Project acronym 3D-JOINT
Project 3D Bioprinting of JOINT Replacements
Researcher (PI) Johannes Jos Malda
Host Institution (HI) UNIVERSITAIR MEDISCH CENTRUM UTRECHT
Call Details Consolidator Grant (CoG), LS7, ERC-2014-CoG
Summary The world has a significant medical challenge in repairing injured or diseased joints. Joint degeneration and its related pain is a major socio-economic burden that will increase over the next decade and is currently addressed by implanting a metal prosthesis. For the long term, the ideal solution to joint injury is to successfully regenerate rather than replace the damaged cartilage with synthetic implants. Recent advances in key technologies are now bringing this “holy grail” within reach; regenerative approaches, based on cell therapy, are already clinically available albeit only for smaller focal cartilage defects.
One of these key technologies is three-dimensional (3D) bio-printing, which provides a greatly controlled placement and organization of living constructs through the layer-by-layer deposition of materials and cells. These tissue constructs can be applied as tissue models for research and screening. However, the lack of biomechanical properties of these tissue constructs has hampered their application to the regeneration of damaged, degenerated or diseased tissue.
Having established a cartilage-focussed research laboratory in the University Medical Center Utrecht, I have addressed this biomechanical limitation of hydrogels through the use of hydrogel composites. Specifically, I have pioneered a 3D bio-printing technology that combines accurately printed small diameter thermoplast filaments with cell invasive hydrogels to form strong fibre-reinforced constructs. This, in combination with bioreactor technology, is the key to the generation of larger, complex tissue constructs with cartilage-like biomechanical resilience. With 3D-JOINT I will use my in-depth bio-printing and bioreactor knowledge and experience to develop a multi-phasic 3D-printed biological replacement of the joint.
Summary
The world has a significant medical challenge in repairing injured or diseased joints. Joint degeneration and its related pain is a major socio-economic burden that will increase over the next decade and is currently addressed by implanting a metal prosthesis. For the long term, the ideal solution to joint injury is to successfully regenerate rather than replace the damaged cartilage with synthetic implants. Recent advances in key technologies are now bringing this “holy grail” within reach; regenerative approaches, based on cell therapy, are already clinically available albeit only for smaller focal cartilage defects.
One of these key technologies is three-dimensional (3D) bio-printing, which provides a greatly controlled placement and organization of living constructs through the layer-by-layer deposition of materials and cells. These tissue constructs can be applied as tissue models for research and screening. However, the lack of biomechanical properties of these tissue constructs has hampered their application to the regeneration of damaged, degenerated or diseased tissue.
Having established a cartilage-focussed research laboratory in the University Medical Center Utrecht, I have addressed this biomechanical limitation of hydrogels through the use of hydrogel composites. Specifically, I have pioneered a 3D bio-printing technology that combines accurately printed small diameter thermoplast filaments with cell invasive hydrogels to form strong fibre-reinforced constructs. This, in combination with bioreactor technology, is the key to the generation of larger, complex tissue constructs with cartilage-like biomechanical resilience. With 3D-JOINT I will use my in-depth bio-printing and bioreactor knowledge and experience to develop a multi-phasic 3D-printed biological replacement of the joint.
Max ERC Funding
1 998 871 €
Duration
Start date: 2015-07-01, End date: 2020-06-30
Project acronym ALLEGRO
Project unrAvelLing sLow modE travelinG and tRaffic: with innOvative data to a new transportation and traffic theory for pedestrians and bicycles
Researcher (PI) Serge Hoogendoorn
Host Institution (HI) TECHNISCHE UNIVERSITEIT DELFT
Call Details Advanced Grant (AdG), SH3, ERC-2014-ADG
Summary A major challenge in contemporary traffic and transportation theory is having a comprehensive understanding of pedestrians and cyclists behaviour. This is notoriously hard to observe, since sensors providing abundant and detailed information about key variables characterising this behaviour have not been available until very recently. The behaviour is also far more complex than that of the much better understood fast mode. This is due to the many degrees of freedom in decision-making, the interactions among slow traffic participants that are more involved and far less guided by traffic rules and regulations than those between car-drivers, and the many fascinating but complex phenomena in slow traffic flows (self-organised patterns, turbulence, spontaneous phase transitions, herding, etc.) that are very hard to predict accurately.
