Project acronym 3D-OA-HISTO
Project Development of 3D Histopathological Grading of Osteoarthritis
Researcher (PI) Simo Jaakko Saarakkala
Host Institution (HI) OULUN YLIOPISTO
Country Finland
Call Details Starting Grant (StG), LS7, ERC-2013-StG
Summary "Background: Osteoarthritis (OA) is a common musculoskeletal disease occurring worldwide. Despite extensive research, etiology of OA is still poorly understood. Histopathological grading (HPG) of 2D tissue sections is the gold standard reference method for determination of OA stage. However, traditional 2D-HPG is destructive and based only on subjective visual evaluation. These limitations induce bias to clinical in vitro OA diagnostics and basic research that both rely strongly on HPG.
Objectives: 1) To establish and validate the very first 3D-HPG of OA based on cutting-edge nano/micro-CT (Computed Tomography) technologies in vitro; 2) To use the established method to clarify the beginning phases of OA; and 3) To validate 3D-HPG of OA for in vivo use.
Methods: Several hundreds of human osteochondral samples from patients undergoing total knee arthroplasty will be collected. The samples will be imaged in vitro with nano/micro-CT and clinical high-end extremity CT devices using specific contrast-agents to quantify tissue constituents and structure in 3D in large volume. From this information, a novel 3D-HPG is developed with statistical classification algorithms. Finally, the developed novel 3D-HPG of OA will be applied clinically in vivo.
Significance: This is the very first study to establish 3D-HPG of OA pathology in vitro and in vivo. Furthermore, the developed technique hugely improves the understanding of the beginning phases of OA. Ultimately, the study will contribute for improving OA patients’ quality of life by slowing the disease progression, and for providing powerful tools to develop new OA therapies."
Summary
"Background: Osteoarthritis (OA) is a common musculoskeletal disease occurring worldwide. Despite extensive research, etiology of OA is still poorly understood. Histopathological grading (HPG) of 2D tissue sections is the gold standard reference method for determination of OA stage. However, traditional 2D-HPG is destructive and based only on subjective visual evaluation. These limitations induce bias to clinical in vitro OA diagnostics and basic research that both rely strongly on HPG.
Objectives: 1) To establish and validate the very first 3D-HPG of OA based on cutting-edge nano/micro-CT (Computed Tomography) technologies in vitro; 2) To use the established method to clarify the beginning phases of OA; and 3) To validate 3D-HPG of OA for in vivo use.
Methods: Several hundreds of human osteochondral samples from patients undergoing total knee arthroplasty will be collected. The samples will be imaged in vitro with nano/micro-CT and clinical high-end extremity CT devices using specific contrast-agents to quantify tissue constituents and structure in 3D in large volume. From this information, a novel 3D-HPG is developed with statistical classification algorithms. Finally, the developed novel 3D-HPG of OA will be applied clinically in vivo.
Significance: This is the very first study to establish 3D-HPG of OA pathology in vitro and in vivo. Furthermore, the developed technique hugely improves the understanding of the beginning phases of OA. Ultimately, the study will contribute for improving OA patients’ quality of life by slowing the disease progression, and for providing powerful tools to develop new OA therapies."
Max ERC Funding
1 500 000 €
Duration
Start date: 2014-02-01, End date: 2019-01-31
Project acronym 3Ps
Project 3Ps
Plastic-Antibodies, Plasmonics and Photovoltaic-Cells: on-site screening of cancer biomarkers made possible
Researcher (PI) Maria Goreti Ferreira Sales
Host Institution (HI) INSTITUTO SUPERIOR DE ENGENHARIA DO PORTO
Country Portugal
Call Details Starting Grant (StG), LS7, ERC-2012-StG_20111109
Summary This project presents a new concept for the detection, diagnosis and monitoring of cancer biomarker patterns in point-of-care. The device under development will make use of the selectivity of the plastic antibodies as sensing materials and the interference they will play on the normal operation of a photovoltaic cell.
