This article describes a Digital Health Framework (DHF), benefitting from the lessons learnt during the three-year life span of the FP7 Synergy-COPD project. The DHF aims to embrace the emerging requirements - data and tools - of applying systems medicine into healthcare with a three-tier strategy articulating formal healthcare, informal care and biomedical research. Accordingly, it has been constructed based on three key building blocks, namely, novel integrated care services with the support of information and communication technologies, a personal health folder (PHF) and a biomedical research environment (DHF-research). Details on the functional requirements and necessary components of the DHF-research are extensively presented. Finally, the specifics of the building blocks strategy for deployment of the DHF, as well as the steps toward adoption are analyzed. The proposed architectural solutions and implementation steps constitute a pivotal strategy to foster and enable 4P medicine (Predictive, Preventive, Personalized and Participatory) in practice and should provide a head start to any community and institution currently considering to implement a biomedical research platform.
Biomedical Research; Chronic care; Clinical Decision Support Systems; Integrated Health Care Systems; Patient Decision Support Systems; Personal Health Folder
The article addresses the strategic role of workforce preparation in the process of adoption of Systems Medicine as a driver of biomedical research in the new health paradigm. It reports on relevant initiatives, like CASyM, fostering Systems Medicine at EU level. The chapter focuses on the BioHealth Computing Program as a reference for multidisciplinary training of future systems-oriented researchers describing the productive interactions with the Synergy-COPD project.
Biomedical Research; Education; Integrated Health Care Systems; Master; PhD; Professionals; Systems Medicine; Training
Background and hypothesis
Heterogeneity in clinical manifestations and disease progression in Chronic Obstructive Pulmonary Disease (COPD) lead to consequences for patient health risk assessment, stratification and management. Implicit with the classical "spill over" hypothesis is that COPD heterogeneity is driven by the pulmonary events of the disease. Alternatively, we hypothesized that COPD heterogeneities result from the interplay of mechanisms governing three conceptually different phenomena: 1) pulmonary disease, 2) systemic effects of COPD and 3) co-morbidity clustering, each of them with their own dynamics.
Objective and method
To explore the potential of a systems analysis of COPD heterogeneity focused on skeletal muscle dysfunction and on co-morbidity clustering aiming at generating predictive modeling with impact on patient management. To this end, strategies combining deterministic modeling and network medicine analyses of the Biobridge dataset were used to investigate the mechanisms of skeletal muscle dysfunction. An independent data driven analysis of co-morbidity clustering examining associated genes and pathways was performed using a large dataset (ICD9-CM data from Medicare, 13 million people). Finally, a targeted network analysis using the outcomes of the two approaches (skeletal muscle dysfunction and co-morbidity clustering) explored shared pathways between these phenomena.
(1) Evidence of abnormal regulation of skeletal muscle bioenergetics and skeletal muscle remodeling showing a significant association with nitroso-redox disequilibrium was observed in COPD; (2) COPD patients presented higher risk for co-morbidity clustering than non-COPD patients increasing with ageing; and, (3) the on-going targeted network analyses suggests shared pathways between skeletal muscle dysfunction and co-morbidity clustering.
The results indicate the high potential of a systems approach to address COPD heterogeneity. Significant knowledge gaps were identified that are relevant to shape strategies aiming at fostering 4P Medicine for patients with COPD.
Chronic diseases; COPD; Disease heterogeneity; Integrated Care; Predictive Medicine; Redox disequilibrium; Systems Medicine; VO2max
Background and hypothesis
Chronic Obstructive Pulmonary Disease (COPD) patients are characterized by heterogeneous clinical manifestations and patterns of disease progression. Two major factors that can be used to identify COPD subtypes are muscle dysfunction/wasting and co-morbidity patterns. We hypothesized that COPD heterogeneity is in part the result of complex interactions between several genes and pathways. We explored the possibility of using a Systems Medicine approach to identify such pathways, as well as to generate predictive computational models that may be used in clinic practice.