With slow traffic modes gaining ground in terms of mode share in many cities, lack of empirical insights, behavioural theories, predictively valid analytical and simulation models, and tools to support planning, design, management and control is posing a major societal problem as well: examples of major accidents due to bad planning, organisation and management of events are manifold, as are locations where safety of slow modes is a serious issue due to interactions with fast modes.
This programme is geared towards establishing a comprehensive theory of slow mode traffic behaviour, considering the different behavioural levels relevant for understanding, reproducing and predicting slow mode traffic flows in cities. The levels deal with walking and cycling operations, activity scheduling and travel behaviour, and knowledge representation and learning. Major scientific breakthroughs are expected at each of these levels, in terms of theory and modelling, by using innovative (big) data collection and experimentation, analysis and fusion techniques, including social media data analytics, using augmented reality, and remote and crowd sensing.
Summary
A major challenge in contemporary traffic and transportation theory is having a comprehensive understanding of pedestrians and cyclists behaviour. This is notoriously hard to observe, since sensors providing abundant and detailed information about key variables characterising this behaviour have not been available until very recently. The behaviour is also far more complex than that of the much better understood fast mode. This is due to the many degrees of freedom in decision-making, the interactions among slow traffic participants that are more involved and far less guided by traffic rules and regulations than those between car-drivers, and the many fascinating but complex phenomena in slow traffic flows (self-organised patterns, turbulence, spontaneous phase transitions, herding, etc.) that are very hard to predict accurately.
With slow traffic modes gaining ground in terms of mode share in many cities, lack of empirical insights, behavioural theories, predictively valid analytical and simulation models, and tools to support planning, design, management and control is posing a major societal problem as well: examples of major accidents due to bad planning, organisation and management of events are manifold, as are locations where safety of slow modes is a serious issue due to interactions with fast modes.
This programme is geared towards establishing a comprehensive theory of slow mode traffic behaviour, considering the different behavioural levels relevant for understanding, reproducing and predicting slow mode traffic flows in cities. The levels deal with walking and cycling operations, activity scheduling and travel behaviour, and knowledge representation and learning. Major scientific breakthroughs are expected at each of these levels, in terms of theory and modelling, by using innovative (big) data collection and experimentation, analysis and fusion techniques, including social media data analytics, using augmented reality, and remote and crowd sensing.
Max ERC Funding
2 458 700 €
Duration
Start date: 2015-11-01, End date: 2020-10-31
Project acronym ASICA
Project New constraints on the Amazonian carbon balance from airborne observations of the stable isotopes of CO2
Researcher (PI) Wouter Peters
Host Institution (HI) WAGENINGEN UNIVERSITY
Call Details Consolidator Grant (CoG), PE10, ERC-2014-CoG
Summary Severe droughts in Amazonia in 2005 and 2010 caused widespread loss of carbon from the terrestrial biosphere. This loss, almost twice the annual fossil fuel CO2 emissions in the EU, suggests a large sensitivity of the Amazonian carbon balance to a predicted more intense drought regime in the next decades. This is a dangerous inference though, as there is no scientific consensus on the most basic metrics of Amazonian carbon exchange: the gross primary production (GPP) and its response to moisture deficits in the soil and atmosphere. Measuring them on scales that span the whole Amazon forest was thus far impossible, but in this project I aim to deliver the first observation-based estimate of pan-Amazonian GPP and its drought induced variations.
My program builds on two recent breakthroughs in our use of stable isotopes (13C, 17O, 18O) in atmospheric CO2: (1) Our discovery that observed δ¹³C in CO2 in the atmosphere is a quantitative measure for vegetation water-use efficiency over millions of square kilometers, integrating the drought response of individual plants. (2) The possibility to precisely measure the relative ratios of 18O/16O and 17O/16O in CO2, called Δ17O. Anomalous Δ17O values are present in air coming down from the stratosphere, but this anomaly is removed upon contact of CO2 with leaf water inside plant stomata. Hence, observed Δ17O values depend directly on the magnitude of GPP. Both δ¹³C and Δ17O measurements are scarce over the Amazon-basin, and I propose more than 7000 new measurements leveraging an established aircraft monitoring program in Brazil. Quantitative interpretation of these observations will break new ground in our use of stable isotopes to understand climate variations, and is facilitated by our renowned numerical modeling system “CarbonTracker”. My program will answer two burning question in carbon cycle science today: (a) What is the magnitude of GPP in Amazonia? And (b) How does it vary over different intensities of drought?