Plastic antibodies will be designed by surface imprinting procedures. Self-assembled monolayer and molecular imprinting techniques will be merged in this process because they allow the self-assembly of nanostructured materials on a “bottom-up” nanofabrication approach. A dye-sensitized solar cell will be used as photovoltaic cell. It includes a liquid interface in the cell circuit, which allows the introduction of the sample (also in liquid phase) without disturbing the normal cell operation. Furthermore, it works well with rather low cost materials and requires mild and easy processing conditions. The cell will be equipped with plasmonic structures to enhance light absorption and cell efficiency.
The device under development will be easily operated by any clinician or patient. It will require ambient light and a regular multimeter. Eye detection will be also tried out.
Summary
This project presents a new concept for the detection, diagnosis and monitoring of cancer biomarker patterns in point-of-care. The device under development will make use of the selectivity of the plastic antibodies as sensing materials and the interference they will play on the normal operation of a photovoltaic cell.
Plastic antibodies will be designed by surface imprinting procedures. Self-assembled monolayer and molecular imprinting techniques will be merged in this process because they allow the self-assembly of nanostructured materials on a “bottom-up” nanofabrication approach. A dye-sensitized solar cell will be used as photovoltaic cell. It includes a liquid interface in the cell circuit, which allows the introduction of the sample (also in liquid phase) without disturbing the normal cell operation. Furthermore, it works well with rather low cost materials and requires mild and easy processing conditions. The cell will be equipped with plasmonic structures to enhance light absorption and cell efficiency.
The device under development will be easily operated by any clinician or patient. It will require ambient light and a regular multimeter. Eye detection will be also tried out.
Max ERC Funding
998 584 €
Duration
Start date: 2013-02-01, End date: 2018-01-31
Project acronym A-LIFE
Project Absorbing aerosol layers in a changing climate: aging, lifetime and dynamics
Researcher (PI) Bernadett Barbara Weinzierl
Host Institution (HI) UNIVERSITAT WIEN
Country Austria
Call Details Starting Grant (StG), PE10, ERC-2014-STG
Summary Aerosols (i.e. tiny particles suspended in the air) are regularly transported in huge amounts over long distances impacting air quality, health, weather and climate thousands of kilometers downwind of the source. Aerosols affect the atmospheric radiation budget through scattering and absorption of solar radiation and through their role as cloud/ice nuclei.
In particular, light absorption by aerosol particles such as mineral dust and black carbon (BC; thought to be the second strongest contribution to current global warming after CO2) is of fundamental importance from a climate perspective because the presence of absorbing particles (1) contributes to solar radiative forcing, (2) heats absorbing aerosol layers, (3) can evaporate clouds and (4) change atmospheric dynamics.
Considering this prominent role of aerosols, vertically-resolved in-situ data on absorbing aerosols are surprisingly scarce and aerosol-dynamic interactions are poorly understood in general. This is, as recognized in the last IPCC report, a serious barrier for taking the accuracy of climate models and predictions to the next level. To overcome this barrier, I propose to investigate aging, lifetime and dynamics of absorbing aerosol layers with a holistic end-to-end approach including laboratory studies, airborne field experiments and numerical model simulations.
Building on the internationally recognized results of my aerosol research group and my long-term experience with airborne aerosol measurements, the time seems ripe to systematically bridge the gap between in-situ measurements of aerosol microphysical and optical properties and the assessment of dynamical interactions of absorbing particles with aerosol layer lifetime through model simulations.
The outcomes of this project will provide fundamental new understanding of absorbing aerosol layers in the climate system and important information for addressing the benefits of BC emission controls for mitigating climate change.
Summary
Aerosols (i.e. tiny particles suspended in the air) are regularly transported in huge amounts over long distances impacting air quality, health, weather and climate thousands of kilometers downwind of the source. Aerosols affect the atmospheric radiation budget through scattering and absorption of solar radiation and through their role as cloud/ice nuclei.
In particular, light absorption by aerosol particles such as mineral dust and black carbon (BC; thought to be the second strongest contribution to current global warming after CO2) is of fundamental importance from a climate perspective because the presence of absorbing particles (1) contributes to solar radiative forcing, (2) heats absorbing aerosol layers, (3) can evaporate clouds and (4) change atmospheric dynamics.
