Periodic Reporting for period 3 - LONGITOOLS (Dynamic longitudinal exposome trajectories in cardiovascular and metabolic non-communicable diseases)
Berichtszeitraum: 2023-01-01 bis 2024-06-30
Cardiovascular diseases are the leading cause of deaths in the EU, and type 2 diabetes and obesity have reached epidemic proportions worldwide. Together, they form significant economic and service strains on healthcare. On top of this, 20% of all deaths in Europe are related to environmental factors and 400,000 premature deaths per year are due to air pollution.
LongITools is a European Union Horizon 2020 funded research and innovation project, has 18 partners, and is coordinated by the University of Oulu in Finland. The project is studying the interactions between environmental, socioeconomic, lifestyle, and biological factors to determine the risk of developing chronic cardiovascular and metabolic non-communicable diseases. With a focus on air pollution, noise pollution, and the built environment, the project is investigating and measuring how exposure to these factors contribute to the risk of developing diseases such as obesity, type 2 diabetes, heart diseases and atherosclerosis across the life-course.
The project will help develop our understanding of the ‘human exposome’. LongITools is one of nine projects that form the European Human Exposome Network (EHEN), the world’s largest network of projects studying the impact of environmental exposure on human health.
The LongITools researchers will analyse and study huge sets of human data. LongITools uses data from 24 studies, including prospective birth cohort studies and longitudinal studies in adults, register-based cohorts, randomised controlled trials and biobanks, covering the whole life-course from conception through pregnancy to old age, with approximately 11 million participants in total. Using an exposome or holistic-based approach, our research aims to link individual and societal health to the environment to define the disease pathways and the best points during the life-course at which to intervene to reduce the risk of developing a disease.
The LongITools consortium is committed to maximising the impact of its research and appreciate that to do this the results need to be relevant, understandable, and accessible to all stakeholders. The aim is to ensure the research findings, where applicable, contribute to the development of joined up policies and interventions that reduce the risk of developing diseases that cause such huge economic and social burdens.
LongITools is a European Union Horizon 2020 funded research and innovation project, has 18 partners, and is coordinated by the University of Oulu in Finland. The project is studying the interactions between environmental, socioeconomic, lifestyle, and biological factors to determine the risk of developing chronic cardiovascular and metabolic non-communicable diseases. With a focus on air pollution, noise pollution, and the built environment, the project is investigating and measuring how exposure to these factors contribute to the risk of developing diseases such as obesity, type 2 diabetes, heart diseases and atherosclerosis across the life-course.
The project will help develop our understanding of the ‘human exposome’. LongITools is one of nine projects that form the European Human Exposome Network (EHEN), the world’s largest network of projects studying the impact of environmental exposure on human health.
The LongITools researchers will analyse and study huge sets of human data. LongITools uses data from 24 studies, including prospective birth cohort studies and longitudinal studies in adults, register-based cohorts, randomised controlled trials and biobanks, covering the whole life-course from conception through pregnancy to old age, with approximately 11 million participants in total. Using an exposome or holistic-based approach, our research aims to link individual and societal health to the environment to define the disease pathways and the best points during the life-course at which to intervene to reduce the risk of developing a disease.
The LongITools consortium is committed to maximising the impact of its research and appreciate that to do this the results need to be relevant, understandable, and accessible to all stakeholders. The aim is to ensure the research findings, where applicable, contribute to the development of joined up policies and interventions that reduce the risk of developing diseases that cause such huge economic and social burdens.
For the last 54 months (Period 1, 2 and 3) the LongITools project has questioned and studied how the general exposome contribute to explain altered health trajectories associated to the epidemics of cardio-metabolic and -vascular diseases in relevant European regions.
As a project we synergised tasks across the project partners to address our scientific challenges, generated FAIR data and analytical tools and promote best practices for open sciences in exposome research. Together, we further implemented and adapted our road map for exploitation to translate the knowledge gained into greater health and wellbeing in the general population. The project has made quantifiable progresses combining the strengths and expertise of each of its members, supported by effective management, targeted communication strategy and agreed project plans.
Important new findings from the LongITools are arising. Quite consistently we are reporting a compelling body of evidence showing new types of associations between altered urban environments with the prevalence of T2D, obesity and cardiovascular diseases (the current results are subjected to further sensitivity analyses to translate these findings into recommendations).
We have piloted the LongITools Healthcare monitoring application that integrates:
• An AI exposome-based prediction;
• A smartphone-based application with wearables;
• A sensory hub.
Separately, each of the components of this proof-of-concept application are representing strong technological development in their relevant fields and a currently leading to promising exploitation either in the academic and the private spheres (see WP7 and 9).
LongITools has built a robust network of stakeholders and followers as planned in our communication, dissemination and exploitation strategy. This is further supported by the European Human Exposome Network where collaborations across projects is contributing to bring visibility in exposome research. This also helps reducing the risk of ‘stakeholder fatigue’. Within each of the ‘LongITools cities’ where general assembly where held, dedicated meetings with local stakeholders were organised. This has contributed to raise the project outreach, improve opportunities for citizen participation and further identify the role of LongITools as an asset to help on-going health or environmental policies.
LongITools has (i) gained the scientific maturity, (ii) developed a strong understanding of the local and EU policy plans and (iii) established a robust network of stakeholders to ensure that the recommendations and policy briefs may reach their expected impacts.
