11 January 2016

Happy new year to all of you

Dear all,

A very happy new year to all of you!

That the year 2016 will bring us nice results!


8 December 2015

Jan Boren (University of Gothenburg, Sweden) about his role in the RESOLVE consortium

  • What is the expertise / knowledge that you bring into the RESOLVE project?
    We have a long history of studying metabolic diseases, including type 2 diabetes and fatty liver. Most of our research has focused on lipids and lipoproteins . Our expertise includes assembly and secretion of lipoproteins in the liver, lipoprotein metabolism and regulation in the blood, mathematical modeling of lipoproteins, stable isotope labelling and molecular lipid analyses.
  • What is your role in the RESOLVE project and why is your data relevant for the consortium?
    Our role is to provide data, both by previous and ongoing studies, of how lipoproteins circulate in the blood. These data provides a fundament on which more complex models can be built.
  • What are the challenges, in your opinion, in the project?
    The most challenging task is to generate the right data, at the right time, that is needed to build the models. Data generation, in particular data from humans, takes very long time and it may be too short time for the modelers to build models based on the data.
  • How can RESOLVE help your research?
    RESOLVE impact our research directly, as development of models allows us to investigate exactly the research questions that are in our primary interest. That is; how the lipid metabolism is regulated and modified by interventions.
  • How do you think, can system approaches help your research?
    Building from our own and others research it is easy to draw a cartoon, a schematic picture, of how things are connected. We may draw lines that connect our favorite molecules and organs. However, when it comes to understand how strong these relationships are in reality things are not so easy. We may have derived our findings from cells, mice models, genetic diseases or observations in humans.
    By building mathematical models it is possible both to verify the existence of the connections, but also to quantify how strong (and relevant) the connections are.
  • How close is your science to the community and patients with the metabolic syndrome?
    Our research is very close to the patients. For the last decade we have focused our efforts on understanding how lipid disorders appear in the metabolic syndrome. Most of our study subjects are individuals with the metabolic syndrome.
  • What are, in your opinion, directions of decisions that are vital to the progress of systems medicine?
    Firstly, we think that systems medicine will be an important corner stone in the future of medical research. For systems medicine to gain traction we believe there are several critical decisions to be made:

    • To many researchers the use of models, equations and special computer software are not easy. Software with a low entry threshold and with out of the box functionality is needed.
    • Comprehensive databases and model collections are needed. Today researchers need to draw data from several sources, using different formats and versions.
    • Many technical hurdles still exist. It is too early to start to focus on particular solutions and/or techniques. For instance, time scales (body weight changes in the scale of years vs hours for blood lipids) and amounts (10’s of kilos of body fat vs grams of blood lipids) needs to be combined with spatial scales (organ, tissue, cells) and blood flow models. Likely, models needs to be described on different levels for different research questions.
    • More research is needed on how to solve computational challenges that arise in biological systems. Uncertainties are present in the measurements as well as in the models. Biological variation is having a large impact on results and new approaches to combine mathematical and statistical models are needed.


1 December 2015

Yvonne Rozendaal about being a PhD student in the RESOLVE consortium

Yvonne Rozendaal is a PhD student for the RESOLVE consortium in the Computational Biology group at Eindhoven University of Technology, the Netherlands. Her research focusses on building computational models to unravel the underlying pathways of the Metabolic Syndrome.

The Metabolic Syndrome is a cluster of co-morbidities, including obesity, elevated blood pressure, insulin resistance (diabetes type 2), and dyslipidemia (high triglyceride levels, low HDL-cholesterol levels). From these symptoms it is evident that both the systems that are responsible for glucose and lipid regulation are affected. This makes it hard to unravel what is the underlying cause that result in the onset and progression of this disease, and what possible treatment options would be targeted at.