Considering this prominent role of aerosols, vertically-resolved in-situ data on absorbing aerosols are surprisingly scarce and aerosol-dynamic interactions are poorly understood in general. This is, as recognized in the last IPCC report, a serious barrier for taking the accuracy of climate models and predictions to the next level. To overcome this barrier, I propose to investigate aging, lifetime and dynamics of absorbing aerosol layers with a holistic end-to-end approach including laboratory studies, airborne field experiments and numerical model simulations.
Building on the internationally recognized results of my aerosol research group and my long-term experience with airborne aerosol measurements, the time seems ripe to systematically bridge the gap between in-situ measurements of aerosol microphysical and optical properties and the assessment of dynamical interactions of absorbing particles with aerosol layer lifetime through model simulations.
The outcomes of this project will provide fundamental new understanding of absorbing aerosol layers in the climate system and important information for addressing the benefits of BC emission controls for mitigating climate change.
Max ERC Funding
1 987 980 €
Duration
Start date: 2015-10-01, End date: 2021-09-30
Project acronym ABINITIODGA
Project Ab initio Dynamical Vertex Approximation
Researcher (PI) Karsten Held
Host Institution (HI) TECHNISCHE UNIVERSITAET WIEN
Country Austria
Call Details Starting Grant (StG), PE3, ERC-2012-StG_20111012
Summary Some of the most fascinating physical phenomena are experimentally observed in strongly correlated electron systems and, on the theoretical side, only poorly understood hitherto. The aim of the ERC project AbinitioDGA is the development, implementation and application of a new, 21th century method for the ab initio calculation of materials with such strong electronic correlations. AbinitioDGA includes strong electronic correlations on all time and length scales and hence is a big step beyond the state-of-the-art methods, such as the local density approximation, dynamical mean field theory, and the GW approach (Green function G times screened interaction W). It has the potential for an extraordinary high impact not only in the field of computational materials science but also for a better understanding of quantum critical heavy fermion systems, high-temperature superconductors, and transport through nano- and heterostructures. These four physical problems and related materials will be studied within the ERC project, besides the methodological development.
On the technical side, AbinitioDGA realizes Hedin's idea to include vertex corrections beyond the GW approximation. All vertex corrections which can be traced back to a fully irreducible local vertex and the bare non-local Coulomb interaction are included. This way, AbinitioDGA does not only contain the GW physics of screened exchange and the strong local correlations of dynamical mean field theory but also non-local correlations beyond on all length scales. Through the latter, AbinitioDGA can prospectively describe phenomena such as quantum criticality, spin-fluctuation mediated superconductivity, and weak localization corrections to the conductivity. Nonetheless, the computational effort is still manageable even for realistic materials calculations, making the considerable effort to implement AbinitioDGA worthwhile.
Summary
Some of the most fascinating physical phenomena are experimentally observed in strongly correlated electron systems and, on the theoretical side, only poorly understood hitherto. The aim of the ERC project AbinitioDGA is the development, implementation and application of a new, 21th century method for the ab initio calculation of materials with such strong electronic correlations. AbinitioDGA includes strong electronic correlations on all time and length scales and hence is a big step beyond the state-of-the-art methods, such as the local density approximation, dynamical mean field theory, and the GW approach (Green function G times screened interaction W). It has the potential for an extraordinary high impact not only in the field of computational materials science but also for a better understanding of quantum critical heavy fermion systems, high-temperature superconductors, and transport through nano- and heterostructures. These four physical problems and related materials will be studied within the ERC project, besides the methodological development.
On the technical side, AbinitioDGA realizes Hedin's idea to include vertex corrections beyond the GW approximation. All vertex corrections which can be traced back to a fully irreducible local vertex and the bare non-local Coulomb interaction are included. This way, AbinitioDGA does not only contain the GW physics of screened exchange and the strong local correlations of dynamical mean field theory but also non-local correlations beyond on all length scales. Through the latter, AbinitioDGA can prospectively describe phenomena such as quantum criticality, spin-fluctuation mediated superconductivity, and weak localization corrections to the conductivity. Nonetheless, the computational effort is still manageable even for realistic materials calculations, making the considerable effort to implement AbinitioDGA worthwhile.