Objective and method
Our overarching goal is to generate clinically applicable predictive models that characterize COPD heterogeneity through a Systems Medicine approach. To this end we have developed a general framework, consisting of three steps/objectives: (1) feature identification, (2) model generation and statistical validation, and (3) application and validation of the predictive models in the clinical scenario. We used muscle dysfunction and co-morbidity as test cases for this framework.
In the study of muscle wasting we identified relevant features (genes) by a network analysis and generated predictive models that integrate mechanistic and probabilistic models. This allowed us to characterize muscle wasting as a general de-regulation of pathway interactions. In the co-morbidity analysis we identified relevant features (genes/pathways) by the integration of gene-disease and disease-disease associations. We further present a detailed characterization of co-morbidities in COPD patients that was implemented into a predictive model. In both use cases we were able to achieve predictive modeling but we also identified several key challenges, the most pressing being the validation and implementation into actual clinical practice.
The results confirm the potential of the Systems Medicine approach to study complex diseases and generate clinically relevant predictive models. Our study also highlights important obstacles and bottlenecks for such approaches (e.g. data availability and normalization of frameworks among others) and suggests specific proposals to overcome them.
Chronic diseases; COPD; Disease heterogeneity; Systems Medicine; Predictive Modeling; Co-morbidity
Previously we generated a chronic obstructive pulmonary disease (COPD) specific knowledge base (http://www.copdknowledgebase.eu) from clinical and experimental data, text-mining results and public databases. This knowledge base allowed the retrieval of specific molecular networks together with integrated clinical and experimental data.
The COPDKB has now been extended to integrate over 40 public data sources on functional interaction (e.g. signal transduction, transcriptional regulation, protein-protein interaction, gene-disease association). In addition we integrated COPD-specific expression and co-morbidity networks connecting over 6 000 genes/proteins with physiological parameters and disease states. Three mathematical models describing different aspects of systemic effects of COPD were connected to clinical and experimental data. We have completely redesigned the technical architecture of the user interface and now provide html and web browser-based access and form-based searches. A network search enables the use of interconnecting information and the generation of disease-specific sub-networks from general knowledge. Integration with the Synergy-COPD Simulation Environment enables multi-scale integrated simulation of individual computational models while integration with a Clinical Decision Support System allows delivery into clinical practice.
The COPD Knowledge Base is the only publicly available knowledge resource dedicated to COPD and combining genetic information with molecular, physiological and clinical data as well as mathematical modelling. Its integrated analysis functions provide overviews about clinical trends and connections while its semantically mapped content enables complex analysis approaches. We plan to further extend the COPDKB by offering it as a repository to publish and semantically integrate data from relevant clinical trials. The COPDKB is freely available after registration at http://www.copdknowledgebase.eu.
Today, many different tools are developed to execute and visualize physiological models that represent the human physiology. Most of these tools run models written in very specific programming languages which in turn simplify the communication among models. Nevertheless, not all of these tools are able to run models written in different programming languages. In addition, interoperability between such models remains an unresolved issue.
In this paper we present a simulation environment that allows, first, the execution of models developed in different programming languages and second the communication of parameters to interconnect these models. This simulation environment, developed within the Synergy-COPD project, aims at helping and supporting bio-researchers and medical students understand the internal mechanisms of the human body through the use of physiological models. This tool is composed of a graphical visualization environment, which is a web interface through which the user can interact with the models, and a simulation workflow management system composed of a control module and a data warehouse manager. The control module monitors the correct functioning of the whole system. The data warehouse manager is responsible for managing the stored information and supporting its flow among the different modules.
This simulation environment has been validated with the integration of three models: two deterministic, i.e. based on linear and differential equations, and one probabilistic, i.e., based on probability theory. These models have been selected based on the disease under study in this project, i.e., chronic obstructive pulmonary disease.
It has been proved that the simulation environment presented here allows the user to research and study the internal mechanisms of the human physiology by the use of models via a graphical visualization environment. A new tool for bio-researchers is ready for deployment in various use cases scenarios.
