative etiological research that should be better exploited.
When considering recommendations, several priority dimensions had to be retained. It is essential that proposals include actions and recommendations that can benefit all Member States of the European Union and not just States with the elite centres. It is also essential to have a broader patient orientation to help provide the knowledge to establish cancer control possibilities when we exhaust what can be achieved by the implementation of current knowledge. It is vital that the actions proposed can contribute to the Lisbon Strategy to make Europe more innovative and competitive in (cancer) research.
The Project participants identified six areas for which consensus solutions should be implemented in order to obtain better coordination of cancer research activities. The required solutions are as follows. The proactive management of innovation, detection, facilitation of collaborations and maintenance of healthy competition within the European cancer research community.The establishment of an exchange portal of information for health professionals, patients and policy makers.The provision of guidance for translational and clinical research including the establishment of a translational research platform involving comprehensive cancer centres and cancer research centres.The coordination of calls and financial management of cancer research projects.The construction of a ‘one–stop shop’ as a contact interface between the industry, small and medium enterprises, scientists and other stakeholders.The support of greater involvement of healthcare professionals in translational research and multidisciplinary training.
In the course of the EUROCAN+PLUS consultative process, several key collaborative projects emerged between the various groups and institutes engaged in the consultation. There was a collaboration network established with Europe’s leading Comprehensive Cancer Centres; funding was awarded for a closer collaboration of Owners of Cancer Registries in Europe (EUROCOURSE); there was funding received from FP7 for an extensive network of leading Biological Resource Centres in Europe (BBMRI); a Working Group identified the special needs of Central, Eastern and South–eastern Europe and proposed a remedy (‘Warsaw Declaration’), and the concept of developing a one–stop shop for dealing with academia and industry including the Innovative Medicines Initiative (IMI) was discussed in detail.
Several other dimensions currently lacking were identified. There is an absolute necessity to include the patients’ voice in the establishment of priority areas in cancer research at the present time. It was a salutary lesson when it was recognized that all that is known about the quality of life of the cancer patient comes from the experience of a tiny proportion of cancer patients included in a few clinical trials. The necessity to have dialogue between funders and scientists to establish the best mechanisms to meet the needs of the entire community was evident. A top priority should be the development of translational research (in its widest form) and the development of effective and innovative cancer treatments and preventative strategies in the European Union. Translational research ranges from bench-to-bedside innovative cancer therapies and extends to include bringing about changes in population behaviours when a risk factor is established.
Having taken note of the barriers and the solutions and having examined relevant examples of existing European organizations in the field, it was agreed during the General Assembly of 19 November 2007 that the EUROCAN+PLUS Project had to recommend the creation of a small, permanent and neutral ECI. This should be a model structure and was widely supported at both General Assemblies of the project. The proposal is based on the successful model of the European Molecular Biology Organisation (EMBO), and its principal aims include providing a forum where researchers from all backgrounds and from all countries can meet with members of other specialities including patients, nurses, clinicians, funders and scientific administrators to develop priority programmes to make Europe more competitive in research and more focused on the cancer patient.
The ECI should assume responsibility for: stimulating innovative cancer research and facilitating processes;becoming the common voice of the cancer research community and serving as an interface between the cancer research community and European citizens, patients’ and organizations;European institutions, Member States, industry and small and medium enterprises;putting into practice the aforementioned solutions aimed at alleviating barriers and coordinating cancer research activities in the EU;dealing with legal and regulatory issues.
Solutions implemented through the ECI will lead to better coordination and collaboration throughout Europe, more efficient use of resources, an increase in Europe’s attractiveness to the biomedical industry and better quality of cancer research and education of health professionals.
The Project considered that European legal instruments currently available were inadequate for addressing many aspects of the barriers identified and for the implementation of effective, lasting solutions. Therefore, the legal environment that could shelter an idea like the ECI remains to be defined but should be done so as a priority. In this context, the initiative of the European Commission for a new legal entity for research infrastructure might be a step in this direction. The development of an effective ECI will require time, but this should be established immediately. As an initial step, coordination efforts should be directed towards the creation of a platform on translational research that could encompass: (1) coordination between basic, clinical and epidemiological research; (2) formal agreements of co-operation between comprehensive cancer centres and basic research laboratories throughout Europe; (3) networking between funding bodies at the European level. Another topic deserving immediate attention is the creation of a European database on cancer research projects and cancer research facilities.
Despite enormous progress in cancer control in Europe during the past two decades, there was an increase of 300,000 in the number of new cases of cancer diagnosed between 2004 and 2006. The European Parliament and its instruments have had a major influence in cancer control, notably in tobacco control and in the implementation of effective population–based screening. To make further progress there is a need for novelty and innovation in cancer research and prevention in Europe, and having a platform such as the ECI, where those involved in all aspects of cancer research can meet, discuss and interact, is a decisive development for Europe.
doi:10.3332/ecancer.2011.84
PMCID: PMC3234055  PMID: 22274749
7.  Insight into human alveolar macrophage and M. tuberculosis interactions via metabolic reconstructions 
A human alveolar macrophage genome-scale metabolic reconstruction was reconstructed from tailoring a global human metabolic network, Recon 1, by using computational algorithms and manual curation.A genome-scale host–pathogen network of the human alveolar macrophage and Mycobacterium tuberculosis is presented. This involved integrating two genome-scale network reconstructions.The reaction activity and gene essentiality predictions of the host–pathogen model represent a more accurate depiction of infection.Integration of high-throughput data into a host-pathogen model followed by systems analysis was performed in order to elucidate major metabolic differences under different types of M. tuberculosis infection.
Mycobacterium tuberculosis (M. tb) is an insidious and highly persistent pathogen that affects one-third of the world's population (WHO, 2009). Metabolism is foundational to M. tb's infection ability and the ensuing host–pathogen interactions. In addition, M. tb has a heterogeneous clinical presentation and can infect virtually every tissue. Depending on the location of the infection, different metabolic pathways are active and inactive in both the host and pathogen cells. In this study, we sought to model the host–pathogen interactions of the human alveolar macrophage and M. tb as well as detail the metabolic differences in specific infection types using genome-scale metabolic reconstructions (Figure 4A).
Genome-scale metabolic reconstructions are knowledge bases of all known metabolic reactions of a given organism. Reconstructions have been shown to elucidate the mechanistic genotype-to-phenotype relationship through the integration of high-throughput and physiological data (Oberhardt et al, 2009). Genome-scale reconstructions are converted into mathematical models under the constraints-based reconstruction and analysis (COBRA) platform (Becker et al, 2007). COBRA models use network stoichiometry and steady-state mass balances to define a solution space of potential flux states that a network can take. Thus, the COBRA approach does not require kinetic parameters.
Recently, the global human metabolic network, Recon 1, has been reconstructed (Duarte et al, 2007). To understand the metabolic host–pathogen integrations of M. tb with its human host, we first tailored the global human metabolic network into a cell-specific metabolic reconstruction of the human alveolar macrophage. This was carried out using established computational algorithms (Becker and Palsson, 2008; Shlomi et al, 2008) and manual curation to confirm the included and excluded reactions. The human alveolar macrophage reconstruction, iAB-AMØ-1410, accounts for 1410 genes, 3012 intracellular reactions, and 2572 metabolites (Figure 4C). iAB-AMØ-1410 was able to accurately predict maximum ATP and NO production rates obtained from experimental data (Griscavage et al, 1993; Newsholme et al, 1999).
The second step to studying host–pathogen interactions was integration of the human alveolar macrophage reconstruction with an existing genome-scale metabolic model of M. tb, iNJ661 (Jamshidi and Palsson, 2007). Interfacial constraints were set to create a phagosomal environment that was hypoxic, nitrosative, rich in fatty acids, and poor in carbohydrates. From the onset, it was apparent that some oxygen (<15% of in vitro uptake) was required for proper simulations. In addition, algorithmic tailoring of the M. tb biomass objective function was performed to better represent an infectious state. The integrated host–pathogen metabolic reconstruction was dubbed iAB-AMØ-1410-Mt-661.
Analysis of the integrated host–pathogen metabolic reconstruction resulted in three main findings. First, by setting interfacial constraints and tailoring the biomass objective function, the solution space better represents an infectious state. Without adding artificial constraints to the host portion of the integrated model, the iAB-AMØ-1410 solution space is greatly reduced (Figure 4B). Macrophage glycolysis and nitric oxide production are up-regulated and macrophage ATP production, nucleotide synthesis, and amino-acid metabolism are suppressed. In addition, M. tb glycolysis is suppressed and isocitrate lyase is up-regulated for generation of acetyl-CoA. Fatty acid oxidation pathways and production of mycolic acids are increased, while production of nucleotides, peptidoglycans, and phenolic glycolipids are reduced. The modified solution space of the alveolar macrophage and M. tb better represents the infectious state.