Max ERC Funding
1 491 090 €
Duration
Start date: 2013-01-01, End date: 2018-07-31
Project acronym activeFly
Project Circuit mechanisms of self-movement estimation during walking
Researcher (PI) M Eugenia CHIAPPE
Host Institution (HI) FUNDACAO D. ANNA SOMMER CHAMPALIMAUD E DR. CARLOS MONTEZ CHAMPALIMAUD
Country Portugal
Call Details Starting Grant (StG), LS5, ERC-2017-STG
Summary The brain evolves, develops, and operates in the context of animal movements. As a consequence, fundamental brain functions such as spatial perception and motor control critically depend on the precise knowledge of the ongoing body motion. An accurate internal estimate of self-movement is thought to emerge from sensorimotor integration; nonetheless, which circuits perform this internal estimation, and exactly how motor-sensory coordination is implemented within these circuits are basic questions that remain to be poorly understood. There is growing evidence suggesting that, during locomotion, motor-related and visual signals interact at early stages of visual processing. In mammals, however, it is not clear what the function of this interaction is. Recently, we have shown that a population of Drosophila optic-flow processing neurons —neurons that are sensitive to self-generated visual flow, receives convergent visual and walking-related signals to form a faithful representation of the fly’s walking movements. Leveraging from these results, and combining quantitative analysis of behavior with physiology, optogenetics, and modelling, we propose to investigate circuit mechanisms of self-movement estimation during walking. We will:1) use cell specific manipulations to identify what cells are necessary to generate the motor-related activity in the population of visual neurons, 2) record from the identified neurons and correlate their activity with specific locomotor parameters, and 3) perturb the activity of different cell-types within the identified circuits to test their role in the dynamics of the visual neurons, and on the fly’s walking behavior. These experiments will establish unprecedented causal relationships among neural activity, the formation of an internal representation, and locomotor control. The identified sensorimotor principles will establish a framework that can be tested in other scenarios or animal systems with implications both in health and disease.
Summary
The brain evolves, develops, and operates in the context of animal movements. As a consequence, fundamental brain functions such as spatial perception and motor control critically depend on the precise knowledge of the ongoing body motion. An accurate internal estimate of self-movement is thought to emerge from sensorimotor integration; nonetheless, which circuits perform this internal estimation, and exactly how motor-sensory coordination is implemented within these circuits are basic questions that remain to be poorly understood. There is growing evidence suggesting that, during locomotion, motor-related and visual signals interact at early stages of visual processing. In mammals, however, it is not clear what the function of this interaction is. Recently, we have shown that a population of Drosophila optic-flow processing neurons —neurons that are sensitive to self-generated visual flow, receives convergent visual and walking-related signals to form a faithful representation of the fly’s walking movements. Leveraging from these results, and combining quantitative analysis of behavior with physiology, optogenetics, and modelling, we propose to investigate circuit mechanisms of self-movement estimation during walking. We will:1) use cell specific manipulations to identify what cells are necessary to generate the motor-related activity in the population of visual neurons, 2) record from the identified neurons and correlate their activity with specific locomotor parameters, and 3) perturb the activity of different cell-types within the identified circuits to test their role in the dynamics of the visual neurons, and on the fly’s walking behavior. These experiments will establish unprecedented causal relationships among neural activity, the formation of an internal representation, and locomotor control. The identified sensorimotor principles will establish a framework that can be tested in other scenarios or animal systems with implications both in health and disease.