Summary
Severe droughts in Amazonia in 2005 and 2010 caused widespread loss of carbon from the terrestrial biosphere. This loss, almost twice the annual fossil fuel CO2 emissions in the EU, suggests a large sensitivity of the Amazonian carbon balance to a predicted more intense drought regime in the next decades. This is a dangerous inference though, as there is no scientific consensus on the most basic metrics of Amazonian carbon exchange: the gross primary production (GPP) and its response to moisture deficits in the soil and atmosphere. Measuring them on scales that span the whole Amazon forest was thus far impossible, but in this project I aim to deliver the first observation-based estimate of pan-Amazonian GPP and its drought induced variations.
My program builds on two recent breakthroughs in our use of stable isotopes (13C, 17O, 18O) in atmospheric CO2: (1) Our discovery that observed δ¹³C in CO2 in the atmosphere is a quantitative measure for vegetation water-use efficiency over millions of square kilometers, integrating the drought response of individual plants. (2) The possibility to precisely measure the relative ratios of 18O/16O and 17O/16O in CO2, called Δ17O. Anomalous Δ17O values are present in air coming down from the stratosphere, but this anomaly is removed upon contact of CO2 with leaf water inside plant stomata. Hence, observed Δ17O values depend directly on the magnitude of GPP. Both δ¹³C and Δ17O measurements are scarce over the Amazon-basin, and I propose more than 7000 new measurements leveraging an established aircraft monitoring program in Brazil. Quantitative interpretation of these observations will break new ground in our use of stable isotopes to understand climate variations, and is facilitated by our renowned numerical modeling system “CarbonTracker”. My program will answer two burning question in carbon cycle science today: (a) What is the magnitude of GPP in Amazonia? And (b) How does it vary over different intensities of drought?
Max ERC Funding
2 269 689 €
Duration
Start date: 2015-09-01, End date: 2020-08-31
Project acronym BayesianMarkets
Project Bayesian markets for unverifiable truths
Researcher (PI) Aurelien Baillon
Host Institution (HI) ERASMUS UNIVERSITEIT ROTTERDAM
Call Details Starting Grant (StG), SH1, ERC-2014-STG
Summary Subjective data play an increasing role in modern economics. For instance, new welfare measurements are based on people’s subjective assessments of their happiness or their life satisfaction. A problem of such measurements is that people have no incentives to tell the truth. To solve this problem and make those measurements incentive compatible, I will introduce a new market institution, called Bayesian markets.
Imagine we ask people whether they are happy with their life. On Bayesian markets, they will trade an asset whose value is the proportion of people answering Yes. Only those answering Yes will have the right to buy the asset and those answering No the right to sell it. Bayesian updating implies that “Yes” agents predict a higher value of the asset than “No” agents do and, consequently, “Yes” agents want to buy it while “No” agents want to sell it. I will show that truth-telling is then the optimal strategy.
Bayesian markets reward truth-telling the same way as prediction markets (betting markets) reward people for reporting their true subjective probabilities about observable events. Yet, unlike prediction markets, they do not require events to be objectively observable. Bayesian markets apply to any type of unverifiable truths, from one’s own happiness to beliefs about events that will never be observed.
The present research program will first establish the theoretical foundations of Bayesian markets. It will then develop the proper methodology to implement them. Finally, it will disseminate the use of Bayesian markets via applications.
The first application will demonstrate how degrees of expertise can be measured and will apply it to risks related to climate change and nuclear power plants. It will contribute to the political debate by shedding new light on what true experts think about these risks. The second application will provide the first incentivized measures of life satisfaction and happiness.
Summary
Subjective data play an increasing role in modern economics. For instance, new welfare measurements are based on people’s subjective assessments of their happiness or their life satisfaction. A problem of such measurements is that people have no incentives to tell the truth. To solve this problem and make those measurements incentive compatible, I will introduce a new market institution, called Bayesian markets.
Imagine we ask people whether they are happy with their life. On Bayesian markets, they will trade an asset whose value is the proportion of people answering Yes. Only those answering Yes will have the right to buy the asset and those answering No the right to sell it. Bayesian updating implies that “Yes” agents predict a higher value of the asset than “No” agents do and, consequently, “Yes” agents want to buy it while “No” agents want to sell it. I will show that truth-telling is then the optimal strategy.