Second, the host-pathogen model more accurately predicts M. tb gene deletion tests than the current in vitro model, iNJ661. The host-pathogen model predicted 11 essential genes and 37 unessential genes differently than iNJ661. A total of 22 of the differentially predicted genes have been experimentally characterized (Sassetti and Rubin, 2003; Sohaskey, 2008). The host-pathogen model correctly predicted 18 of the 22 genes. Thus, iAB-AMØ-1410-Mt-661 is a more accurate platform for studying infectious states of M. tb.
Finally, we sought to determine metabolic differences in both the macrophage and M. tb between three different types of infection: latent, pulmonary, and meningeal. Transcription profiling data of the macrophage for the three infections (Thuong et al, 2008) were integrated in the context of the host–pathogen network to elucidate the reaction activity of the three infections. There was wide heterogeneity in the three infection states; some of these differences are highlighted. Macrophage hyaluronan synthase and export were only active in the pulmonary infection. This is potentially interesting from a pharmaceutical viewpoint as hyaluronan has been implicated as a potential carbon source for extracellular M. tb (Hirayama et al, 2009). In addition, we detected metabolic activity differences in M. tb pathways that have been previously discussed as potential drug targets (Eoh et al, 2007; Boshoff et al, 2008). Polyprenyl metabolic reactions were only active in the latent state infection, while de novo synthesis of nicotinamide cofactors was only active in latent and meningeal M. tb infections.
Host-pathogen modeling represents a novel approach for studying metabolic interactions during infection. iAB-AMØ-1410-Mt-661 is a more accurate platform for understanding the biology and pathophysiology of M. tb infection. Most importantly, genome-scale metabolic reconstructions can act as scaffolds for integrating high-throughput data. Particularly, in this study we were able to discern reaction activity differences between different infection types.
Metabolic coupling of Mycobacterium tuberculosis to its host is foundational to its pathogenesis. Computational genome-scale metabolic models have shown utility in integrating -omic as well as physiologic data for systemic, mechanistic analysis of metabolism. To date, integrative analysis of host–pathogen interactions using in silico mass-balanced, genome-scale models has not been performed. We, therefore, constructed a cell-specific alveolar macrophage model, iAB-AMØ-1410, from the global human metabolic reconstruction, Recon 1. The model successfully predicted experimentally verified ATP and nitric oxide production rates in macrophages. This model was then integrated with an M. tuberculosis H37Rv model, iNJ661, to build an integrated host–pathogen genome-scale reconstruction, iAB-AMØ-1410-Mt-661. The integrated host–pathogen network enables simulation of the metabolic changes during infection. The resulting reaction activity and gene essentiality targets of the integrated model represent an altered infectious state. High-throughput data from infected macrophages were mapped onto the host–pathogen network and were able to describe three distinct pathological states. Integrated host–pathogen reconstructions thus form a foundation upon which understanding the biology and pathophysiology of infections can be developed.
doi:10.1038/msb.2010.68
PMCID: PMC2990636  PMID: 20959820
computational biology; host–pathogen; Mycobacterium tuberculosis; systems biology; macrophage
8.  PD_NGSAtlas: a reference database combining next-generation sequencing epigenomic and transcriptomic data for psychiatric disorders 
BMC Medical Genomics  2014;7(1):71.
Background
Psychiatric disorders such as schizophrenia (SZ) and bipolar disorder (BP) are projected to lead the global disease burden within the next decade. Several lines of evidence suggest that epigenetic- or genetic-mediated dysfunction is frequently present in these disorders. To date, the inheritance patterns have been complicated by the problem of integrating epigenomic and transcriptomic factors that have yet to be elucidated. Therefore, there is a need to build a comprehensive database for storing epigenomic and transcriptomic data relating to psychiatric disorders.
Description
We have developed the PD_NGSAtlas, which focuses on the efficient storage of epigenomic and transcriptomic data based on next-generation sequencing and on the quantitative analyses of epigenetic and transcriptional alterations involved in psychiatric disorders. The current release of the PD_NGSAtlas contains 43 DNA methylation profiles and 37 transcription profiles detected by MeDIP-Seq and RNA-Seq, respectively, in two distinct brain regions and peripheral blood of SZ, BP and non-psychiatric controls. In addition to these data that were generated in-house, we have included, and will continue to include, published DNA methylation and gene expression data from other research groups, with a focus on psychiatric disorders. A flexible query engine has been developed for the acquisition of methylation profiles and transcription profiles for special genes or genomic regions of interest of the selected samples. Furthermore, the PD_NGSAtlas offers online tools for identifying aberrantly methylated and expressed events involved in psychiatric disorders. A genome browser has been developed to provide integrative and detailed views of multidimensional data in a given genomic context, which can help researchers understand molecular mechanisms from epigenetic and transcriptional perspectives. Moreover, users can download the methylation and transcription data for further analyses.
Conclusions
The PD_NGSAtlas aims to provide storage of epigenomic and transcriptomic data as well as quantitative analyses of epigenetic and transcriptional alterations involved in psychiatric disorders. The PD_NGSAtlas will be a valuable data resource and will enable researchers to investigate the pathophysiology and aetiology of disease in detail. The database is available at http://bioinfo.hrbmu.edu.cn/pd_ngsatlas/.
Electronic supplementary material
The online version of this article (doi:10.1186/s12920-014-0071-z) contains supplementary material, which is available to authorized users.
doi:10.1186/s12920-014-0071-z
PMCID: PMC4308070  PMID: 25551368
Schizophrenia; Bipolar disorder; Next-generation sequencing; Epigenomic and transcriptomic data; Brain; Blood
9.  The Rat Genome Database, update 2007—Easing the path from disease to data and back again 
Nucleic Acids Research  2006;35(Database issue):D658-D662.
The Rat Genome Database (RGD, ) is one of the core resources for rat genomics and recent developments have focused on providing support for disease-based research using the rat model. Recognizing the importance of the rat as a disease model we have employed targeted curation strategies to curate genes, QTL and strain data for neurological and cardiovascular disease areas. This work has centered on rat but also includes data for mouse and human to create ‘disease portals’ that provide a unified view of the genes, QTL and strain models for these diseases across the three species. The disease curation efforts combined with normal curation activities have served to greatly increase the content of the database, particularly for biological information, including gene ontology, disease, pathway and phenotype ontology annotations. In addition to improving the features and database content, community outreach has been expanded to demonstrate how investigators can leverage the resources at RGD to facilitate their research and to elicit suggestions and needs for future developments. We have published a number of papers that provide additional information on the ontology annotations and the tools at RGD for data mining and analysis to better enable researchers to fully utilize the database.
doi:10.1093/nar/gkl988
PMCID: PMC1761441  PMID: 17151068
10.  Analysis of disease-associated objects at the Rat Genome Database 
The Rat Genome Database (RGD) is the premier resource for genetic, genomic and phenotype data for the laboratory rat, Rattus norvegicus. In addition to organizing biological data from rats, the RGD team focuses on manual curation of gene–disease associations for rat, human and mouse. In this work, we have analyzed disease-associated strains, quantitative trait loci (QTL) and genes from rats. These disease objects form the basis for seven disease portals. Among disease portals, the cardiovascular disease and obesity/metabolic syndrome portals have the highest number of rat strains and QTL. These two portals share 398 rat QTL, and these shared QTL are highly concentrated on rat chromosomes 1 and 2. For disease-associated genes, we performed gene ontology (GO) enrichment analysis across portals using RatMine enrichment widgets. Fifteen GO terms, five from each GO aspect, were selected to profile enrichment patterns of each portal. Of the selected biological process (BP) terms, ‘regulation of programmed cell death’ was the top enriched term across all disease portals except in the obesity/metabolic syndrome portal where ‘lipid metabolic process’ was the most enriched term. ‘Cytosol’ and ‘nucleus’ were common cellular component (CC) annotations for disease genes, but only the cancer portal genes were highly enriched with ‘nucleus’ annotations. Similar enrichment patterns were observed in a parallel analysis using the DAVID functional annotation tool. The relationship between the preselected 15 GO terms and disease terms was examined reciprocally by retrieving rat genes annotated with these preselected terms. The individual GO term–annotated gene list showed enrichment in physiologically related diseases. For example, the ‘regulation of blood pressure’ genes were enriched with cardiovascular disease annotations, and the ‘lipid metabolic process’ genes with obesity annotations. Furthermore, we were able to enhance enrichment of neurological diseases by combining ‘G-protein coupled receptor binding’ annotated genes with ‘protein kinase binding’ annotated genes.