Max ERC Funding
1 500 000 €
Duration
Start date: 2017-11-01, End date: 2022-10-31
Project acronym ACTIVENP
Project Active and low loss nano photonics (ActiveNP)
Researcher (PI) Thomas Arno Klar
Host Institution (HI) UNIVERSITAT LINZ
Country Austria
Call Details Starting Grant (StG), PE3, ERC-2010-StG_20091028
Summary This project aims at designing novel hybrid nanophotonic devices comprising metallic nanostructures and active elements such as dye molecules or colloidal quantum dots. Three core objectives, each going far beyond the state of the art, shall be tackled: (i) Metamaterials containing gain materials: Metamaterials introduce magnetism to the optical frequency range and hold promise to create entirely novel devices for light manipulation. Since present day metamaterials are extremely absorptive, it is of utmost importance to fight losses. The ground-breaking approach of this proposal is to incorporate fluorescing species into the nanoscale metallic metastructures in order to compensate losses by stimulated emission. (ii) The second objective exceeds the ansatz of compensating losses and will reach out for lasing action. Individual metallic nanostructures such as pairs of nanoparticles will form novel and unusual nanometre sized resonators for laser action. State of the art microresonators still have a volume of at least half of the wavelength cubed. Noble metal nanoparticle resonators scale down this volume by a factor of thousand allowing for truly nanoscale coherent light sources. (iii) A third objective concerns a substantial improvement of nonlinear effects. This will be accomplished by drastically sharpened resonances of nanoplasmonic devices surrounded by active gain materials. An interdisciplinary team of PhD students and a PostDoc will be assembled, each scientist being uniquely qualified to cover one of the expertise fields: Design, spectroscopy, and simulation. The project s outcome is twofold: A substantial expansion of fundamental understanding of nanophotonics and practical devices such as nanoscopic lasers and low loss metamaterials.
Summary
This project aims at designing novel hybrid nanophotonic devices comprising metallic nanostructures and active elements such as dye molecules or colloidal quantum dots. Three core objectives, each going far beyond the state of the art, shall be tackled: (i) Metamaterials containing gain materials: Metamaterials introduce magnetism to the optical frequency range and hold promise to create entirely novel devices for light manipulation. Since present day metamaterials are extremely absorptive, it is of utmost importance to fight losses. The ground-breaking approach of this proposal is to incorporate fluorescing species into the nanoscale metallic metastructures in order to compensate losses by stimulated emission. (ii) The second objective exceeds the ansatz of compensating losses and will reach out for lasing action. Individual metallic nanostructures such as pairs of nanoparticles will form novel and unusual nanometre sized resonators for laser action. State of the art microresonators still have a volume of at least half of the wavelength cubed. Noble metal nanoparticle resonators scale down this volume by a factor of thousand allowing for truly nanoscale coherent light sources. (iii) A third objective concerns a substantial improvement of nonlinear effects. This will be accomplished by drastically sharpened resonances of nanoplasmonic devices surrounded by active gain materials. An interdisciplinary team of PhD students and a PostDoc will be assembled, each scientist being uniquely qualified to cover one of the expertise fields: Design, spectroscopy, and simulation. The project s outcome is twofold: A substantial expansion of fundamental understanding of nanophotonics and practical devices such as nanoscopic lasers and low loss metamaterials.
Max ERC Funding
1 494 756 €
Duration
Start date: 2010-10-01, End date: 2015-09-30
Project acronym ACTOMYO
Project Mechanisms of actomyosin-based contractility during cytokinesis
Researcher (PI) Ana Costa Xavier de Carvalho
Host Institution (HI) INSTITUTO DE BIOLOGIA MOLECULAR E CELULAR-IBMC
Country Portugal
Call Details Starting Grant (StG), LS3, ERC-2014-STG
Summary Cytokinesis completes cell division by partitioning the contents of the mother cell to the two daughter cells. This process is accomplished through the assembly and constriction of a contractile ring, a complex actomyosin network that remains poorly understood on the molecular level. Research in cytokinesis has overwhelmingly focused on signaling mechanisms that dictate when and where the contractile ring is assembled. By contrast, the research I propose here addresses fundamental questions about the structural and functional properties of the contractile ring itself. We will use the nematode C. elegans to exploit the power of quantitative live imaging assays in an experimentally tractable metazoan organism. The early C. elegans embryo is uniquely suited to the study of the contractile ring, as cells dividing perpendicularly to the imaging plane provide a full end-on view of the contractile ring throughout constriction. This greatly facilitates accurate measurements of constriction kinetics, ring width and thickness, and levels as well as dynamics of fluorescently-tagged contractile ring components. Combining image-based assays with powerful molecular replacement technology for structure-function studies, we will 1) determine the contribution of branched and non-branched actin filament populations to contractile ring formation; 2) explore its ultra-structural organization in collaboration with a world expert in electron microcopy; 3) investigate how the contractile ring network is dynamically remodeled during constriction with the help of a novel laser microsurgery assay that has uncovered a remarkably robust ring repair mechanism; and 4) use a targeted RNAi screen and phenotype profiling to identify new components of actomyosin contractile networks. The results from this interdisciplinary project will significantly enhance our mechanistic understanding of cytokinesis and other cellular processes that involve actomyosin-based contractility.