Bayesian markets reward truth-telling the same way as prediction markets (betting markets) reward people for reporting their true subjective probabilities about observable events. Yet, unlike prediction markets, they do not require events to be objectively observable. Bayesian markets apply to any type of unverifiable truths, from one’s own happiness to beliefs about events that will never be observed.
The present research program will first establish the theoretical foundations of Bayesian markets. It will then develop the proper methodology to implement them. Finally, it will disseminate the use of Bayesian markets via applications.
The first application will demonstrate how degrees of expertise can be measured and will apply it to risks related to climate change and nuclear power plants. It will contribute to the political debate by shedding new light on what true experts think about these risks. The second application will provide the first incentivized measures of life satisfaction and happiness.
Max ERC Funding
1 500 000 €
Duration
Start date: 2016-01-01, End date: 2020-12-31
Project acronym BREATHE
Project Biochemically modified messenger RNA encoding nucleases for in vivo gene correction of severe inherited lung diseases
Researcher (PI) Michael Kormann
Host Institution (HI) EBERHARD KARLS UNIVERSITAET TUEBINGEN
Call Details Starting Grant (StG), LS7, ERC-2014-STG
Summary Surfactant Protein B (SP-B) deficiency and Cystic Fibrosis (CF) are severe, fatal inherited diseases affecting the lungs of ten thousands of people, for which there is currently no available cure. Although gene therapy is a promising therapeutic approach, various technical problems, including numerous physical and immune-mediated barriers, have prevented successful application to date. My recent studies were the first to demonstrate the life-saving efficacy of repeated pulmonary delivery of chemically modified messenger RNA (mRNA) in a mouse model of congenital SP-B deficiency. By incorporating balanced amounts of modified nucleotides to mimic endogenous transcripts, I developed a safe and therapeutically efficient vehicle for lung transfection that eliminates the risk of genomic integration commonly associated with DNA-based vectors. I also assessed the delivery of mRNA-encoded site-specific nucleases to the lung to facilitate targeted gene correction of the underlying disease-causing mutations. In comprehensive studies, we show that a single application of nucleases encoded by nucleotide-modified RNA (nec-mRNA) can generate in vivo correction of terminally differentiated alveolar type II cells, which more than quadrupled the life span of SP-B deficient mice. Together with my working group, I aim to further develop this technology to enhance the efficiency and safety of nec-mRNA-mediated in vivo lung stem cell targeting, providing an ultimate cure by permanent correction. Specifically, we will test this approach in humanized mouse models of SP-B deficiency and CF. Developing and genetically engineering humanized models in vivo will be a critical step towards the safe translation of mRNA based nuclease technology to the clinic. With my competitive edge in lung-transfection technology and strong data, I feel that my group is uniquely suited to achieve these goals and to make a highly valuable contribution to the development of an efficient treatment.
Summary
Surfactant Protein B (SP-B) deficiency and Cystic Fibrosis (CF) are severe, fatal inherited diseases affecting the lungs of ten thousands of people, for which there is currently no available cure. Although gene therapy is a promising therapeutic approach, various technical problems, including numerous physical and immune-mediated barriers, have prevented successful application to date. My recent studies were the first to demonstrate the life-saving efficacy of repeated pulmonary delivery of chemically modified messenger RNA (mRNA) in a mouse model of congenital SP-B deficiency. By incorporating balanced amounts of modified nucleotides to mimic endogenous transcripts, I developed a safe and therapeutically efficient vehicle for lung transfection that eliminates the risk of genomic integration commonly associated with DNA-based vectors. I also assessed the delivery of mRNA-encoded site-specific nucleases to the lung to facilitate targeted gene correction of the underlying disease-causing mutations. In comprehensive studies, we show that a single application of nucleases encoded by nucleotide-modified RNA (nec-mRNA) can generate in vivo correction of terminally differentiated alveolar type II cells, which more than quadrupled the life span of SP-B deficient mice. Together with my working group, I aim to further develop this technology to enhance the efficiency and safety of nec-mRNA-mediated in vivo lung stem cell targeting, providing an ultimate cure by permanent correction. Specifically, we will test this approach in humanized mouse models of SP-B deficiency and CF. Developing and genetically engineering humanized models in vivo will be a critical step towards the safe translation of mRNA based nuclease technology to the clinic. With my competitive edge in lung-transfection technology and strong data, I feel that my group is uniquely suited to achieve these goals and to make a highly valuable contribution to the development of an efficient treatment.
