Our research: topics and work packages
Topic 4: The molecular level of OMICs: proteomics, metabolomics and epigenomics
Lead: SDU
To study the OMICs behind MARKOPOLO, the focus lies on identifying biological markers that indicate how pollution and noise exposure impact human health. Standardized protocols ensure reliable data collection, while omics techniques are applied to preclinical models and human samples to analyse biochemical responses to environmental stressors. Advanced analyses (redox-phospho-proteomics, metabolomic epigenetics) investigate how factors like age, gender, and pre-existing conditions influence these responses, helping to pinpoint early signs of health risks. The findings will be integrated into predictive models that link environmental exposures to heart and brain diseases, supporting the development of a tool to map high-risk areas and inform public health strategies. To enhance collaboration, all data will be made accessible for further research in environmental health and policy.
Involved work packages:
- WP9: Initial Omics Screening and Biomarker Diversity
- WP10: Advanced Omics Studies and Biomarkers Selection
- WP13: Integrative analysis: integration of the molecular, environmental and clinical results, and finalizing omics analysis of remaining samples and omics data quality assurance
Topic 5: Connecting Pollution to Disease: Advanced Bioinformatics and Risk Assessment
Lead: LIH
The bioinformatics aspect of MARKOPOLO focuses on harmonizing and analysing multi-omics data to understand how pollution affects human health. Standardized protocols will be proposed to ensure data consistency, while advanced bioinformatics techniques will identify key molecular markers and pathways associated with air and noise pollution. By integrating several omics layers, including pre-existing transcriptomics, and newly obtained proteomics, epigenomics and cytokine datasets, this research will provide a deeper understanding of how environmental exposures contribute to disease. The findings will drive the development of predictive models, connecting pollution to heart and brain disorders, which will ultimately lead to an exposome-disease maps.
Involved work packages:
- WP11: Bioinformatics I: Harmonization of the processes and analysis of the existing multi-omics data
- WP12: Bioinformatics II: Analysis of experimental omics, exposome, clinical data II
- WP13: Integrative analysis: integration of the molecular, environmental and clinical results, and finalizing omics analysis of remaining samples and omics data quality assurance
Topic 6: Project Management
Lead: UMC-Mainz & concentris
The responsibility for the project management lies primarily with the coordinator (COO) at the University Medical Center Mainz (UMC-Mainz). The COO is supported by concentris, a company with longstanding expertise in the management of EC funded research projects in the health area. Management tasks include monitoring the implementation of the project, acting as the intermediary for all communications between the project partners and the European Commission (EC), dealing with the paperwork for the EC including submitting deliverables and reports to the EC with the timings and conditions set in the grant agreement and dealing with all financial matters.
Involved work packages:
- WP14: Project management I: Legal, ethics, governance and economic aspects
- WP15: Project management II: Legal, ethics, governance and economic aspects
- WP16: Project management III: Legal, ethics, governance and economic aspects
Topic 7: Science Communication, Dissemination, Training & Exploitation of Results
Lead: concentris
The science communication and dissemination team will translate MARKOPOLO results into benefits for society. The main objective is to make MARKOPOLO outputs accessible in clear and customized formats and support their uptake by the scientific, clinical and public health community, and the general public. Furthermore, the team aims to create platforms and materials for dissemination, training and communication that ensure open access and reproducibility of research outputs. New scientific knowledge and tools will be systematically and openly shared as early and widely as possible. Additionally, the team is responsible for utilizing MARKOPOLO health data for risk assessment by translating scientific findings into recommendation documents that align with both lay press and health policy standards.
Involved work packages:
- WP17: Dissemination & Training I
- WP18: Dissemination, Exploitation/Risk Assessment, Policy Recommendations and Training II
- WP19: Dissemination, Exploitation/Risk Assessment, Policy Recommendations and Training III
Topic 8: Science-policy interfaces
Lead: JMU
This topic explores how scientific research on environmental health exposure informs pollution policy. To identify gaps in the information used for decision-making, experts will be interviewed, pollution policy documents analysed, and transdisciplinary meetings observed. The study will also examine how different countries bridge the gap between science and policy, highlighting key players who facilitate knowledge sharing among researchers, policymakers, and practitioners. Finally, a model will be developed to illustrate how science, policy, and practice can work together more effectively to enhance knowledge integration in environmental health risk management.