As a project we synergised tasks across the project partners to address our scientific challenges, generated FAIR data and analytical tools and promote best practices for open sciences in exposome research. Together, we further implemented and adapted our road map for exploitation to translate the knowledge gained into greater health and wellbeing in the general population. The project has made quantifiable progresses combining the strengths and expertise of each of its members, supported by effective management, targeted communication strategy and agreed project plans.
Important new findings from the LongITools are arising. Quite consistently we are reporting a compelling body of evidence showing new types of associations between altered urban environments with the prevalence of T2D, obesity and cardiovascular diseases (the current results are subjected to further sensitivity analyses to translate these findings into recommendations).
We have piloted the LongITools Healthcare monitoring application that integrates:
• An AI exposome-based prediction;
• A smartphone-based application with wearables;
• A sensory hub.
Separately, each of the components of this proof-of-concept application are representing strong technological development in their relevant fields and a currently leading to promising exploitation either in the academic and the private spheres (see WP7 and 9).
LongITools has built a robust network of stakeholders and followers as planned in our communication, dissemination and exploitation strategy. This is further supported by the European Human Exposome Network where collaborations across projects is contributing to bring visibility in exposome research. This also helps reducing the risk of ‘stakeholder fatigue’. Within each of the ‘LongITools cities’ where general assembly where held, dedicated meetings with local stakeholders were organised. This has contributed to raise the project outreach, improve opportunities for citizen participation and further identify the role of LongITools as an asset to help on-going health or environmental policies.
LongITools has (i) gained the scientific maturity, (ii) developed a strong understanding of the local and EU policy plans and (iii) established a robust network of stakeholders to ensure that the recommendations and policy briefs may reach their expected impacts.
It is anticipated that there will be eight key exploitable results (KERs) from the project. One completed KER is the LongITools Innovation Toolbox which details the project’s results and enables stakeholders to find out more about the KERs and how to collaborate (https://longitools.org/innovation-toolbox).
• KER #1 LongITools Metadata Catalogue will bring together existing networks and cohort data into one open science platform ensuring a better reuse of data and increased benefit to scientific communities. To-date (year 3 of the project), the catalogue, extended to other EHEN projects and more data will be added to the catalogue.
• KER #2 Analytical Tools and Toolbox aims to develop a toolbox that can reduce the time it takes for researchers to find resources to address a specific set of hypotheses, therefore promoting rapid innovation and boosting EU scientific competitiveness. To-date, the technical part of this analytical tool-box has been developed and the ‘tools’ are being collected, to eventually translate exposome methodology for data scientists.
• KER #3 Life-Course Causal Models will provide scientific models to better, and/or with greater precision, predict the causative mechanisms of cardiovascular and metabolic non-communicable diseases. To-date, epidemiological and econometric models to ascertain the causal mechanisms are under testing.
• KER #4 Healthcare Risk Assessment App - a personalised and precise monitoring system integrating exposome-based data from users, environmental sensors, and wearables to estimate, using an Artificial Intelligence based predictive model, an individual’s risk of developing cardiovascular and metabolic diseases To-date, this proof of concept system has been developed and will now be tested via a feasibility study with 15 volunteers in Italy.
• KER #5 Policy & Regulation Database and Healthcare Utilisation Catalogue, KER #6 Economic Simulation Platform, KER #7 Policy Options will help define actions to prevent cardiovascular and metabolic non-communicable diseases via cost effective clinical interventions and/or policy planning. To date, two novel analytical tools for use in life-course modelling, to help researchers to estimate the causal effects of healthcare policies, laws and regulations and their impacts on the utilisation of health services, are completed. Research is ongoing to provide input to the policy options.
• KER #1 LongITools Metadata Catalogue will bring together existing networks and cohort data into one open science platform ensuring a better reuse of data and increased benefit to scientific communities. To-date (year 3 of the project), the catalogue, extended to other EHEN projects and more data will be added to the catalogue.
• KER #2 Analytical Tools and Toolbox aims to develop a toolbox that can reduce the time it takes for researchers to find resources to address a specific set of hypotheses, therefore promoting rapid innovation and boosting EU scientific competitiveness. To-date, the technical part of this analytical tool-box has been developed and the ‘tools’ are being collected, to eventually translate exposome methodology for data scientists.
• KER #3 Life-Course Causal Models will provide scientific models to better, and/or with greater precision, predict the causative mechanisms of cardiovascular and metabolic non-communicable diseases. To-date, epidemiological and econometric models to ascertain the causal mechanisms are under testing.
• KER #4 Healthcare Risk Assessment App - a personalised and precise monitoring system integrating exposome-based data from users, environmental sensors, and wearables to estimate, using an Artificial Intelligence based predictive model, an individual’s risk of developing cardiovascular and metabolic diseases To-date, this proof of concept system has been developed and will now be tested via a feasibility study with 15 volunteers in Italy.
• KER #5 Policy & Regulation Database and Healthcare Utilisation Catalogue, KER #6 Economic Simulation Platform, KER #7 Policy Options will help define actions to prevent cardiovascular and metabolic non-communicable diseases via cost effective clinical interventions and/or policy planning. To date, two novel analytical tools for use in life-course modelling, to help researchers to estimate the causal effects of healthcare policies, laws and regulations and their impacts on the utilisation of health services, are completed. Research is ongoing to provide input to the policy options.