Simulation environment; deterministic model; probabilistic model; interoperability; knowledge base; data base; case
To integrate heterogeneous and large omics data constitutes not only a conceptual challenge but a practical hurdle in the daily analysis of omics data. With the rise of novel omics technologies and through large-scale consortia projects, biological systems are being further investigated at an unprecedented scale generating heterogeneous and often large data sets. These data-sets encourage researchers to develop novel data integration methodologies. In this introduction we review the definition and characterize current efforts on data integration in the life sciences. We have used a web-survey to assess current research projects on data-integration to tap into the views, needs and challenges as currently perceived by parts of the research community.
The Notch signaling pathway is instrumental for cell fate decisions. Signals from the Notch receptor are transduced by CSL-type DNA-binding proteins. In Drosophila, this protein is named Suppressor of Hairless [Su(H)]. Together with the intracellular domain of the activated Notch receptor ICN, Su(H) assembles a transcriptional activator complex on Notch target genes. Hairless acts as the major antagonist of the Notch signaling pathway in Drosophila by means of the formation of a repressor complex together with Su(H) and several co-repressors. Su(H) is characterized by three domains, the N-terminal domain NTD, the beta-trefoil domain BTD and the C-terminal domain CTD. NTD and BTD bind to the DNA, whereas BTD and CTD bind to ICN. Hairless binds to the CTD, however, to sites different from ICN. In this work, we have addressed the question of competition and availability of Su(H) for ICN and Hairless binding in vivo. To this end, we overexpressed the CTD during fly development. We observed a strong activation of Notch signaling processes in various tissues, which may be explained by an interference of CTD with Hairless corepressor activity. Accordingly, a combined overexpression of CTD together with Hairless ameliorated the effects, unlike Su(H) which strongly enhances repression when overexpressed concomitantly with Hairless. Interestingly, in the combined overexpression CTD accumulated in the nucleus together with Hairless, whereas it is predominantly cytoplasmic on its own.
The Notch signalling pathway mediates cell-cell communication in a wide variety of organisms. The major components, as well as the basic mechanisms of Notch signal transduction, are remarkably well conserved amongst vertebrates and invertebrates. Notch signalling results in transcriptional activation of Notch target genes, which is mediated by an activator complex composed of the DNA binding protein CSL, the intracellular domain of the Notch receptor, and the transcriptional coactivator Mastermind. In the absence of active signalling, CSL represses transcription from Notch target genes by the recruitment of corepressors. The Notch activator complex is extremely well conserved and has been studied in great detail. However, Notch repressor complexes are far less understood. In Drosophila melanogaster, the CSL protein is termed Suppressor of Hairless [Su(H)]. Su(H) functions as a transcriptional repressor by binding Hairless, the major antagonist of Notch signalling in Drosophila, which in turn recruits two general corepressors – Groucho and C-terminal binding protein CtBP. Recently, we determined that the C-terminal domain (CTD) of Su(H) binds Hairless and identified a single site in Hairless, which is essential for contacting Su(H). Here we present additional biochemical and in vivo studies aimed at mapping the residues in Su(H) that contact Hairless. Focusing on surface exposed residues in the CTD, we identified two sites that affect Hairless binding in biochemical assays. Mutation of these sites neither affects binding to DNA nor to Notch. Subsequently, these Su(H) mutants were found to function normally in cellular and in vivo assays using transgenic flies. However, these experiments rely on Su(H) overexpression, which does not allow for detection of quantitative or subtle differences in activity. We discuss the implications of our results.
Despite high conservation of the Notch pathway, its repression appears diverse between organisms. In Drosophila, a high-affinity complex forms between the CSL orthologue Su(H) and Hairless, which is analyzed in great detail in vitro and in vivo. Drosophila Hairless is shown to bind CBF1 and inhibit Notch transcriptional output in mammalian cells.