As you can image, we cannot simply open up a patient to see which and how organs and tissues are affected. Nevertheless, we can easily perform measurements to assess the glucose and lipid levels in the blood at many different time points during the disease development. However, the concentrations in the blood are only balances of exchange fluxes between for example the liver and adipose tissue. From only these concentrations we cannot unravel what and how different organs and tissues play a role in the onset and progression of the Metabolic Syndrome.

However, from the literature we know the different functions that different organs and tissues exhibit. Using this biological information, together with the measured data, we can project the measured information onto this scheme of the regulatory system, and translate this into equations that describe the exchange and conversion of various metabolites between e.g. the liver, adipose tissue and blood plasma. And then the data obtained from preclinical studies to predict the unknown and unobserved processes (fluxes, species, time points) can be integrated in the model.

Furthermore, we can even simulate possible treatments and interventions and explore their effects. In this case of the Metabolic Syndrome, especially the balance between energy intake and energy consumption (through e.g. exercise and heat production) is important. Recently much attention has been paid to the activity of so-called Brown Adipose Tissue (BAT), which possesses the ability to produce heat under e.g. cold exposure. But there are other ways to stimulate energy expenditure: BAT can also be activated via pharmacological targeting. This seems a promising target to combat obesity and its related diseases, and is one step closer to finding out which processes we should target to reverse the Metabolic Syndrome back to a healthy state.


13 November 2015

Prof. Kardassis about his role in the RESOLVE consortium


 What is the expertise / knowledge that you bring into the RESOLVE project?

 The expertise that I bring into the RESOLVE project is transcriptomics i.e. obtaining and analyzing RNA data from tissue samples in order to identify global changes in the expression profiles of genes and their association with certain human diseases. In RESOLVE, the disease in focus is the metabolic syndrome (MetS) i.e. a complex metabolic disorder consisting of multiples clinical features including obesity, type II diabetes and dyslipidemia. In our group, we are using the apoE3Leiden.CETP mouse model of MetS and we are performing genetic interventions in order to study the role of key transcription factors (proteins that are involved in the regulation of the expression of genes at the level of transcription) in the pathogenesis of the disease. Our ultimate goal is to use all this information in order to optimize the computational model of MetS that the RESOLVE consortium is developing and to identify novel biomarkers and possible therapeutic targets that will improve the prognosis, the diagnosis and the treatment of MetS.


What is your role in the RESOLVE project and why is your data relevant for the consortium?

 Human diseases are caused by dysregulation of the expression or the activity of genes. In monogenic disorders, the study of their molecular and genetic basis is a relatively easy task but for complex diseases such as the MetS which includes several co-morbidities, the role of specific genes in disease initiation, progression and resolution is not known. My role in RESOLVE is to provide information regarding the genes and gene networks which are involved in the various stages of the pathogenesis of MetS and how these are related to disturbances in other metabolic parameters.


What are the challenges, in your opinion, in the project?

 The challenges in the project are multiple. Perhaps the key challenge is how to integrate data obtained from different sources (human patients, mouse models) in a meaningful and useful way so that we understand better the pathology of the disease and develop novel diagnostic and prognostic tools. Another challenge is how to use standard operating procedures (SOPs) in an optimal way so that we minimize to the best possible degree the variability in the measurements between labs. Finally, a key challenge is how we will use all the information coming from different and complementary -omics approaches to further develop a comprehensive computer model allowing targeting the underlying mechanism of low HDL-C, high triglyceride and loss of glycemic control in MetS patients. This will hopefully be translated into novel avenues for development of therapeutic intervention.



How can RESOLVE help your research?

 RESOLVE is a highly multidisciplinary consortium consisting of teams with expertise in biochemistry, clinical chemistry, molecular biology, genetics, clinicians, biomedical engineers etc.  Through my participation at the RESOLVE consortium I have the opportunity to collaborate with all these people and exchange ideas, samples, technologies and data. Understanding complex diseases such as the MetS is a team effort and I am very fortunate to be part of this great team of investigators.


How do you think, can system approaches help your research?