Summary
Cytokinesis completes cell division by partitioning the contents of the mother cell to the two daughter cells. This process is accomplished through the assembly and constriction of a contractile ring, a complex actomyosin network that remains poorly understood on the molecular level. Research in cytokinesis has overwhelmingly focused on signaling mechanisms that dictate when and where the contractile ring is assembled. By contrast, the research I propose here addresses fundamental questions about the structural and functional properties of the contractile ring itself. We will use the nematode C. elegans to exploit the power of quantitative live imaging assays in an experimentally tractable metazoan organism. The early C. elegans embryo is uniquely suited to the study of the contractile ring, as cells dividing perpendicularly to the imaging plane provide a full end-on view of the contractile ring throughout constriction. This greatly facilitates accurate measurements of constriction kinetics, ring width and thickness, and levels as well as dynamics of fluorescently-tagged contractile ring components. Combining image-based assays with powerful molecular replacement technology for structure-function studies, we will 1) determine the contribution of branched and non-branched actin filament populations to contractile ring formation; 2) explore its ultra-structural organization in collaboration with a world expert in electron microcopy; 3) investigate how the contractile ring network is dynamically remodeled during constriction with the help of a novel laser microsurgery assay that has uncovered a remarkably robust ring repair mechanism; and 4) use a targeted RNAi screen and phenotype profiling to identify new components of actomyosin contractile networks. The results from this interdisciplinary project will significantly enhance our mechanistic understanding of cytokinesis and other cellular processes that involve actomyosin-based contractility.
Max ERC Funding
1 499 989 €
Duration
Start date: 2015-07-01, End date: 2021-12-31
Project acronym Age Asymmetry
Project Age-Selective Segregation of Organelles
Researcher (PI) Pekka Aleksi Katajisto
Host Institution (HI) HELSINGIN YLIOPISTO
Country Finland
Call Details Starting Grant (StG), LS3, ERC-2015-STG
Summary Our tissues are constantly renewed by stem cells. Over time, stem cells accumulate cellular damage that will compromise renewal and results in aging. As stem cells can divide asymmetrically, segregation of harmful factors to the differentiating daughter cell could be one possible mechanism for slowing damage accumulation in the stem cell. However, current evidence for such mechanisms comes mainly from analogous findings in yeast, and studies have concentrated only on few types of cellular damage.
I hypothesize that the chronological age of a subcellular component is a proxy for all the damage it has sustained. In order to secure regeneration, mammalian stem cells may therefore specifically sort old cellular material asymmetrically. To study this, I have developed a novel strategy and tools to address the age-selective segregation of any protein in stem cell division. Using this approach, I have already discovered that stem-like cells of the human mammary epithelium indeed apportion chronologically old mitochondria asymmetrically in cell division, and enrich old mitochondria to the differentiating daughter cell. We will investigate the mechanisms underlying this novel phenomenon, and its relevance for mammalian aging.
We will first identify how old and young mitochondria differ, and how stem cells recognize them to facilitate the asymmetric segregation. Next, we will analyze the extent of asymmetric age-selective segregation by targeting several other subcellular compartments in a stem cell division. Finally, we will determine whether the discovered age-selective segregation is a general property of stem cell in vivo, and it's functional relevance for maintenance of stem cells and tissue regeneration. Our discoveries may open new possibilities to target aging associated functional decline by induction of asymmetric age-selective organelle segregation.
Summary
Our tissues are constantly renewed by stem cells. Over time, stem cells accumulate cellular damage that will compromise renewal and results in aging. As stem cells can divide asymmetrically, segregation of harmful factors to the differentiating daughter cell could be one possible mechanism for slowing damage accumulation in the stem cell. However, current evidence for such mechanisms comes mainly from analogous findings in yeast, and studies have concentrated only on few types of cellular damage.
