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Promoting the work of the OPCW through toxicology societies
Abstracts / Toxicology Letters 258S (2016) S15–S38
ing into force of the Chemical Weapons Convention to ensure the elimination and prevent re-emergence of this chemicals as warfare agents through a unique inspection and verification regime and also to enhance capacity of the member states to respond timely and effectively to incidents involving such chemical warfare agents or other toxic industrial chemicals including OPs.
S33
President of EUROTOX, Greece
aspect of understanding the environmental determinants of chronic disease. Metabolic phenotypes and their responses to various environmental stimuli report on the changes in complex biochemical networks that incorporate processes modulated by numerous genomic and environmental factors. Measuring the human metabolome in biofluids or tissue represents a huge profiling challenge, which has been addressed by the application of high resolution analytical platforms. A combination of targeted and untargeted strategies are regularly applied to provide wide coverage of the human metabolome, and included in several large-scale molecular epidemiological projects are underway, including the focus of this contribution, EU FP7 EXPOsOMICS. The key analytical challenges of metabolome measurement and quality control within large sample sets is discussed, alongside the need to understand variability in both metabolome components in the context of different states of health and disease.
http://dx.doi.org/10.1016/j.toxlet.2016.06.1225
http://dx.doi.org/10.1016/j.toxlet.2016.06.1227
Symposium S14: The impact of complexity on chronic disease from exposure to treatment
S14-3 Advances in multi-omics approaches in chronic disease
http://dx.doi.org/10.1016/j.toxlet.2016.06.1224 S13-4 Promoting the work of the OPCW through toxicology societies Aristidis Tsatsakis
S14-1 Disease networks and predictive methods for clinical data analytics Cesare Furlanello ∗ Predictive Models for Biomedicine & Environment, Fondazione Bruno Kessler, Trento, Italy Novel bioinformatics tools based on network analysis approaches are increasingly used in Systems Medicine. Indeed complex disease arise from the interaction of heterogeneous factors within different domains, such as genetics, metabolomics, proteomic and environment, affecting biological networks, genes and pathways that govern molecular actions. Disease networks have bipartite structures linking diseases to genes, or diseases to symptoms. Further, undirected networks connecting diseases can be defined from the clinical evidence of co-morbidity extracted from clinical patient data. The talk will describe the landscape of main bioinformatics methods and data resources for disease networks, also introducing the expected high impact of deep learning to discover significant complex patterns in disease by modeling multivariate time series of clinical measurements with deep multilayer networks. http://dx.doi.org/10.1016/j.toxlet.2016.06.1226 S14-2 Emergence of new properties in the investigation of disease aetiology: The contribution of omics Toby James Athersuch ∗ Department of Surgery and Cancer, Imperial College London, London, UK The emerging concept of a human exposome – an environmentally-based complement to the human genome – places substantial weight on the internal chemical milieu of individuals. Small molecule metabolites of endogenous and exogenous origin are involved in a wide variety of cellular- and system-level functions; their measurement represents a critical
Jos Kleinjans ∗ Department of Toxicogenomics, Maastricht University, The Netherlands Molecular biomarkers for predicting chronic disease risk in human populations exposed to adverse environmental factors have been explored for more than 25 years now. Where initially such markers, though informative, were considered of limited value in view of issues concerning sensitivity and specificity, e.g. biological relevance for the targeted endpoint of chronic disease, that advent of the so-called omics technologies have been welcome primarily because of their potential of providing in depth information on underlying mechanisms eventually inducing chronic disease. While the first generation of omics-based biomarker studies have predominantly explore whole genome gene expression analysis (transcriptomics), more recent studies have built on our increasing insight into the mechanistic contribution of multiple layers of cellular regulation, and on the consequent development of further analytical omics platforms nowadays enabling not only transcriptomics analysis, but epigenomics, proteomics and metabolomics investigations as well. Recent studies, for instance within the framework of related EU projects such as EnviroGenoMarkers and Exposomics, report on the interesting cross-talk between the epigenome, the transcriptome and microRNAs monitored in the blood of smoking individuals as well as of environmentally exposed subjects. Within this context, circulating microRNAs seem particularly promising because of their potential target organ specificity. A range of case studies on the outcome of population studies applying this multi-omics approach will be presented. http://dx.doi.org/10.1016/j.toxlet.2016.06.1228 S14-4 Integrating genomic and clinical complexity for better patient outcomes Gerrit Meijer ∗ Netherlands Cancer Institute, Amsterdam, Netherlands The innovation gap is a serious problem in translational research: How can we validate innovations, such as biomarkers
ing into force of the Chemical Weapons Convention to ensure the elimination and prevent re-emergence of this chemicals as warfare agents through a unique inspection and verification regime and also to enhance capacity of the member states to respond timely and effectively to incidents involving such chemical warfare agents or other toxic industrial chemicals including OPs.