 In complex diseases such as the MetS which includes several co-morbidities, the role of specific genes in disease initiation, progression and resolution is not well known. It is anticipated that disturbances in genes encoding for transcription factors or signaling proteins will affect the expression and the activity of complex downstream gene networks and have a major impact on the pathogenesis of the diseases either in a positive or a negative way. The best approach to understand in depth MetS and to develop reliable diagnostic tools and therapies is through a systems approach only i.e. by applying large scale -omics approaches (proteomics, lipidomics, transcriptomics) that provide information not only on the expression of specific genes or the protein and lipid content at specific time points or conditions but also on how these patetrns are connected to each other in networks. RESOLVE has given me the opportunity to have access to large scale omics data from partner labs on one hand and at the same time the transcriptomics data that come out of our lab are accessible to the other partners for utilization and integration. I am anticipating that this team effort will be translated ino high impact joint publications and will open new avenues of research and new opportunities for funding.


How close is your science to the community and patients with the metabolic syndrome?

 In my lab we are doing basic science i.e. we are trying to understand the molecular and genetic basis of human diseases such as the MetS at the molecular and cellular level. This information will subsequently need to be translated, in collaboration with clinical colleagues and the pharma industry, into novel treatments and therapies to the benefit of the patients. As basic scientists, we are not close to the patients but we are trying to disseminate the results of our research to the patient communities by giving seminars and writing articles in the local press.


What are, in your opinion, directions of decisions that are vital to the progress of systems medicine?

  • Formation of systems (or translational) medicine “Centers of Excellence” in each country which will require joint investment (facilities and personnel) from EU and the government
  • More Horizon 2020 calls for systems medicine with the opportunity for renewal of successful proposals
  • Support for the development of novel computational tools for the translational utilization of systems medicine omics data
  • Development of strong European bioinformatics centers that will store and analyze the enormous amounts of new data coming from the labs


6 November 2015

Markus Heine (postdoctoral fellow) about his work in the RESOLVE project

My name is Markus Heine and I am a postdoctoral fellow at the University Medical Center Hamburg-Eppendorf (UKE) in the laboratory of Joerg Heeren. We aim to understand the systemic regulation of energy metabolism in health and disease states. Energy dense lipids are transported in the blood by special carriers that are called lipoproteins. We focus on the metabolism of a special class of lipoproteins, the triglyceride lipoproteins (TRL) that are produced from the liver as well as from intestinal cells after a lipid rich meal. Usually, TRL are processed by professional lipid handling organs, e.g. adipose tissue and muscle. These processes can be altered in disease conditions such as the Metabolic Syndrome in an organ-specific manner, changes that are often associated with the development of severe chronic diseases such as diabetes and atherosclerosis. In the EU project RESOLVE we try to understand the systemic disturbances in sugar and lipid metabolism observed in individuals with the Metabolic Syndrome. In my project, I am focusing on an adipose tissue that was just recently found to be active in adult humans, the brown adipose tissue (BAT). In contrast to white adipose tissue that stores energy in form of lipids, BAT burns lipids upon cold exposure to generate heat to defend the body against cold. Thus, the activation of BAT may be a good target to treat patients with obesity-associated diseases. To visualize and quantify the fate of lipoproteins under conditions of BAT activation, we have established several nanoparticle-based tools. These technologies are used to define the variables that influence the transport of TRL to their final destinations. One variable is the hormone insulin which is produced after a sugar digestion and mediates the uptake of sugars into different organs. We think that insulin also plays an important role for lipid uptake processes into activated BAT to fill up energy stores. Therefore, we used models to decipher the role of insulin under conditions mimicking the Metabolic Syndrome. The data generated in our laboratory are then used for a computer model called ADAPT, which at the end should help to predict disease development in individuals with the Metabolic Syndrome. Based on the ADAPT model the ultimate goal will be to identify individuals at high risk for the development of a specific, life-threatening disease allowing individualized prevention and treatment of obesity, atherosclerosis and diabetes.


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