Max ERC Funding
1 497 125 €
Duration
Start date: 2015-04-01, End date: 2020-03-31
Project acronym COAT
Project Collapse Of Atmospheric Turbulence
Researcher (PI) Bas Johannes Henricus Van de wiel
Host Institution (HI) TECHNISCHE UNIVERSITEIT DELFT
Call Details Consolidator Grant (CoG), PE10, ERC-2014-CoG
Summary This project aims to predict the cessation of continuous turbulence in the evening boundary layer. The interaction between the lower atmosphere and the surface is studied in detail, as this plays a crucial role in the dynamics. Present generation forecasting models are incapable to predict whether or not turbulence will survive or collapse under cold conditions. In nature, both situations frequently occur and lead to completely different temperature signatures. As such, significant forecast errors are made, particularly in arctic regions and winter conditions. Therefore, prediction of turbulence collapse is highly relevant for weather and climate prediction.
Key innovation lies in our hypothesis. The collapse of turbulence is explained from a maximum sustainable heat flux hypothesis which foresees in an enforcing positive feedback between the atmosphere and the underlying surface. A comprehensive theory for the transition between the main two nocturnal regimes would be ground-breaking in meteorological literature.
We propose an integrated approach, which combines in-depth theoretical work, simulation with models of various hierarchy (DNS, LES, RANS), and observational analysis. Such comprehensive methodology is new with respect to the problem at hand. An innovative element is the usage of Direct Numerical Simulation in combination with dynamical surface interactions. This advanced technique fully resolves turbulent motions up to their smallest scale without the need to rely on subgrid closure assumptions. From a 10-year dataset (200m mast at Cabauw, Netherlands) nights are classified according to their turbulence characteristics. Multi-night composites are used as benchmark-cases to guide realistic numerical modelling. In the validation phase, generality of the results with respect to both climate and surface characteristics is assessed by comparison with the FLUXNET data-consortium, which operates on a long-term basis over 240 sites across the globe.
Summary
This project aims to predict the cessation of continuous turbulence in the evening boundary layer. The interaction between the lower atmosphere and the surface is studied in detail, as this plays a crucial role in the dynamics. Present generation forecasting models are incapable to predict whether or not turbulence will survive or collapse under cold conditions. In nature, both situations frequently occur and lead to completely different temperature signatures. As such, significant forecast errors are made, particularly in arctic regions and winter conditions. Therefore, prediction of turbulence collapse is highly relevant for weather and climate prediction.
Key innovation lies in our hypothesis. The collapse of turbulence is explained from a maximum sustainable heat flux hypothesis which foresees in an enforcing positive feedback between the atmosphere and the underlying surface. A comprehensive theory for the transition between the main two nocturnal regimes would be ground-breaking in meteorological literature.
We propose an integrated approach, which combines in-depth theoretical work, simulation with models of various hierarchy (DNS, LES, RANS), and observational analysis. Such comprehensive methodology is new with respect to the problem at hand. An innovative element is the usage of Direct Numerical Simulation in combination with dynamical surface interactions. This advanced technique fully resolves turbulent motions up to their smallest scale without the need to rely on subgrid closure assumptions. From a 10-year dataset (200m mast at Cabauw, Netherlands) nights are classified according to their turbulence characteristics. Multi-night composites are used as benchmark-cases to guide realistic numerical modelling. In the validation phase, generality of the results with respect to both climate and surface characteristics is assessed by comparison with the FLUXNET data-consortium, which operates on a long-term basis over 240 sites across the globe.
Max ERC Funding
1 659 580 €
Duration
Start date: 2016-01-01, End date: 2020-12-31
Project acronym COMBIOSCOPY
Project Computational Biophotonics for Endoscopic Cancer Diagnosis and Therapy
Researcher (PI) Lena Maier-Hein
Host Institution (HI) DEUTSCHES KREBSFORSCHUNGSZENTRUM HEIDELBERG
Call Details Starting Grant (StG), LS7, ERC-2014-STG
Summary Key challenges in endoscopic tumor diagnosis and therapy consist of the detection and discrimination of malignant tissue as well as the precise navigation of medical instruments. Currently, a low level of sensitivity and specificity in tumor detection and lack of global orientation lead to both over- and undertreatment, tumor recurrence, intra-operative complications, and high costs. The goal of this multidisciplinary project is to revolutionize clinical endoscopic imaging based on the systematic integration of two new but independant fields of research up until this point: Biophotonics and computer-assisted interventions (COMputational BIOphotonics in endoSCOPY).