S33
President of EUROTOX, Greece
aspect of understanding the environmental determinants of chronic disease. Metabolic phenotypes and their responses to various environmental stimuli report on the changes in complex biochemical networks that incorporate processes modulated by numerous genomic and environmental factors. Measuring the human metabolome in biofluids or tissue represents a huge profiling challenge, which has been addressed by the application of high resolution analytical platforms. A combination of targeted and untargeted strategies are regularly applied to provide wide coverage of the human metabolome, and included in several large-scale molecular epidemiological projects are underway, including the focus of this contribution, EU FP7 EXPOsOMICS. The key analytical challenges of metabolome measurement and quality control within large sample sets is discussed, alongside the need to understand variability in both metabolome components in the context of different states of health and disease.
http://dx.doi.org/10.1016/j.toxlet.2016.06.1225
http://dx.doi.org/10.1016/j.toxlet.2016.06.1227
Symposium S14: The impact of complexity on chronic disease from exposure to treatment
S14-3 Advances in multi-omics approaches in chronic disease
http://dx.doi.org/10.1016/j.toxlet.2016.06.1224 S13-4 Promoting the work of the OPCW through toxicology societies Aristidis Tsatsakis
S14-1 Disease networks and predictive methods for clinical data analytics Cesare Furlanello ∗ Predictive Models for Biomedicine & Environment, Fondazione Bruno Kessler, Trento, Italy Novel bioinformatics tools based on network analysis approaches are increasingly used in Systems Medicine. Indeed complex disease arise from the interaction of heterogeneous factors within different domains, such as genetics, metabolomics, proteomic and environment, affecting biological networks, genes and pathways that govern molecular actions. Disease networks have bipartite structures linking diseases to genes, or diseases to symptoms. Further, undirected networks connecting diseases can be defined from the clinical evidence of co-morbidity extracted from clinical patient data. The talk will describe the landscape of main bioinformatics methods and data resources for disease networks, also introducing the expected high impact of deep learning to discover significant complex patterns in disease by modeling multivariate time series of clinical measurements with deep multilayer networks. http://dx.doi.org/10.1016/j.toxlet.2016.06.1226 S14-2 Emergence of new properties in the investigation of disease aetiology: The contribution of omics Toby James Athersuch ∗ Department of Surgery and Cancer, Imperial College London, London, UK The emerging concept of a human exposome – an environmentally-based complement to the human genome – places substantial weight on the internal chemical milieu of individuals. Small molecule metabolites of endogenous and exogenous origin are involved in a wide variety of cellular- and system-level functions; their measurement represents a critical
Jos Kleinjans ∗ Department of Toxicogenomics, Maastricht University, The Netherlands Molecular biomarkers for predicting chronic disease risk in human populations exposed to adverse environmental factors have been explored for more than 25 years now. Where initially such markers, though informative, were considered of limited value in view of issues concerning sensitivity and specificity, e.g. biological relevance for the targeted endpoint of chronic disease, that advent of the so-called omics technologies have been welcome primarily because of their potential of providing in depth information on underlying mechanisms eventually inducing chronic disease. While the first generation of omics-based biomarker studies have predominantly explore whole genome gene expression analysis (transcriptomics), more recent studies have built on our increasing insight into the mechanistic contribution of multiple layers of cellular regulation, and on the consequent development of further analytical omics platforms nowadays enabling not only transcriptomics analysis, but epigenomics, proteomics and metabolomics investigations as well. Recent studies, for instance within the framework of related EU projects such as EnviroGenoMarkers and Exposomics, report on the interesting cross-talk between the epigenome, the transcriptome and microRNAs monitored in the blood of smoking individuals as well as of environmentally exposed subjects. Within this context, circulating microRNAs seem particularly promising because of their potential target organ specificity. A range of case studies on the outcome of population studies applying this multi-omics approach will be presented. http://dx.doi.org/10.1016/j.toxlet.2016.06.1228 S14-4 Integrating genomic and clinical complexity for better patient outcomes Gerrit Meijer ∗ Netherlands Cancer Institute, Amsterdam, Netherlands The innovation gap is a serious problem in translational research: How can we validate innovations, such as biomarkers