Database URL: http://rgd.mcw.edu
doi:10.1093/database/bat046
PMCID: PMC3689439  PMID: 23794737
11.  DNA microarray data integration by ortholog gene analysis reveals potential molecular mechanisms of estrogen-dependent growth of human uterine fibroids 
BMC Women's Health  2007;7:5.
Background
Uterine fibroids or leiomyoma are a common benign smooth muscle tumor. The tumor growth is well known to be estrogen-dependent. However, the molecular mechanisms of its estrogen-dependency is not well understood.
Methods
Differentially expressed genes in human uterine fibroids were either retrieved from published papers or from our own statistical analysis of downloaded array data. Probes for the same genes on different Affymetrix chips were mapped based on probe comparison information provided by Affymetrix. Genes identified by two or three array studies were submitted for ortholog analysis. Human and rat ortholog genes were identified by using ortholog gene databases, HomoloGene and TOGA and were confirmed by synteny analysis with MultiContigView tool in the Ensembl genome browser.
Results
By integrated analysis of three recently published DNA microarray studies with human tissue, thirty-eight genes were found to be differentially expressed in the same direction in fibroid compared to adjacent uterine myometrium by at least two research groups. Among these genes, twelve with rat orthologs were identified as estrogen-regulated from our array study investigating uterine expression in ovariectomized rats treated with estrogen. Functional and pathway analyses of the twelve genes suggested multiple molecular mechanisms for estrogen-dependent cell survival and tumor growth. Firstly, estrogen increased expression of the anti-apoptotic PCP4 gene and suppressed the expression of growth inhibitory receptors PTGER3 and TGFBR2. Secondly, estrogen may antagonize PPARγ signaling, thought to inhibit fibroid growth and survival, at two points in the PPAR pathway: 1) through increased ANXA1 gene expression which can inhibit phospholipase A2 activity and in turn decrease arachidonic acid synthesis, and 2) by decreasing L-PGDS expression which would reduce synthesis of PGJ2, an endogenous ligand for PPARγ. Lastly, estrogen affects retinoic acid (RA) synthesis and mobilization by regulating expression of CRABP2 and ALDH1A1. RA has been shown to play a significant role in the development of uterine fibroids in an animal model.
Conclusion
Integrated analysis of multiple array datasets revealed twelve human and rat ortholog genes that were differentially expressed in human uterine fibroids and transcriptionally responsive to estrogen in the rat uterus. Functional and pathway analysis of these genes suggest multiple potential molecular mechanisms for the poorly understood estrogen-dependent growth of uterine fibroids. Fully understanding the exact molecular interactions among these gene products requires further study to validate their roles in uterine fibroids. This work provides new avenues of study which could influence the future direction of therapeutic intervention for the disease.
doi:10.1186/1472-6874-7-5
PMCID: PMC1852551  PMID: 17407572
12.  Metabolic network reconstruction of Chlamydomonas offers insight into light-driven algal metabolism 
A comprehensive genome-scale metabolic network of Chlamydomonas reinhardtii, including a detailed account of light-driven metabolism, is reconstructed and validated. The model provides a new resource for research of C. reinhardtii metabolism and in algal biotechnology.
The genome-scale metabolic network of Chlamydomonas reinhardtii (iRC1080) was reconstructed, accounting for >32% of the estimated metabolic genes encoded in the genome, and including extensive details of lipid metabolic pathways.This is the first metabolic network to explicitly account for stoichiometry and wavelengths of metabolic photon usage, providing a new resource for research of C. reinhardtii metabolism and developments in algal biotechnology.Metabolic functional annotation and the largest transcript verification of a metabolic network to date was performed, at least partially verifying >90% of the transcripts accounted for in iRC1080. Analysis of the network supports hypotheses concerning the evolution of latent lipid pathways in C. reinhardtii, including very long-chain polyunsaturated fatty acid and ceramide synthesis pathways.A novel approach for modeling light-driven metabolism was developed that accounts for both light source intensity and spectral quality of emitted light. The constructs resulting from this approach, termed prism reactions, were shown to significantly improve the accuracy of model predictions, and their use was demonstrated for evaluation of light source efficiency and design.
Algae have garnered significant interest in recent years, especially for their potential application in biofuel production. The hallmark, model eukaryotic microalgae Chlamydomonas reinhardtii has been widely used to study photosynthesis, cell motility and phototaxis, cell wall biogenesis, and other fundamental cellular processes (Harris, 2001). Characterizing algal metabolism is key to engineering production strains and understanding photobiological phenomena. Based on extensive literature on C. reinhardtii metabolism, its genome sequence (Merchant et al, 2007), and gene functional annotation, we have reconstructed and experimentally validated the genome-scale metabolic network for this alga, iRC1080, the first network to account for detailed photon absorption permitting growth simulations under different light sources. iRC1080 accounts for 1080 genes, associated with 2190 reactions and 1068 unique metabolites and encompasses 83 subsystems distributed across 10 cellular compartments (Figure 1A). Its >32% coverage of estimated metabolic genes is a tremendous expansion over previous algal reconstructions (Boyle and Morgan, 2009; Manichaikul et al, 2009). The lipid metabolic pathways of iRC1080 are considerably expanded relative to existing networks, and chemical properties of all metabolites in these pathways are accounted for explicitly, providing sufficient detail to completely specify all individual molecular species: backbone molecule and stereochemical numbering of acyl-chain positions; acyl-chain length; and number, position, and cis–trans stereoisomerism of carbon–carbon double bonds. Such detail in lipid metabolism will be critical for model-driven metabolic engineering efforts.
We experimentally verified transcripts accounted for in the network under permissive growth conditions, detecting >90% of tested transcript models (Figure 1B) and providing validating evidence for the contents of iRC1080. We also analyzed the extent of transcript verification by specific metabolic subsystems. Some subsystems stood out as more poorly verified, including chloroplast and mitochondrial transport systems and sphingolipid metabolism, all of which exhibited <80% of transcripts detected, reflecting incomplete characterization of compartmental transporters and supporting a hypothesis of latent pathway evolution for ceramide synthesis in C. reinhardtii. Additional lines of evidence from the reconstruction effort similarly support this hypothesis including lack of ceramide synthetase and other annotation gaps downstream in sphingolipid metabolism. A similar hypothesis of latent pathway evolution was established for very long-chain fatty acids (VLCFAs) and their polyunsaturated analogs (VLCPUFAs) (Figure 1C), owing to the absence of this class of lipids in previous experimental measurements, lack of a candidate VLCFA elongase in the functional annotation, and additional downstream annotation gaps in arachidonic acid metabolism.
The network provides a detailed account of metabolic photon absorption by light-driven reactions, including photosystems I and II, light-dependent protochlorophyllide oxidoreductase, provitamin D3 photoconversion to vitamin D3, and rhodopsin photoisomerase; this network accounting permits the precise modeling of light-dependent metabolism. iRC1080 accounts for effective light spectral ranges through analysis of biochemical activity spectra (Figure 3A), either reaction activity or absorbance at varying light wavelengths. Defining effective spectral ranges associated with each photon-utilizing reaction enabled our network to model growth under different light sources via stoichiometric representation of the spectral composition of emitted light, termed prism reactions. Coefficients for different photon wavelengths in a prism reaction correspond to the ratios of photon flux in the defined effective spectral ranges to the total emitted photon flux from a given light source (Figure 3B). This approach distinguishes the amount of emitted photons that drive different metabolic reactions. We created prism reactions for most light sources that have been used in published studies for algal and plant growth including solar light, various light bulbs, and LEDs. We also included regulatory effects, resulting from lighting conditions insofar as published studies enabled. Light and dark conditions have been shown to affect metabolic enzyme activity in C. reinhardtii on multiple levels: transcriptional regulation, chloroplast RNA degradation, translational regulation, and thioredoxin-mediated enzyme regulation. Through application of our light model and prism reactions, we were able to closely recapitulate experimental growth measurements under solar, incandescent, and red LED lights. Through unbiased sampling, we were able to establish the tremendous statistical significance of the accuracy of growth predictions achievable through implementation of prism reactions. Finally, application of the photosynthetic model was demonstrated prospectively to evaluate light utilization efficiency under different light sources. The results suggest that, of the existing light sources, red LEDs provide the greatest efficiency, about three times as efficient as sunlight. Extending this analysis, the model was applied to design a maximally efficient LED spectrum for algal growth. The result was a 677-nm peak LED spectrum with a total incident photon flux of 360 μE/m2/s, suggesting that for the simple objective of maximizing growth efficiency, LED technology has already reached an effective theoretical optimum.