In metazoans, the highly conserved Notch pathway drives cellular specification. On receptor activation, the intracellular domain of Notch assembles a transcriptional activator complex that includes the DNA-binding protein CSL, a composite of human C-promoter binding factor 1, Suppressor of Hairless of Drosophila melanogaster [Su(H)], and lin-12 and Glp-1 phenotype of Caenorhabditis elegans. In the absence of ligand, CSL represses Notch target genes. However, despite the structural similarity of CSL orthologues, repression appears largely diverse between organisms. Here we analyze the Notch repressor complex in Drosophila, consisting of the fly CSL protein, Su(H), and the corepressor Hairless, which recruits general repressor proteins. We show that the C-terminal domain of Su(H) is necessary and sufficient for forming a high-affinity complex with Hairless. Mutations in Su(H) that affect interactions with Notch and Mastermind have no effect on Hairless binding. Nonetheless, we demonstrate that Notch and Hairless compete for CSL in vitro and in cell culture. In addition, we identify a site in Hairless that is crucial for binding Su(H) and subsequently show that this Hairless mutant is strongly impaired, failing to properly assemble the repressor complex in vivo. Finally, we demonstrate Hairless-mediated inhibition of Notch signaling in a cell culture assay, which hints at a potentially similar repression mechanism in mammals that might be exploited for therapeutic purposes.
To enhance our understanding of complex biological systems like diseases we need to put all of the available data into context and use this to detect relations, pattern and rules which allow predictive hypotheses to be defined. Life science has become a data rich science with information about the behaviour of millions of entities like genes, chemical compounds, diseases, cell types and organs, which are organised in many different databases and/or spread throughout the literature. Existing knowledge such as genotype - phenotype relations or signal transduction pathways must be semantically integrated and dynamically organised into structured networks that are connected with clinical and experimental data. Different approaches to this challenge exist but so far none has proven entirely satisfactory.
To address this challenge we previously developed a generic knowledge management framework, BioXM™, which allows the dynamic, graphic generation of domain specific knowledge representation models based on specific objects and their relations supporting annotations and ontologies. Here we demonstrate the utility of BioXM for knowledge management in systems biology as part of the EU FP6 BioBridge project on translational approaches to chronic diseases. From clinical and experimental data, text-mining results and public databases we generate a chronic obstructive pulmonary disease (COPD) knowledge base and demonstrate its use by mining specific molecular networks together with integrated clinical and experimental data.
We generate the first semantically integrated COPD specific public knowledge base and find that for the integration of clinical and experimental data with pre-existing knowledge the configuration based set-up enabled by BioXM reduced implementation time and effort for the knowledge base compared to similar systems implemented as classical software development projects. The knowledgebase enables the retrieval of sub-networks including protein-protein interaction, pathway, gene - disease and gene - compound data which are used for subsequent data analysis, modelling and simulation. Pre-structured queries and reports enhance usability; establishing their use in everyday clinical settings requires further simplification with a browser based interface which is currently under development.
The Notch signaling pathway is fundamental to the regulation of many cell fate decisions in eumetazoans. Not surprisingly, members of this pathway are highly conserved even between vertebrates and invertebrates. There is one notable exception, Hairless, which acts as a general Notch antagonist in Drosophila. Hairless silences Notch target genes by assembling a repressor complex together with Suppressor of Hairless [Su(H)] and the co-repressors Groucho (Gro) and C-terminal binding protein (CtBP). Now with the availability of genomic databases, presumptive Hairless homologues are predicted, however only in insect species. To further our understanding of Hairless structure and function, we have cloned the Hairless gene from Apis mellifera (A.m.H) and characterized its functional conservation in Drosophila.