I hypothesize that the chronological age of a subcellular component is a proxy for all the damage it has sustained. In order to secure regeneration, mammalian stem cells may therefore specifically sort old cellular material asymmetrically. To study this, I have developed a novel strategy and tools to address the age-selective segregation of any protein in stem cell division. Using this approach, I have already discovered that stem-like cells of the human mammary epithelium indeed apportion chronologically old mitochondria asymmetrically in cell division, and enrich old mitochondria to the differentiating daughter cell. We will investigate the mechanisms underlying this novel phenomenon, and its relevance for mammalian aging.
We will first identify how old and young mitochondria differ, and how stem cells recognize them to facilitate the asymmetric segregation. Next, we will analyze the extent of asymmetric age-selective segregation by targeting several other subcellular compartments in a stem cell division. Finally, we will determine whether the discovered age-selective segregation is a general property of stem cell in vivo, and it's functional relevance for maintenance of stem cells and tissue regeneration. Our discoveries may open new possibilities to target aging associated functional decline by induction of asymmetric age-selective organelle segregation.
Max ERC Funding
1 500 000 €
Duration
Start date: 2016-05-01, End date: 2021-04-30
Project acronym AGEMEC
Project Age-dependent mechanisms of sporadic Alzheimer’s Disease in patient-derived neurons
Researcher (PI) Jerome Stefan MERTENS
Host Institution (HI) UNIVERSITAET INNSBRUCK
Country Austria
Call Details Starting Grant (StG), LS5, ERC-2019-STG
Summary Sporadic Alzheimer’s Disease (AD) accounts for the overwhelming majority of all AD cases and exclusively affects people at old age. However, mechanistic links between aging and AD pathology remain elusive. We recently discovered that in contrast to iPSC models, direct conversion of human fibroblasts into induced neurons (iNs) preserves signatures of aging, and we have started to develop a patient-based iN model system for AD. Our preliminary data suggests that AD iNs show a neuronal but de-differentiated transcriptome signature. In this project, we first combine cellular neuroscience assays and epigenetic landscape profiling to understand how neurons in AD fail to maintain their fully mature differentiated state, which might be key in permitting disease development. Next, using metabolome analysis including mass spec metabolite assessment, we explore a profound metabolic switch in AD iNs that shows surprisingly many aspects of aerobic glycolysis observed also in cancer. While this link might represent an interesting connection between two age-dependent and de-differentiation-associated diseases, it also opens new avenues to harness knowledge from the cancer field to better understand sporadic AD. We further focus on identifying and manipulating key metabolic regulators that appear to malfunction in an age-dependent manner, with the ultimate goal to define potential targets and treatment strategies. Finally, we will focus on early AD mechanisms by extending our model to mild cognitive impairment (MCI) patients. An agnostic transcriptome and epigenetic landscape approach of glutamatergic and serotonergic iNs will help to determine the earliest and probably most treatable disease mechanisms of AD, and to better understand the contribution of neuropsychiatric risk factors. We anticipate that this project will help to illuminate the mechanistic interface of cellular aging and the development of AD, and help to define new strategies for AD.
Summary
Sporadic Alzheimer’s Disease (AD) accounts for the overwhelming majority of all AD cases and exclusively affects people at old age. However, mechanistic links between aging and AD pathology remain elusive. We recently discovered that in contrast to iPSC models, direct conversion of human fibroblasts into induced neurons (iNs) preserves signatures of aging, and we have started to develop a patient-based iN model system for AD. Our preliminary data suggests that AD iNs show a neuronal but de-differentiated transcriptome signature. In this project, we first combine cellular neuroscience assays and epigenetic landscape profiling to understand how neurons in AD fail to maintain their fully mature differentiated state, which might be key in permitting disease development. Next, using metabolome analysis including mass spec metabolite assessment, we explore a profound metabolic switch in AD iNs that shows surprisingly many aspects of aerobic glycolysis observed also in cancer. While this link might represent an interesting connection between two age-dependent and de-differentiation-associated diseases, it also opens new avenues to harness knowledge from the cancer field to better understand sporadic AD. We further focus on identifying and manipulating key metabolic regulators that appear to malfunction in an age-dependent manner, with the ultimate goal to define potential targets and treatment strategies. Finally, we will focus on early AD mechanisms by extending our model to mild cognitive impairment (MCI) patients. An agnostic transcriptome and epigenetic landscape approach of glutamatergic and serotonergic iNs will help to determine the earliest and probably most treatable disease mechanisms of AD, and to better understand the contribution of neuropsychiatric risk factors. We anticipate that this project will help to illuminate the mechanistic interface of cellular aging and the development of AD, and help to define new strategies for AD.