In summary, the C. reinhardtii metabolic network iRC1080 that we have reconstructed offers insight into the basic biology of this species and may be employed prospectively for genetic engineering design and light source design relevant to algal biotechnology. iRC1080 was used to analyze lipid metabolism and generate novel hypotheses about the evolution of latent pathways. The predictive capacity of metabolic models developed from iRC1080 was demonstrated in simulating mutant phenotypes and in evaluation of light source efficiency. Our network provides a broad knowledgebase of the biochemistry and genomics underlying global metabolism of a photoautotroph, and our modeling approach for light-driven metabolism exemplifies how integration of largely unvisited data types, such as physicochemical environmental parameters, can expand the diversity of applications of metabolic networks.
Metabolic network reconstruction encompasses existing knowledge about an organism's metabolism and genome annotation, providing a platform for omics data analysis and phenotype prediction. The model alga Chlamydomonas reinhardtii is employed to study diverse biological processes from photosynthesis to phototaxis. Recent heightened interest in this species results from an international movement to develop algal biofuels. Integrating biological and optical data, we reconstructed a genome-scale metabolic network for this alga and devised a novel light-modeling approach that enables quantitative growth prediction for a given light source, resolving wavelength and photon flux. We experimentally verified transcripts accounted for in the network and physiologically validated model function through simulation and generation of new experimental growth data, providing high confidence in network contents and predictive applications. The network offers insight into algal metabolism and potential for genetic engineering and efficient light source design, a pioneering resource for studying light-driven metabolism and quantitative systems biology.
doi:10.1038/msb.2011.52
PMCID: PMC3202792  PMID: 21811229
Chlamydomonas reinhardtii; lipid metabolism; metabolic engineering; photobioreactor
13.  Genome Sequencing Reveals Loci under Artificial Selection that Underlie Disease Phenotypes in the Laboratory Rat 
Cell  2013;154(3):691-703.
Summary
Large numbers of inbred laboratory rat strains have been developed for a range of complex disease phenotypes. To gain insights into the evolutionary pressures underlying selection for these phenotypes, we sequenced the genomes of 27 rat strains, including 11 models of hypertension, diabetes, and insulin resistance, along with their respective control strains. Altogether, we identified more than 13 million single-nucleotide variants, indels, and structural variants across these rat strains. Analysis of strain-specific selective sweeps and gene clusters implicated genes and pathways involved in cation transport, angiotensin production, and regulators of oxidative stress in the development of cardiovascular disease phenotypes in rats. Many of the rat loci that we identified overlap with previously mapped loci for related traits in humans, indicating the presence of shared pathways underlying these phenotypes in rats and humans. These data represent a step change in resources available for evolutionary analysis of complex traits in disease models.
PaperClip
Graphical Abstract
Highlights
•Genomes of 27 rat strains were sequenced; >13 million sequence variants identified•Selective sweeps and coevolved gene clusters were detected in 11 disease models•Previously identified and new disease genes and pathways were identified•This is first evolutionary analysis of artificial selection for disease phenotypes
Evolution analysis of artificial selection for disease phenotypes, such as hypertension and diabetes, in 27 rat strains reveals disease-related variants and loci.
doi:10.1016/j.cell.2013.06.040
PMCID: PMC3732391  PMID: 23890820
14.  Disease pathways at the Rat Genome Database Pathway Portal: genes in context—a network approach to understanding the molecular mechanisms of disease 
Human Genomics  2014;8(1):17.
Background
Biological systems are exquisitely poised to respond and adjust to challenges, including damage. However, sustained damage can overcome the ability of the system to adjust and result in a disease phenotype, its underpinnings many times elusive. Unraveling the molecular mechanisms of systems biology, of how and why it falters, is essential for delineating the details of the path(s) leading to the diseased state and for designing strategies to revert its progression. An important aspect of this process is not only to define the function of a gene but to identify the context within which gene functions act. It is within the network, or pathway context, that the function of a gene fulfills its ultimate biological role. Resolving the extent to which defective function(s) affect the proceedings of pathway(s) and how altered pathways merge into overpowering the system’s defense machinery are key to understanding the molecular aspects of disease and envisioning ways to counteract it. A network-centric approach to diseases is increasingly being considered in current research. It also underlies the deployment of disease pathways at the Rat Genome Database Pathway Portal. The portal is presented with an emphasis on disease and altered pathways, associated drug pathways, pathway suites, and suite networks.
Results
The Pathway Portal at the Rat Genome Database (RGD) provides an ever-increasing collection of interactive pathway diagrams and associated annotations for metabolic, signaling, regulatory, and drug pathways, including disease and altered pathways. A disease pathway is viewed from the perspective of networks whose alterations are manifested in the affected phenotype. The Pathway Ontology (PW), built and maintained at RGD, facilitates the annotations of genes, the deployment of pathway diagrams, and provides an overall navigational tool. Pathways that revolve around a common concept and are globally connected are presented within pathway suites; a suite network combines two or more pathway suites.
Conclusions
The Pathway Portal is a rich resource that offers a range of pathway data and visualization, including disease pathways and related pathway suites. Viewing a disease pathway from the perspective of underlying altered pathways is an aid for dissecting the molecular mechanisms of disease.
doi:10.1186/s40246-014-0017-8
PMCID: PMC4191248  PMID: 25265995
Molecular pathway; Disease pathway; Altered pathway; Ontology; Systems biology
15.  Production of p53 gene knockout rats by homologous recombination in embryonic stem cells 
Nature  2010;467(7312):211-213.
The use of homologous recombination to modify genes in embryonic stem (ES) cells provides a powerful means to elucidate gene function and create disease models1. Application of this technology to engineer genes in rats has previously been impossible in the absence of germline competent ES cells in this species. We have recently established authentic rat ES cells2, 3. Here we report the generation of the first gene knockout rats using the ES cell-based gene targeting technology. We designed a targeting vector to disrupt the tumor suppressor gene p53 (also known as Tp53) in rat ES cells via homologous recombination. p53 gene-targeted rat ES cells can be routinely generated. Furthermore, the p53 gene-targeted mutation in the rat ES cell genome can transmit through the germline via ES cell-rat chimeras to create p53 gene knockout rats. The rat is the most widely used animal model other than humans in biological research4–7. The establishment of gene targeting technology in rat ES cells, in combination with advances in genomics and the vast amount of research data on physiology and pharmacology in this species, now provides a powerful new platform for the study of human disease.
doi:10.1038/nature09368
PMCID: PMC2937076  PMID: 20703227
16.  A Numerical Approach to Ion Channel Modelling Using Whole-Cell Voltage-Clamp Recordings and a Genetic Algorithm 
PLoS Computational Biology  2007;3(8):e169.
The activity of trans-membrane proteins such as ion channels is the essence of neuronal transmission. The currently most accurate method for determining ion channel kinetic mechanisms is single-channel recording and analysis. Yet, the limitations and complexities in interpreting single-channel recordings discourage many physiologists from using them. Here we show that a genetic search algorithm in combination with a gradient descent algorithm can be used to fit whole-cell voltage-clamp data to kinetic models with a high degree of accuracy. Previously, ion channel stimulation traces were analyzed one at a time, the results of these analyses being combined to produce a picture of channel kinetics. Here the entire set of traces from all stimulation protocols are analysed simultaneously. The algorithm was initially tested on simulated current traces produced by several Hodgkin-Huxley–like and Markov chain models of voltage-gated potassium and sodium channels. Currents were also produced by simulating levels of noise expected from actual patch recordings. Finally, the algorithm was used for finding the kinetic parameters of several voltage-gated sodium and potassium channels models by matching its results to data recorded from layer 5 pyramidal neurons of the rat cortex in the nucleated outside-out patch configuration. The minimization scheme gives electrophysiologists a tool for reproducing and simulating voltage-gated ion channel kinetics at the cellular level.