For the first time, quantitative multi-modal imaging biomarkers based on structural and functional data are being developed to enhance the physician’s view by providing information that cannot be seen with the naked eye. To this extent, white light images co-registered with multispectral optical and photoacoustic images will be processed in a combined manner to dynamically reconstruct not only the visible surface in 3D but also subsurface anatomical and functional detail such as 3D vessel topology, blood volume and oxygenation. Spatio-temporal registration of multi-modal data acquired before and during the procedure will enable (1) the highly specific local tissue classification and discrimination based on tissue shape, texture, function and radiological contrast imagery as well as (2) global context-aware instrument guidance.
This innovative approach to radiation-free real-time imaging will be implemented and evaluated by means of computer-assisted colonoscopy and laparoscopy. The potential socioeconomic impact of providing high precision minimally-invasive tumor diagnosis and therapy at low cost is extremely high.
Summary
Key challenges in endoscopic tumor diagnosis and therapy consist of the detection and discrimination of malignant tissue as well as the precise navigation of medical instruments. Currently, a low level of sensitivity and specificity in tumor detection and lack of global orientation lead to both over- and undertreatment, tumor recurrence, intra-operative complications, and high costs. The goal of this multidisciplinary project is to revolutionize clinical endoscopic imaging based on the systematic integration of two new but independant fields of research up until this point: Biophotonics and computer-assisted interventions (COMputational BIOphotonics in endoSCOPY).
For the first time, quantitative multi-modal imaging biomarkers based on structural and functional data are being developed to enhance the physician’s view by providing information that cannot be seen with the naked eye. To this extent, white light images co-registered with multispectral optical and photoacoustic images will be processed in a combined manner to dynamically reconstruct not only the visible surface in 3D but also subsurface anatomical and functional detail such as 3D vessel topology, blood volume and oxygenation. Spatio-temporal registration of multi-modal data acquired before and during the procedure will enable (1) the highly specific local tissue classification and discrimination based on tissue shape, texture, function and radiological contrast imagery as well as (2) global context-aware instrument guidance.
This innovative approach to radiation-free real-time imaging will be implemented and evaluated by means of computer-assisted colonoscopy and laparoscopy. The potential socioeconomic impact of providing high precision minimally-invasive tumor diagnosis and therapy at low cost is extremely high.
Max ERC Funding
1 499 699 €
Duration
Start date: 2015-07-01, End date: 2020-06-30
Project acronym COSMIC
Project Commitment, maturation and infectivity of sexual stage malaria parasites in natural infections
Researcher (PI) Jan Teun Bousema
Host Institution (HI) STICHTING KATHOLIEKE UNIVERSITEIT
Call Details Starting Grant (StG), LS7, ERC-2014-STG
Summary Background: One of the major challenges for malaria control and elimination is the phenomenally efficient spread of malaria through sexual stage malaria parasites (gametocytes). The epidemiology and dynamics of gametocytes are poorly understood: it is presently unknown when commitment to gametocytes first occurs during infections and what intrinsic or extrinsic factors influence gametocyte production and infectivity to mosquitoes.
I hypothesize that continuous early commitment to gametocyte production and the preferential sequestration of mature gametocytes in the subdermal vasculature are key to explaining the high efficiency of malaria transmission.
Aim: This proposal has three main aims: i) to determine when commitment to gametocyte production first occurs during experimental and natural infections; ii) to delineate environmental triggers that stimulate gametocyte production in the absence and presence of treatment; iii) to quantify the differential distribution of parasite developmental stages in different compartments of the human bloodstream.
Approach: We will use novel parasite stage composition assays in combination with epidemiological methods to determine the dynamics of gametocyte commitment and maturation during controlled malaria infections in malaria-naive volunteers and during naturally acquired malaria infections in cohorts exposed to malaria in Burkina Faso. A stage-specific immunohistochemistry assay will, for the first time, directly quantify malaria stage composition in the subdermal vasculature and mosquito bloodmeals and allow comparison with other compartments of the circulation.
