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Dynamic longitudinal exposome trajectories in cardiovascular and metabolic non-communicable diseases

Periodic Reporting for period 2 - LONGITOOLS (Dynamic longitudinal exposome trajectories in cardiovascular and metabolic non-communicable diseases)

Okres sprawozdawczy: 2021-07-01 do 2022-12-31

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’, how collective environmental, socioeconomic, and lifestyle exposures, and the totality of these across a lifetime, cause common diseases. 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.
The scientific objective of LongITools is to test the exposome hypothesis linking air pollution, noise and the built environment to the risk of CVM-NCDs. During the first 36 months, the following has been achieved:

• Developed the partnership to ensure cohesion across the consortium and work packages.

• Working with the European Human Exposome Network (EHEN) projects, a novel Metadata Catalogue has been developed. This online, searchable catalogue details information about the data sets available within the LongITools consortium and the institutions. To make the data interoperable, each data set has been mapped to an initial set of exposome variables to an agreed definition (a harmonised or common data model). The catalogue follows and supports the FAIR data infrastructure principles. It will continue to be refined and it is hoped will incorporate many of the EHEN projects.

• The development of statistical, econometric and economic microsimulation models to support the research are well underway.

• Numerous exposome based research projects are planned and being undertaken. The outcomes of this research is being translated into publications and will feed into policy options. To-date, over 50 peer-review articles have been published by LongITools consortium members, many of which received attention by the scientific community and other stakeholder groups.

• A first complete version of the healthcare risk assessment application has been fully implemented and released (currently available on Italian Play store and App store for the proof-of-concept study participants).

• The project website has continued to be developed with a new structure and content. Regular updates on progress are provided via various communication channels, including via the Innovation Toolbox.

• To develop a network of stakeholders, one Science Connecting Policy workshop and three Policy Forums have been held. These events have led to the publications of blogs, input to a high-level report and the ongoing development of a white paper, together with the stakeholders.

• Contributions to EHEN Working Groups and activities and, since M30, joint coordination of EHEN with the EXIMIOUS project.
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.
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