Author Summary
Voltage-gated ion channels affect neuronal integration of information. Some neurons express more than ten different types of voltage-gated ion channels, making information processing a highly convoluted process. Kinetic modelling of ion channels is an important method for unravelling the role of each channel type in neuronal function. However, the most commonly used analysis techniques suffer from shortcomings that limit the ability of researchers to rapidly produce physiologically relevant models of voltage-gated ion channels and of neuronal physiology. We show that conjugating a stochastic search algorithm with ionic currents measured using multiple voltage-clamp protocols enables the semi-automatic production of models of voltage-gated ion channels. Once fully automated, this approach may be used for high throughput analysis of voltage-gated currents. This in turn will greatly shorten the time required for building models of neuronal physiology to facilitate our understanding of neuronal behaviour.
doi:10.1371/journal.pcbi.0030169
PMCID: PMC1963494  PMID: 17784781
17.  Multiscale Modeling and Data Integration in the Virtual Physiological Rat Project 
Annals of Biomedical Engineering  2012;40(11):2365-2378.
It has become increasingly evident that the descriptions of many complex diseases are only possible by taking into account multiple influences at different physiological scales. To do this with computational models often requires the integration of several models that have overlapping scales (genes to molecules, molecules to cells, cells to tissues). The Virtual Physiological Rat (VPR) Project, a National Institute of General Medical Sciences (NIGMS) funded National Center of Systems Biology, is tasked with mechanistically describing several complex diseases and is therefore identifying methods to facilitate the process of model integration across physiological scales. In addition, the VPR has a considerable experimental component and the resultant data must be integrated into these composite multiscale models and made available to the research community. A perspective of the current state of the art in model integration and sharing along with archiving of experimental data will be presented here in the context of multiscale physiological models. It was found that current ontological, model and data repository resources and integrative software tools are sufficient to create composite models from separate existing models and the example composite model developed here exhibits emergent behavior not predicted by the separate models.
doi:10.1007/s10439-012-0611-7
PMCID: PMC3463790  PMID: 22805979
Semantic annotation; Model merging; Model repositories; Biomedical ontologies; Data dissemination; Model sharing; Mechanistic physiological models; Virtual Physiological Rat
18.  Liver Dysfunction and Phosphatidylinositol-3-Kinase Signalling in Early Sepsis: Experimental Studies in Rodent Models of Peritonitis 
PLoS Medicine  2012;9(11):e1001338.
Experimental studies in a rat model of fecal peritonitis conducted by Michael Bauer and colleagues show that in this model, changes in liver function occur early in the development of sepsis, with potential implications for prognosis and development of new therapeutic approaches.
Background
Hepatic dysfunction and jaundice are traditionally viewed as late features of sepsis and portend poor outcomes. We hypothesized that changes in liver function occur early in the onset of sepsis, yet pass undetected by standard laboratory tests.
Methods and Findings
In a long-term rat model of faecal peritonitis, biotransformation and hepatobiliary transport were impaired, depending on subsequent disease severity, as early as 6 h after peritoneal contamination. Phosphatidylinositol-3-kinase (PI3K) signalling was simultaneously induced at this time point. At 15 h there was hepatocellular accumulation of bilirubin, bile acids, and xenobiotics, with disturbed bile acid conjugation and drug metabolism. Cholestasis was preceded by disruption of the bile acid and organic anion transport machinery at the canalicular pole. Inhibitors of PI3K partially prevented cytokine-induced loss of villi in cultured HepG2 cells. Notably, mice lacking the PI3Kγ gene were protected against cholestasis and impaired bile acid conjugation. This was partially confirmed by an increase in plasma bile acids (e.g., chenodeoxycholic acid [CDCA] and taurodeoxycholic acid [TDCA]) observed in 48 patients on the day severe sepsis was diagnosed; unlike bilirubin (area under the receiver-operating curve: 0.59), these bile acids predicted 28-d mortality with high sensitivity and specificity (area under the receiver-operating curve: CDCA: 0.77; TDCA: 0.72; CDCA+TDCA: 0.87).
Conclusions
Liver dysfunction is an early and commonplace event in the rat model of sepsis studied here; PI3K signalling seems to play a crucial role. All aspects of hepatic biotransformation are affected, with severity relating to subsequent prognosis. Detected changes significantly precede conventional markers and are reflected by early alterations in plasma bile acids. These observations carry important implications for the diagnosis of liver dysfunction and pharmacotherapy in the critically ill. Further clinical work is necessary to extend these concepts into clinical practice.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Sepsis (blood poisoning)—a life-threatening condition caused by an inappropriate immune response to an infection—is a major global cause of death. Normally, when bacteria or other microbes enter the human body, the immune system efficiently destroys the invaders. In sepsis the immune system goes into overdrive, and the chemicals it releases into the blood to combat the infection trigger widespread inflammation (swelling). This leads to the formation of small blood clots and leaky blood vessels that block the flow of blood to vital organs such as the kidneys and liver. In the most severe cases, multiple organs fail and the patient dies. Anyone can get sepsis, but people with weakened immune systems, the very young, and the elderly are most vulnerable. Symptoms of sepsis include fever, chills, rapid breathing, a fast heart rate, and confusion. In its early stages, sepsis can be treated with antibiotics alone, but people with severe sepsis need to be admitted to an intensive care unit where the vital organs can be supported while the infection is treated.
Why Was This Study Done?
Thirty to fifty percent of people who develop severe sepsis die. If sepsis could be diagnosed in its early stages, it might be possible to save more people. Unfortunately, the symptoms of sepsis mimic those of other conditions, and, because sepsis tends to develop very quickly, it is often not diagnosed until it is too late to save the patient's life. The development of liver (hepatic) dysfunction and jaundice are both regarded as late features of sepsis (jaundice is yellowing of the skin and eyes caused by a build-up of bilirubin in the blood). However, the researchers hypothesized that changes in liver function occur early in sepsis and could, therefore, be used to improve the diagnosis and management of sepsis.
What Did the Researchers Do and Find?
The researchers induced sepsis in rats by injecting bacteria into the peritoneal cavity (the gap between the abdominal wall and the abdominal organs), separated the infected animals into predicted survivors and non-survivors based on their heart stroke volume measured using cardiac ultrasound, and then examined their liver function. The expression of genes encoding proteins involved in “biotransformation” and “hepatobiliary transport” (the processes that convert waste products and toxic chemicals into substances that can be conjugated to increase solubility and then excreted) was down-regulated within six hours of sepsis induction in the predicted non-survivors compared to the predicted survivors. Functional changes such as bilirubin and bile acid accumulation in the liver (cholestasis), poor excretion of xenobiotics (molecules not usually found in the body such as antibiotics), and disturbed bile acid conjugation were also seen in predicted non-survivors but not in survivors. Moreover, phosphatidylinositol-3-kinase (PI3K) signaling (which is involved in several immune processes) increased soon after sepsis induction in non-survivor but not in survivor animals. Notably, mice lacking the PI3Kγ gene did not develop cholestasis or show impaired bile acid conjugation after induction of sepsis. Finally, in human patients, plasma bile acids were increased in 48 patients on the day that severe sepsis was diagnosed, and these increases accurately predicted death in these patients.
What Do These Findings Mean?
These findings show that liver dysfunction is an early event in animal models of sepsis and that PI3K signalling plays a crucial role in the development of liver dysfunction. They show that all aspects of liver biotransformation are affected during sepsis and suggest that outcomes are related to the severity of these changes. The limited clinical data included in this study also support the hypothesis that changes in liver function occur early in sepsis, although these data need confirming and extending. Taken together, these findings suggest that liver function tests might aid early diagnosis of sepsis and might also provide information about likely outcomes. They also have important implications for the use of drugs in patients who are critically ill with sepsis, in that some of the drugs routinely administered to such patients may not be adequately detoxified and may, therefore, contribute to organ injury. Finally, these findings suggest that inhibition of PI3Kγ may alleviate sepsis-associated cholestasis.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001338.
This study is further discussed in a PLOS Medicine Perspective by John Marshall
The US National Institute of General Medical Sciences has a fact sheet on sepsis
The UK National Health Service Choices website has information about sepsis and about jaundice
The Surviving Sepsis Campaign, which was developed to improve the management, diagnosis, and treatment of sepsis, provides basic information about sepsis
The Sepsis Alliance, a US not-for-profit organization, also provides information about sepsis for patients and their families, including personal stories about sepsis
The not-for profit UK Sepsis Trust is another useful source of information about sepsis that includes patient stories
MedlinePlus provides links to additional resources about sepsis and jaundice (in English and Spanish)
doi:10.1371/journal.pmed.1001338
PMCID: PMC3496669  PMID: 23152722
19.  INMEX—a web-based tool for integrative meta-analysis of expression data 
Nucleic Acids Research  2013;41(Web Server issue):W63-W70.