Importance and Innovation: This is the first study to comprehensively characterize gametocyte commitment, maturation and infectivity in experimental and natural infections. This proposal will provide insight in one of the most important questions for malaria elimination: what processes are responsible for the phenomenally efficient transmission of malaria.
Summary
Background: One of the major challenges for malaria control and elimination is the phenomenally efficient spread of malaria through sexual stage malaria parasites (gametocytes). The epidemiology and dynamics of gametocytes are poorly understood: it is presently unknown when commitment to gametocytes first occurs during infections and what intrinsic or extrinsic factors influence gametocyte production and infectivity to mosquitoes.
I hypothesize that continuous early commitment to gametocyte production and the preferential sequestration of mature gametocytes in the subdermal vasculature are key to explaining the high efficiency of malaria transmission.
Aim: This proposal has three main aims: i) to determine when commitment to gametocyte production first occurs during experimental and natural infections; ii) to delineate environmental triggers that stimulate gametocyte production in the absence and presence of treatment; iii) to quantify the differential distribution of parasite developmental stages in different compartments of the human bloodstream.
Approach: We will use novel parasite stage composition assays in combination with epidemiological methods to determine the dynamics of gametocyte commitment and maturation during controlled malaria infections in malaria-naive volunteers and during naturally acquired malaria infections in cohorts exposed to malaria in Burkina Faso. A stage-specific immunohistochemistry assay will, for the first time, directly quantify malaria stage composition in the subdermal vasculature and mosquito bloodmeals and allow comparison with other compartments of the circulation.
Importance and Innovation: This is the first study to comprehensively characterize gametocyte commitment, maturation and infectivity in experimental and natural infections. This proposal will provide insight in one of the most important questions for malaria elimination: what processes are responsible for the phenomenally efficient transmission of malaria.
Max ERC Funding
1 500 000 €
Duration
Start date: 2015-07-01, End date: 2020-06-30
Project acronym EdGe
Project The molecular genetic architecture of educational attainment and its significance for cognitive health
Researcher (PI) Philipp Daniel Koellinger
Host Institution (HI) STICHTING VU
Call Details Consolidator Grant (CoG), SH1, ERC-2014-CoG
Summary Since many social and economic outcomes are moderately heritable, it is in principle possible to discover genetic variants associated with them. Such discoveries could yield new insights into the causal pathways underlying human behaviour, the complex interplay of environmental and genetic factors, and the relationship between socio-economic traits and health.
This proposal builds on a recent genome-wide association study on educational attainment (EA) led by the applicant (Rietveld et al. 2013, Science), which identified for the first time specific genetic variants robustly associated with a socio-economic outcome. The project will leverage the unique resources of the Social Science Genetic Association Consortium (SSGAC), which is co-led by the applicant.
The proposed research will extend existing knowledge by: 1) discovering additional genetic variants and causal pathways associated with EA; 2) developing methods to use the available genetic association results in novel, more efficient ways; 3) shedding new light on characteristics related to EA such as economic preferences, cognitive function, and cognitive health; 4) showing how policies promoting EA interact with genetic predisposition; 5) using genetic information to better understand the causal effects of educational policy interventions, 6) developing better tools to identify individuals at risk for cognition-related diseases before the onset of symptoms; and 7) identifying causal pathways of genetic influence on cognitive health via neurobiological measures. The project aims to elucidate the complex causal pathways connecting genes, environment, individual characteristics, and health-related outcomes; make methodological contributions applicable in genetic epidemiology and the social sciences; and contribute towards designing more effective public policy, which could improve public health and lower health costs.
Summary
Since many social and economic outcomes are moderately heritable, it is in principle possible to discover genetic variants associated with them. Such discoveries could yield new insights into the causal pathways underlying human behaviour, the complex interplay of environmental and genetic factors, and the relationship between socio-economic traits and health.
This proposal builds on a recent genome-wide association study on educational attainment (EA) led by the applicant (Rietveld et al. 2013, Science), which identified for the first time specific genetic variants robustly associated with a socio-economic outcome. The project will leverage the unique resources of the Social Science Genetic Association Consortium (SSGAC), which is co-led by the applicant.