The Apis Hairless protein is only one third of the size of the Drosophila orthologue. Interestingly, the defined Suppressor of Hairless binding domain is interrupted by a nonconserved spacer sequence and the N-terminal motif is sufficient for binding. In contrast to Apis Hairless, the Drosophila orthologue contains a large acidic domain and we provide experimental evidence that this acidic domain is necessary to silence Hairless activity in vivo. Despite the dramatic size differences, Apis Hairless binds to the Drosophila Hairless interactors Su(H), Gro, CtBP and Pros26.4. Hence, Apis Hairless assembles a repressor complex with Drosophila components that may have a different topology. Nevertheless, Apis Hairless is sufficient to repress the Notch target gene vestigial in Drosophila. Moreover, it is able to rescue Hairless mutant phenotypes, providing in vivo evidence for its function as a bona fide Notch antagonist.
This is the first interspecies-complementation analysis of the Hairless gene. Guided by evolutionary comparisons, we hope to eventually identify all the relevant structural domains and cofactors of Hairless, thereby opening an avenue for further insights into the repressor-complexes that down-regulate Notch signaling also in other, higher eukaryotes.
Polycomb (PcG) and trithorax (trxG) genes encode proteins involved in the maintenance of gene expression patterns, notably Hox genes, throughout development. PcG proteins are required for long-term gene repression whereas TrxG proteins are positive regulators that counteract PcG action. PcG and TrxG proteins form large complexes that bind chromatin at overlapping sites called Polycomb and Trithorax Response Elements (PRE/TRE). A third class of proteins, so-called “Enhancers of Trithorax and Polycomb” (ETP), interacts with either complexes, behaving sometimes as repressors and sometimes as activators. The role of ETP proteins is largely unknown.
In a two-hybrid screen, we identified Cyclin G (CycG) as a partner of the Drosophila ETP Corto. Inactivation of CycG by RNA interference highlights its essential role during development. We show here that Corto and CycG directly interact and bind to each other in embryos and S2 cells. Moreover, CycG is targeted to polytene chromosomes where it co-localizes at multiple sites with Corto and with the PcG factor Polyhomeotic (PH). We observed that corto is involved in maintaining Abd-B repression outside its normal expression domain in embryos. This could be achieved by association between Corto and CycG since both proteins bind the regulatory element iab-7 PRE and the promoter of the Abd-B gene.
Our results suggest that CycG could regulate the activity of Corto at chromatin and thus be involved in changing Corto from an Enhancer of TrxG into an Enhancer of PcG.
Protein Kinase D (PKD) is an effector of diacylglycerol-regulated signaling pathways. Three isoforms are known in mammals that have been linked to diverse cellular functions including regulation of cell proliferation, differentiation, motility and secretory transport from the trans-Golgi network to the plasma membrane. In Drosophila, there is a single PKD orthologue, whose broad expression implicates a more general role in development.
We have employed tissue specific overexpression of various PKD variants as well as tissue specific RNAi, in order to investigate the function of the PKD gene in Drosophila. Apart from a wild type (WT), a kinase dead (kd) and constitutively active (SE) Drosophila PKD variant, we also analyzed two human isoforms hPKD2 and hPKD3 for their capacity to substitute PKD activity in the fly. Overexpression of either WT or kd-PKD variants affected primarily wing vein development. However, overexpression of SE-PKD and PKD RNAi was deleterious. We observed tissue loss, wing defects and degeneration of the retina. The latter phenotype conforms to a role of PKD in the regulation of cytoskeletal dynamics. Strongest phenotypes were larval to pupal lethality. RNAi induced phenotypes could be rescued by a concurrent overexpression of Drosophila wild type PKD or either human isoform hPKD2 and hPKD3.
Our data confirm the hypothesis that Drosophila PKD is a multifunctional kinase involved in diverse processes such as regulation of the cytoskeleton, cell proliferation and death as well as differentiation of various fly tissues.