The widespread applications of various ‘omics’ technologies in biomedical research together with the emergence of public data repositories have resulted in a plethora of data sets for almost any given physiological state or disease condition. Properly combining or integrating these data sets with similar basic hypotheses can help reduce study bias, increase statistical power and improve overall biological understanding. However, the difficulties in data management and the complexities of analytical approaches have significantly limited data integration to enable meta-analysis. Here, we introduce integrative meta-analysis of expression data (INMEX), a user-friendly web-based tool designed to support meta-analysis of multiple gene-expression data sets, as well as to enable integration of data sets from gene expression and metabolomics experiments. INMEX contains three functional modules. The data preparation module supports flexible data processing, annotation and visualization of individual data sets. The statistical analysis module allows researchers to combine multiple data sets based on P-values, effect sizes, rank orders and other features. The significant genes can be examined in functional analysis module for enriched Gene Ontology terms or Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, or expression profile visualization. INMEX has built-in support for common gene/metabolite identifiers (IDs), as well as 45 popular microarray platforms for human, mouse and rat. Complex operations are performed through a user-friendly web interface in a step-by-step manner. INMEX is freely available at http://www.inmex.ca.
doi:10.1093/nar/gkt338
PMCID: PMC3692077  PMID: 23766290
20.  e-Health, m-Health and healthier social media reform: the big scale view 
Introduction
In the upcoming decade, digital platforms will be the backbone of a strategic revolution in the way medical services are provided, affecting both healthcare providers and patients. Digital-based patient-centered healthcare services allow patients to actively participate in managing their own care, in times of health as well as illness, using personally tailored interactive tools. Such empowerment is expected to increase patients’ willingness to adopt actions and lifestyles that promote health as well as improve follow-up and compliance with treatment in cases of chronic illness. Clalit Health Services (CHS) is the largest HMO in Israel and second largest world-wide. Through its 14 hospitals, 1300 primary and specialized clinics, and 650 pharmacies, CHS provides comprehensive medical care to the majority of Israel’s population (above 4 million members). CHS e-Health wing focuses on deepening patient involvement in managing health, through personalized digital interactive tools. Currently, CHS e-Health wing provides e-health services for 1.56 million unique patients monthly with 2.4 million interactions every month (August 2011). Successful implementation of e-Health solutions is not a sum of technology, innovation and health; rather it’s the expertise of tailoring knowledge and leadership capabilities in multidisciplinary areas: clinical, ethical, psychological, legal, comprehension of patient and medical team engagement etc. The Google Health case excellently demonstrates this point. On the other hand, our success with CHS is a demonstration that e-Health can be enrolled effectively and fast with huge benefits for both patients and medical teams, and with a robust business model.
CHS e-Health core components
They include:
1. The personal health record layer (what the patient can see) presents patients with their own medical history as well as the medical history of their preadult children, including diagnoses, allergies, vaccinations, laboratory results with interpretations in layman’s terms, medications with clear, straightforward explanations regarding dosing instructions, important side effects, contraindications, such as lactation etc., and other important medical information. All personal e-Health services require identification and authorization.
2. The personal knowledge layer (what the patient should know) presents patients with personally tailored recommendations for preventative medicine and health promotion. For example, diabetic patients are push notified regarding their yearly eye exam. The various health recommendations include: occult blood testing, mammography, lipid profile etc. Each recommendation contains textual, visual and interactive content components in order to promote engagement and motivate the patient to actually change his health behaviour.
3. The personal health services layer (what the patient can do) enables patients to schedule clinic visits, order chronic prescriptions, e-consult their physician via secured e-mail, set SMS medication reminders, e-consult a pharmacist regarding personal medications. Consultants’ answers are sent securely to the patients’ personal mobile device.
On December 2009 CHS launched secured, web based, synchronous medical consultation via video conference. Currently 11,780 e-visits are performed monthly (May 2011). The medical encounter includes e-prescription and referral capabilities which are biometrically signed by the physician. On December 2010 CHS launched a unique mobile health platform, which is one of the most comprehensive personal m-Health applications world-wide. An essential advantage of mobile devices is their potential to bridge the digital divide. Currently, CHS m-Health platform is used by more than 45,000 unique users, with 75,000 laboratory results views/month, 1100 m-consultations/month and 9000 physician visit scheduling/month.
4. The Bio-Sensing layer (what physiological data the patient can populate) includes diagnostic means that allow remote physical examination, bio-sensors that broadcast various physiological measurements, and smart homecare devices, such as e-Pill boxes that gives seniors, patients and their caregivers the ability to stay at home and live life to its fullest. Monitored data is automatically transmitted to the patient’s Personal Health Record and to relevant medical personnel.
The monitoring layer is embedded in the chronic disease management platform, and in the interactive health promotion and wellness platform. It includes tailoring of consumer-oriented medical devices and service provided by various professional personnel—physicians, nurses, pharmacists, dieticians and more.
5. The Social layer (what the patient can share). Social media networks triggered an essential change at the humanity ‘genome’ level, yet to be further defined in the upcoming years. Social media has huge potential in promoting health as it combines fun, simple yet extraordinary user experience, and bio-social-feedback. There are two major challenges in leveraging health care through social networks:
a. Our personal health information is the cornerstone for personalizing healthier lifestyle, disease management and preventative medicine. We naturally see our personal health data as a super-private territory. So, how do we bring the power of our private health information, currently locked within our Personal Health Record, into social media networks without offending basic privacy issues?
b. Disease management and preventive medicine are currently neither considered ‘cool’ nor ‘fun’ or ‘potentially highly viral’ activities; yet, health is a major issue of everybody’s life. It seems like we are missing a crucial element with a huge potential in health behavioural change—the Fun Theory. Social media platforms comprehends user experience tools that potentially could break current misconception, and engage people in the daily task of taking better care of themselves.
CHS e-Health innovation team characterized several break-through applications in this unexplored territory within social media networks, fusing personal health and social media platforms without offending privacy. One of the most crucial issues regarding adoption of e-health and m-health platforms is change management. Being a ‘hot’ innovative ‘gadget’ is far from sufficient for changing health behaviours at the individual and population levels.
CHS health behaviour change management methodology includes 4 core elements:
1. Engaging two completely different populations: patients, and medical teams. e-Health applications must present true added value for both medical teams and patients, engaging them through understanding and assimilating “what’s really in it for me”. Medical teams are further subdivided into physicians, nurses, pharmacists and administrative personnel—each with their own driving incentive. Resistance to change is an obstacle in many fields but it is particularly true in the conservative health industry. To successfully manage a large scale persuasive process, we treat intra-organizational human resources as “Change Agents”. Harnessing the persuasive power of ~40,000 employees requires engaging them as the primary target group. Successful recruitment has the potential of converting each patient-medical team interaction into an exposure opportunity to the new era of participatory medicine via e-health and m-health channels.
2. Implementation waves: every group of digital health products that are released at the same time are seen as one project. Each implementation wave leverages the focus of the organization and target populations to a defined time span. There are three major and three minor implementation waves a year.
3. Change-Support Arrow: a structured infrastructure for every implementation wave. The sub-stages in this strategy include:
Cross organizational mapping and identification of early adopters and stakeholders relevant to the implementation wave
Mapping positive or negative perceptions and designing specific marketing approaches for the distinct target groups
Intra and extra organizational marketing
Conducting intensive training and presentation sessions for groups of implementers
Running conflict-prevention activities, such as advanced tackling of potential union resistance
Training change-agents with resistance-management behavioural techniques, focused intervention for specific incidents and for key opinion leaders
Extensive presence in the clinics during the launch period, etc.
The entire process is monitored and managed continuously by a review team.
4. Closing Phase: each wave is analyzed and a “lessons-learned” session concludes the changes required in the modus operandi of the e-health project team.
PMCID: PMC3571141
e-Health; mobile health; personal health record; online visit; patient empowerment; knowledge prescription
21.  Threats to Validity in the Design and Conduct of Preclinical Efficacy Studies: A Systematic Review of Guidelines for In Vivo Animal Experiments 
PLoS Medicine  2013;10(7):e1001489.