The proposed research will extend existing knowledge by: 1) discovering additional genetic variants and causal pathways associated with EA; 2) developing methods to use the available genetic association results in novel, more efficient ways; 3) shedding new light on characteristics related to EA such as economic preferences, cognitive function, and cognitive health; 4) showing how policies promoting EA interact with genetic predisposition; 5) using genetic information to better understand the causal effects of educational policy interventions, 6) developing better tools to identify individuals at risk for cognition-related diseases before the onset of symptoms; and 7) identifying causal pathways of genetic influence on cognitive health via neurobiological measures. The project aims to elucidate the complex causal pathways connecting genes, environment, individual characteristics, and health-related outcomes; make methodological contributions applicable in genetic epidemiology and the social sciences; and contribute towards designing more effective public policy, which could improve public health and lower health costs.
Max ERC Funding
1 870 135 €
Duration
Start date: 2015-09-01, End date: 2020-08-31
Project acronym EMBRYOandLATERHEALTH
Project Embryonic origins of cardiovascular health in later life: disentangling early causal pathways in a lifecourse perspective
Researcher (PI) Vincent Wilfred Vishal-Kapoor Jaddoe
Host Institution (HI) ERASMUS UNIVERSITAIR MEDISCH CENTRUM ROTTERDAM
Call Details Consolidator Grant (CoG), LS7, ERC-2014-CoG
Summary Children born preterm or with a small size at birth have increased risks of cardiovascular disease and type 2 diabetes in adulthood. These intriguing associations strongly suggest that common diseases have at least part of their origins in early fetal life. From both an etiological and preventive perspective, it is important to disentangle the early fetal critical periods and causal pathways. An accumulating body of evidence suggests that early pregnancy, or even the preconception period, may influence the risk of cardiovascular and metabolic disease throughout the lifecourse. The main hypothesis for this project is that adverse exposures before or very early in pregnancy induce embryonic and placental developmental adaptations, which permanently affect cardiovascular and metabolic development and predispose individuals to both adverse outcomes at birth and cardiovascular and metabolic dysfunction and diseases in later life. I will use an integrated epidemiological, molecular and clinical full lifecourse approach from preconception to adulthood embedded in three population-based cohort studies. Innovative element are: 1) focus on developmental adaptations during the embryonic phase and early placentation assessed by advanced imaging studies at 6, 8, 10 and 12 weeks of gestation; (2) detailed cardiovascular and metabolic studies in infancy and late childhood, including 3T MRI of the heart, aorta, liver and abdomen, metabolomics analyses; and (3) genome-wide DNA-methylation studies to identify specific DNA-methylation changes related to preconception or early pregnancy exposures, which persist in late childhood and adulthood and are associated with cardiovascular and metabolic outcomes in later life. With these approaches, this project will provide unique and important new perspectives into the earliest origins of cardiovascular disease and type 2 diabetes and will ultimately contribute to development of preventive strategies focused on future parents and children.
Summary
Children born preterm or with a small size at birth have increased risks of cardiovascular disease and type 2 diabetes in adulthood. These intriguing associations strongly suggest that common diseases have at least part of their origins in early fetal life. From both an etiological and preventive perspective, it is important to disentangle the early fetal critical periods and causal pathways. An accumulating body of evidence suggests that early pregnancy, or even the preconception period, may influence the risk of cardiovascular and metabolic disease throughout the lifecourse. The main hypothesis for this project is that adverse exposures before or very early in pregnancy induce embryonic and placental developmental adaptations, which permanently affect cardiovascular and metabolic development and predispose individuals to both adverse outcomes at birth and cardiovascular and metabolic dysfunction and diseases in later life. I will use an integrated epidemiological, molecular and clinical full lifecourse approach from preconception to adulthood embedded in three population-based cohort studies. Innovative element are: 1) focus on developmental adaptations during the embryonic phase and early placentation assessed by advanced imaging studies at 6, 8, 10 and 12 weeks of gestation; (2) detailed cardiovascular and metabolic studies in infancy and late childhood, including 3T MRI of the heart, aorta, liver and abdomen, metabolomics analyses; and (3) genome-wide DNA-methylation studies to identify specific DNA-methylation changes related to preconception or early pregnancy exposures, which persist in late childhood and adulthood and are associated with cardiovascular and metabolic outcomes in later life. With these approaches, this project will provide unique and important new perspectives into the earliest origins of cardiovascular disease and type 2 diabetes and will ultimately contribute to development of preventive strategies focused on future parents and children.
Max ERC Funding
1 969 586 €
Duration
Start date: 2015-09-01, End date: 2020-08-31