Notch signal transduction centers on a conserved DNA-binding protein called Suppressor of Hairless [Su(H)] in Drosophila species. In the absence of Notch activation, target genes are repressed by Su(H) acting in conjunction with a partner, Hairless, which contains binding motifs for two global corepressors, CtBP and Groucho (Gro). Usually these corepressors are thought to act via different mechanisms; complexed with other transcriptional regulators, they function independently and/or redundantly. Here we have investigated the requirement for Gro and CtBP in Hairless-mediated repression. Unexpectedly, we find that mutations inactivating one or the other binding motif can have detrimental effects on Hairless similar to those of mutations that inactivate both motifs. These results argue that recruitment of one or the other corepressor is not sufficient to confer repression in the context of the Hairless-Su(H) complex; Gro and CtBP need to function in combination. In addition, we demonstrate that Hairless has a second mode of repression that antagonizes Notch intracellular domain and is independent of Gro or CtBP binding.
In Drosophila melanogaster the Enhancer of split-Complex [E(spl)-C] consists of seven highly related genes encoding basic helix-loop-helix (bHLH) repressors and intermingled, four genes that belong to the Bearded (Brd) family. Both gene classes are targets of the Notch signalling pathway. The Achaete-Scute-Complex [AS-C] comprises four genes encoding bHLH activators. The question arose how these complexes evolved with regard to gene number in the evolution of insects concentrating on Diptera and the Hymenoptera Apis mellifera.
In Drosophilids both gene complexes are highly conserved, spanning roughly 40 million years of evolution. However, in species more diverged like Anopheles or Apis we find dramatic differences. Here, the E(spl)-C consists of one bHLH (mβ) and one Brd family member (mα) in a head to head arrangement. Interestingly in Apis but not in Anopheles, there are two more E(spl) bHLH like genes within 250 kb, which may reflect duplication events in the honeybee that occurred independently of that in Diptera. The AS-C may have arisen from a single sc/l'sc like gene which is well conserved in Apis and Anopheles and a second ase like gene that is highly diverged, however, located within 50 kb.
E(spl)-C and AS-C presumably evolved by gene duplication to the nowadays complex composition in Drosophilids in order to govern the accurate expression patterns typical for these highly evolved insects. The ancestral ur-complexes, however, consisted most likely of just two genes: E(spl)-C contains one bHLH member of mβ type and one Brd family member of mα type and AS-C contains one sc/l'sc and a highly diverged ase like gene.
In this paper, we present the Functional Catalogue (FunCat), a hierarchically structured, organism-independent, flexible and scalable controlled classification system enabling the functional description of proteins from any organism. FunCat has been applied for the manual annotation of prokaryotes, fungi, plants and animals. We describe how FunCat is implemented as a highly efficient and robust tool for the manual and automatic annotation of genomic sequences. Owing to its hierarchical architecture, FunCat has also proved to be useful for many subsequent downstream bioinformatic applications. This is illustrated by the analysis of large-scale experiments from various investigations in transcriptomics and proteomics, where FunCat was used to project experimental data into functional units, as ‘gold standard’ for functional classification methods, and also served to compare the significance of different experimental methods. Over the last decade, the FunCat has been established as a robust and stable annotation scheme that offers both, meaningful and manageable functional classification as well as ease of perception.
The discovery that several inherited human diseases are caused by
mtDNA depletion has led to an increased interest in the replication and
maintenance of mtDNA. We have isolated a new mutant in the
lopo (low power) gene from
Drosophila melanogaster affecting the mitochondrial
single-stranded DNA-binding protein (mtSSB), which is one of the key
components in mtDNA replication and maintenance.
lopo1 mutants die late in the third instar
before completion of metamorphosis because of a failure in cell
proliferation. Molecular, histochemical, and physiological experiments
show a drastic decrease in mtDNA content that is coupled with the loss
of respiration in these mutants. However, the number and morphology of
mitochondria are not greatly affected. Immunocytochemical analysis
shows that mtSSB is expressed in all tissues but is highly enriched in
proliferating tissues and in the developing oocyte.
lopo1 is the first mtSSB mutant in higher
eukaryotes, and its analysis demonstrates the essential function of
this gene in development, providing an excellent model to study
mitochondrial biogenesis in animals.