Max ERC Funding
1 499 565 €
Duration
Start date: 2020-02-01, End date: 2025-01-31
Project acronym AI-PREVENT
Project A nationwide artificial intelligence risk assessment for primary prevention of cardiometabolic diseases
Researcher (PI) Andrea Ganna
Host Institution (HI) HELSINGIN YLIOPISTO
Country Finland
Call Details Starting Grant (StG), LS7, ERC-2020-STG
Summary Diabetes, stroke and coronary artery disease (cardiometabolic diseases) are the leading cause of death in Europe. Given that effective pharmacological and lifestyle interventions are available, it is important to identify high risk individuals at an early stage. Traditionally, this is done using clinical prediction models. However, the established models have substantial limitations: they are often used by doctors only when an underlying disease is already suspected, they are not developed on updated nationally-representative data and they require time-consuming clinical measurements. Thus, a substantial part of the population is not provided with risk assessment. I propose to revolutionize the existing approaches to primary prevention by providing risk assessment of cardiometabolic diseases before an individual even steps into the doctor’s office for a visit. To this end my project has three main objectives:
1) Development of artificial intelligence (AI) approaches to model health trajectories based on nationwide registry data on medications, diagnoses, familial risk and socio-demographic information to obtain accurate risk estimates for cardiometabolic disease. I will integrate high quality data from selected countries that have long traditions of registry data (Finland and Sweden, over 7.5 million individuals).
2) To identify health trajectories that maximize the clinical utility of genetic scores by integrating genetic and registry-based data on > 1 million people to identify subgroups of individuals for whom genetic information might improve risk prediction.
3) Validation of AI and genetic-based risk assessment as first-stage screening via a clinical study in 2800 individuals.
My project leverages the latest developments in AI and high-quality data of unprecedented scale to deliver a paradigm shift with important public health consequences by potentially changing the way cardiometabolic disease risk is assessed.
Summary
Diabetes, stroke and coronary artery disease (cardiometabolic diseases) are the leading cause of death in Europe. Given that effective pharmacological and lifestyle interventions are available, it is important to identify high risk individuals at an early stage. Traditionally, this is done using clinical prediction models. However, the established models have substantial limitations: they are often used by doctors only when an underlying disease is already suspected, they are not developed on updated nationally-representative data and they require time-consuming clinical measurements. Thus, a substantial part of the population is not provided with risk assessment. I propose to revolutionize the existing approaches to primary prevention by providing risk assessment of cardiometabolic diseases before an individual even steps into the doctor’s office for a visit. To this end my project has three main objectives:
1) Development of artificial intelligence (AI) approaches to model health trajectories based on nationwide registry data on medications, diagnoses, familial risk and socio-demographic information to obtain accurate risk estimates for cardiometabolic disease. I will integrate high quality data from selected countries that have long traditions of registry data (Finland and Sweden, over 7.5 million individuals).
2) To identify health trajectories that maximize the clinical utility of genetic scores by integrating genetic and registry-based data on > 1 million people to identify subgroups of individuals for whom genetic information might improve risk prediction.
3) Validation of AI and genetic-based risk assessment as first-stage screening via a clinical study in 2800 individuals.
My project leverages the latest developments in AI and high-quality data of unprecedented scale to deliver a paradigm shift with important public health consequences by potentially changing the way cardiometabolic disease risk is assessed.
Max ERC Funding
1 550 057 €
Duration
Start date: 2021-01-01, End date: 2025-12-31