Background
The vast majority of medical interventions introduced into clinical development prove unsafe or ineffective. One prominent explanation for the dismal success rate is flawed preclinical research. We conducted a systematic review of preclinical research guidelines and organized recommendations according to the type of validity threat (internal, construct, or external) or programmatic research activity they primarily address.
Methods and Findings
We searched MEDLINE, Google Scholar, Google, and the EQUATOR Network website for all preclinical guideline documents published up to April 9, 2013 that addressed the design and conduct of in vivo animal experiments aimed at supporting clinical translation. To be eligible, documents had to provide guidance on the design or execution of preclinical animal experiments and represent the aggregated consensus of four or more investigators. Data from included guidelines were independently extracted by two individuals for discrete recommendations on the design and implementation of preclinical efficacy studies. These recommendations were then organized according to the type of validity threat they addressed. A total of 2,029 citations were identified through our search strategy. From these, we identified 26 guidelines that met our eligibility criteria—most of which were directed at neurological or cerebrovascular drug development. Together, these guidelines offered 55 different recommendations. Some of the most common recommendations included performance of a power calculation to determine sample size, randomized treatment allocation, and characterization of disease phenotype in the animal model prior to experimentation.
Conclusions
By identifying the most recurrent recommendations among preclinical guidelines, we provide a starting point for developing preclinical guidelines in other disease domains. We also provide a basis for the study and evaluation of preclinical research practice.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
The development process for new drugs is lengthy and complex. It begins in the laboratory, where scientists investigate the causes of diseases and identify potential new treatments. Next, promising interventions undergo preclinical research in cells and in animals (in vivo animal experiments) to test whether the intervention has the expected effect and to support the generalization (extension) of this treatment–effect relationship to patients. Drugs that pass these tests then enter clinical trials, where their safety and efficacy is tested in selected groups of patients under strictly controlled conditions. Finally, the government bodies responsible for drug approval review the results of the clinical trials, and successful drugs receive a marketing license, usually a decade or more after the initial laboratory work. Notably, only 11% of agents that enter clinical testing (investigational drugs) are ultimately licensed.
Why Was This Study Done?
The frequent failure of investigational drugs during clinical translation is potentially harmful to trial participants. Moreover, the costs of these failures are passed onto healthcare systems in the form of higher drug prices. It would be good, therefore, to reduce the attrition rate of investigational drugs. One possible explanation for the dismal success rate of clinical translation is that preclinical research, the key resource for justifying clinical development, is flawed. To address this possibility, several groups of preclinical researchers have issued guidelines intended to improve the design and execution of in vivo animal studies. In this systematic review (a study that uses predefined criteria to identify all the research on a given topic), the authors identify the experimental practices that are commonly recommended in these guidelines and organize these recommendations according to the type of threat to validity (internal, construct, or external) that they address. Internal threats to validity are factors that confound reliable inferences about treatment–effect relationships in preclinical research. For example, experimenter expectation may bias outcome assessment. Construct threats to validity arise when researchers mischaracterize the relationship between an experimental system and the clinical disease it is intended to represent. For example, researchers may use an animal model for a complex multifaceted clinical disease that only includes one characteristic of the disease. External threats to validity are unseen factors that frustrate the transfer of treatment–effect relationships from animal models to patients.
What Did the Researchers Do and Find?
The researchers identified 26 preclinical guidelines that met their predefined eligibility criteria. Twelve guidelines addressed preclinical research for neurological and cerebrovascular drug development; other disorders covered by guidelines included cardiac and circulatory disorders, sepsis, pain, and arthritis. Together, the guidelines offered 55 different recommendations for the design and execution of preclinical in vivo animal studies. Nineteen recommendations addressed threats to internal validity. The most commonly included recommendations of this type called for the use of power calculations to ensure that sample sizes are large enough to yield statistically meaningful results, random allocation of animals to treatment groups, and “blinding” of researchers who assess outcomes to treatment allocation. Among the 25 recommendations that addressed threats to construct validity, the most commonly included recommendations called for characterization of the properties of the animal model before experimentation and matching of the animal model to the human manifestation of the disease. Finally, six recommendations addressed threats to external validity. The most commonly included of these recommendations suggested that preclinical research should be replicated in different models of the same disease and in different species, and should also be replicated independently.
What Do These Findings Mean?
This systematic review identifies a range of investigational recommendations that preclinical researchers believe address threats to the validity of preclinical efficacy studies. Many of these recommendations are not widely implemented in preclinical research at present. Whether the failure to implement them explains the frequent discordance between the results on drug safety and efficacy obtained in preclinical research and in clinical trials is currently unclear. These findings provide a starting point, however, for the improvement of existing preclinical research guidelines for specific diseases, and for the development of similar guidelines for other diseases. They also provide an evidence-based platform for the analysis of preclinical evidence and for the study and evaluation of preclinical research practice. These findings should, therefore, be considered by investigators, institutional review bodies, journals, and funding agents when designing, evaluating, and sponsoring translational research.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001489.
The US Food and Drug Administration provides information about drug approval in the US for consumers and for health professionals; its Patient Network provides a step-by-step description of the drug development process that includes information on preclinical research
The UK Medicines and Healthcare Products Regulatory Agency (MHRA) provides information about all aspects of the scientific evaluation and approval of new medicines in the UK; its My Medicine: From Laboratory to Pharmacy Shelf web pages describe the drug development process from scientific discovery, through preclinical and clinical research, to licensing and ongoing monitoring
The STREAM website provides ongoing information about policy, ethics, and practices used in clinical translation of new drugs
The CAMARADES collaboration offers a “supporting framework for groups involved in the systematic review of animal studies” in stroke and other neurological diseases
doi:10.1371/journal.pmed.1001489
PMCID: PMC3720257  PMID: 23935460
22.  PhenUMA: a tool for integrating the biomedical relationships among genes and diseases 
BMC Bioinformatics  2014;15(1):375.
Background
Several types of genetic interactions in humans can be directly or indirectly associated with the causal effects of mutations. These interactions are usually based on their co-associations to biological processes, coexistence in cellular locations, coexpression in cell lines, physical interactions and so on. In addition, pathological processes can present similar phenotypes that have mutations either in the same genomic location or in different genomic regions. Therefore, integrative resources for all of these complex interactions can help us prioritize the relationships between genes and diseases that are most deserving to be studied by researchers and physicians.
Results
PhenUMA is a web application that displays biological networks using information from biomedical and biomolecular data repositories. One of its most innovative features is to combine the benefits of semantic similarity methods with the information taken from databases of genetic diseases and biological interactions. More specifically, this tool is useful in studying novel pathological relationships between functionally related genes, merging diseases into clusters that share specific phenotypes or finding diseases related to reported phenotypes.
Conclusions
This framework builds, analyzes and visualizes networks based on both functional and phenotypic relationships. The integration of this information helps in the discovery of alternative pathological roles of genes, biological functions and diseases. PhenUMA represents an advancement toward the use of new technologies for genomics and personalized medicine.
Electronic supplementary material
The online version of this article (doi:10.1186/s12859-014-0375-1) contains supplementary material, which is available to authorized users.
doi:10.1186/s12859-014-0375-1
PMCID: PMC4260198  PMID: 25420641
Functional relationships; Phenotypic relationships; Gene-disease relationships; Systems biology; Network medicine; Network biology
23.  A Risk Prediction Model for the Assessment and Triage of Women with Hypertensive Disorders of Pregnancy in Low-Resourced Settings: The miniPIERS (Pre-eclampsia Integrated Estimate of RiSk) Multi-country Prospective Cohort Study 
PLoS Medicine  2014;11(1):e1001589.
Beth Payne and colleagues use a risk prediction model, the Pre-eclampsia Integrated Estimate of RiSk (miniPIERS) to help inform the clinical assessment and triage of women with hypertensive disorders of pregnancy in low-resourced settings.
Please see later in the article for the Editors' Summary
Background
Pre-eclampsia/eclampsia are leading causes of maternal mortality and morbidity, particularly in low- and middle- income countries (LMICs). We developed the miniPIERS risk prediction model to provide a simple, evidence-based tool to identify pregnant women in LMICs at increased risk of death or major hypertensive-related complications.
Methods and Findings
From 1 July 2008 to 31 March 2012, in five LMICs, data were collected prospectively on 2,081 women with any hypertensive disorder of pregnancy admitted to a participating centre. Candidate predictors collected within 24 hours of admission were entered into a step-wise backward elimination logistic regression model to predict a composite adverse maternal outcome within 48 hours of admission. Model internal validation was accomplished by bootstrapping and external validation was completed using data from 1,300 women in the Pre-eclampsia Integrated Estimate of RiSk (fullPIERS) dataset. Predictive performance was assessed for calibration, discrimination, and stratification capacity. The final miniPIERS model included: parity (nulliparous versus multiparous); gestational age on admission; headache/visual disturbances; chest pain/dyspnoea; vaginal bleeding with abdominal pain; systolic blood pressure; and dipstick proteinuria. The miniPIERS model was well-calibrated and had an area under the receiver operating characteristic curve (AUC ROC) of 0.768 (95% CI 0.735–0.801) with an average optimism of 0.037. External validation AUC ROC was 0.713 (95% CI 0.658–0.768). A predicted probability ≥25% to define a positive test classified women with 85.5% accuracy. Limitations of this study include the composite outcome and the broad inclusion criteria of any hypertensive disorder of pregnancy. This broad approach was used to optimize model generalizability.
Conclusions
The miniPIERS model shows reasonable ability to identify women at increased risk of adverse maternal outcomes associated with the hypertensive disorders of pregnancy. It could be used in LMICs to identify women who would benefit most from interventions such as magnesium sulphate, antihypertensives, or transportation to a higher level of care.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Each year, ten million women develop pre-eclampsia or a related hypertensive (high blood pressure) disorder of pregnancy and 76,000 women die as a result. Globally, hypertensive disorders of pregnancy cause around 12% of maternal deaths—deaths of women during or shortly after pregnancy. The mildest of these disorders is gestational hypertension, high blood pressure that develops after 20 weeks of pregnancy. Gestational hypertension does not usually harm the mother or her unborn child and resolves after delivery but up to a quarter of women with this condition develop pre-eclampsia, a combination of hypertension and protein in the urine (proteinuria). Women with mild pre-eclampsia may not have any symptoms—the condition is detected during antenatal checks—but more severe pre-eclampsia can cause headaches, blurred vision, and other symptoms, and can lead to eclampsia (fits), multiple organ failure, and death of the mother and/or her baby. The only “cure” for pre-eclampsia is to deliver the baby as soon as possible but women are sometimes given antihypertensive drugs to lower their blood pressure or magnesium sulfate to prevent seizures.
Why Was This Study Done?
Women in low- and middle-income countries (LMICs) are more likely to develop complications of pre-eclampsia than women in high-income countries and most of the deaths associated with hypertensive disorders of pregnancy occur in LMICs. The high burden of illness and death in LMICs is thought to be primarily due to delays in triage (the identification of women who are or may become severely ill and who need specialist care) and delays in transporting these women to facilities where they can receive appropriate care. Because there is a shortage of health care workers who are adequately trained in the triage of suspected cases of hypertensive disorders of pregnancy in many LMICs, one way to improve the situation might be to design a simple tool to identify women at increased risk of complications or death from hypertensive disorders of pregnancy. Here, the researchers develop miniPIERS (Pre-eclampsia Integrated Estimate of RiSk), a clinical risk prediction model for adverse outcomes among women with hypertensive disorders of pregnancy suitable for use in community and primary health care facilities in LMICs.
What Did the Researchers Do and Find?
The researchers used data on candidate predictors of outcome that are easy to collect and/or measure in all health care settings and that are associated with pre-eclampsia from women admitted with any hypertensive disorder of pregnancy to participating centers in five LMICs to build a model to predict death or a serious complication such as organ damage within 48 hours of admission. The miniPIERS model included parity (whether the woman had been pregnant before), gestational age (length of pregnancy), headache/visual disturbances, chest pain/shortness of breath, vaginal bleeding with abdominal pain, systolic blood pressure, and proteinuria detected using a dipstick. The model was well-calibrated (the predicted risk of adverse outcomes agreed with the observed risk of adverse outcomes among the study participants), it had a good discriminatory ability (it could separate women who had a an adverse outcome from those who did not), and it designated women as being at high risk (25% or greater probability of an adverse outcome) with an accuracy of 85.5%. Importantly, external validation using data collected in fullPIERS, a study that developed a more complex clinical prediction model based on data from women attending tertiary hospitals in high-income countries, confirmed the predictive performance of miniPIERS.
What Do These Findings Mean?
These findings indicate that the miniPIERS model performs reasonably well as a tool to identify women at increased risk of adverse maternal outcomes associated with hypertensive disorders of pregnancy. Because miniPIERS only includes simple-to-measure personal characteristics, symptoms, and signs, it could potentially be used in resource-constrained settings to identify the women who would benefit most from interventions such as transportation to a higher level of care. However, further external validation of miniPIERS is needed using data collected from women living in LMICs before the model can be used during routine antenatal care. Moreover, the value of miniPIERS needs to be confirmed in implementation projects that examine whether its potential translates into clinical improvements. For now, though, the model could provide the basis for an education program to increase the knowledge of women, families, and community health care workers in LMICs about the signs and symptoms of hypertensive disorders of pregnancy.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001589.
The World Health Organization provides guidelines for the management of hypertensive disorders of pregnancy in low-resourced settings
The Maternal and Child Health Integrated Program provides information on pre-eclampsia and eclampsia targeted to low-resourced settings along with a tool-kit for LMIC providers
The US National Heart, Lung, and Blood Institute provides information about high blood pressure in pregnancy and a guide to lowering blood pressure in pregnancy
The UK National Health Service Choices website provides information about pre-eclampsia
The US not-for profit organization Preeclampsia Foundation provides information about all aspects of pre-eclampsia; its website includes some personal stories
The UK charity Healthtalkonline also provides personal stories about hypertensive disorders of pregnancy
MedlinePlus provides links to further information about high blood pressure and pregnancy (in English and Spanish); the MedlinePlus Encyclopedia has a video about pre-eclampsia (also in English and Spanish)
More information about miniPIERS and about fullPIERS is available
doi:10.1371/journal.pmed.1001589
PMCID: PMC3897359  PMID: 24465185
24.  PAGED: a pathway and gene-set enrichment database to enable molecular phenotype discoveries 
BMC Bioinformatics  2012;13(Suppl 15):S2.
Background
Over the past decade, pathway and gene-set enrichment analysis has evolved into the study of high-throughput functional genomics. Owing to poorly annotated and incomplete pathway data, researchers have begun to combine pathway and gene-set enrichment analysis as well as network module-based approaches to identify crucial relationships between different molecular mechanisms.
Methods
To meet the new challenge of molecular phenotype discovery, in this work, we have developed an integrated online database, the Pathway And Gene Enrichment Database (PAGED), to enable comprehensive searches for disease-specific pathways, gene signatures, microRNA targets, and network modules by integrating gene-set-based prior knowledge as molecular patterns from multiple levels: the genome, transcriptome, post-transcriptome, and proteome.
Results
The online database we developed, PAGED http://bio.informatics.iupui.edu/PAGED is by far the most comprehensive public compilation of gene sets. In its current release, PAGED contains a total of 25,242 gene sets, 61,413 genes, 20 organisms, and 1,275,560 records from five major categories. Beyond its size, the advantage of PAGED lies in the explorations of relationships between gene sets as gene-set association networks (GSANs). Using colorectal cancer expression data analysis as a case study, we demonstrate how to query this database resource to discover crucial pathways, gene signatures, and gene network modules specific to colorectal cancer functional genomics.
Conclusions
This integrated online database lays a foundation for developing tools beyond third-generation pathway analysis approaches on for discovering molecular phenotypes, especially for disease-associated pathway/gene-set enrichment analysis.
doi:10.1186/1471-2105-13-S15-S2
PMCID: PMC3439733  PMID: 23046413
25.  What everybody should know about the Rat Genome and its online resources 
Nature genetics  2008;40(5):523-527.
It has been four years since the rat genome’s original publication. Five groups are working together to assemble, annotate and release the next version of the genome for this key model system. As the prevailing model for physiology, complex disease and pharmacological studies, there is an acute need for the rat’s genomic resources to keep pace with the rat’s prominence in the laboratory. In this commentary we describe the current status of the rat genome sequence and the plans for its impending ‘upgrade’. We then cover the key online resources providing access to the rat genome, including the new SNP views at Ensembl, NCBI’s RefSeq and Genes databases, UCSC’s Genome Browser and RGD’s disease portals for cardiovascular disease and obesity.
doi:10.1038/ng0508-523
PMCID: PMC2505193  PMID: 18443589

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