Involved work packages:
- WP20: Assessment of science-policy interfaces in environmental health risk management
Topic 9: EU framework program for research & innovation on environment and health: clustering activities
Lead: UMC-Mainz
The clustering activities focus on building strong connections between MARKOPOLO and other projects, funded from the same call (HORIZON-HLTH-2024-ENVHLTH-02-06 “The role of environmental pollution in non-communicable diseases: air, noise and light and hazardous waste pollution”). By creating a collaborative project cluster, we enhance synergies, streamline information flows, and strengthen the link between science and policy. The cluster also maximizes the impact of communication and dissemination efforts, ensuring broader outreach and knowledge exchange. Key focus areas include data management, policy feedback, scientific collaboration, and strategic communication.
Click here to read more about the Cluster EXPO HEALTH NET
Involved work packages:
- WP21: Clustering activities
Topic 10: Ethics
Lead: UMC-Mainz
This work package ensures that the project meets all required ethical standards. It outlines the necessary ethics guidelines and compliance measures, ensuring responsible research practices throughout the project.
Involved work packages:
- WP22: Ethics requirements
Topic 1: The use of preclinical models for controlled noise and particulate matter exposure studies
Lead: UMC-Mainz
To investigate how exposure to noise and ultrafine particulate matter (UFP) contributes to chronic diseases affecting the lung, brain, and heart, advanced exposure models in 3D cell cultures and mice are used. The research focuses on identifying the biological mechanisms behind the detrimental health effects, with a focus on vulnerable groups, aging populations, and sex-specific differences. This part of MARKOPOLO also explores how combined environmental exposures may amplify health risks and seeks to identify ways to mitigate damage at multiple levels. These insights will support better prevention strategies and inform public health policies.
Involved work packages:
- WP1: Functional and biochemical disease-relevant changes by noise and/or PM (UFP) in preclinical models - focus: lung/brain-heart axis
- WP2: Additive effects by noise and/or PM (UFP) in preclinical models - focus: chronic diseases and pharmacological preventive strategies
- WP3: Additive effects by noise and/or PM (UFP) in preclinical models - focus: aging process and sex as confounders
Topic 2: Human exposure studies on noise and particulate matter effects
The primary goal is to deepen the understanding of how air pollution and noise impact cardiovascular, metabolic and neurodegenerative health, particularly in vulnerable groups. This includes enhancing methodologies for measuring and modelling exposure to pollutants, including with a focus on ultrafine particles, evaluating the health impact of air and noise pollution mixtures on health in observational and experimental studies, and examining the role of socio-economic factors in environmental exposure inequities. Additionally, the we aim is to evaluate evidence-based lifestyle interventions to reduce health risks, targeting diet and physical activity. To support better health risk management, advanced tools for environmental health impact assessment are being developed, with a focus on cardiovascular, metabolic and neurodegenerative diseases. The use of developed health-based tools may empower politicians and clinicians to enhance environmental health risk management and disease treatment strategies to support better metabolic disorders prevention and patient outcomes.
Involved work packages:
- WP4: Improve estimation of human environmental exposures on cardiovascular health indices
- WP5: Evaluating human health risks of air pollutants and noise sources with other environmental factors
- WP6: Tools for integrated environmental health impact assessment and health risk management
Topic 3: Computational modeling of Noise/PM lung damage and health effects in the population
To study the health effects of particulate matter (PM) exposure, advanced atmospheric chemistry climate models are used to help the creation and understanding of high-resolution maps of ultrafine particle (UFP) concentrations. Such maps are essential to track the spread of UFP and to estimate the population’s exposure to such harmful particles. By combining exposure maps with epidemiological studies, complex scientific data is transformed into actionable knowledge. At the same time, detailed models are developed to examine how UFP exposure impacts the cardiovascular system at a molecular level, giving a detailed medical explanation on the pollution effect on human health. To translate these findings into public health insights, real air pollution data is analysed to estimate its potential to cause oxidative stress, a key factor in many diseases. Finally, a combination of exposure maps and oxidative stress is used to develop a “risk index”, to help policymakers and the public better understand air pollution risks and make informed decisions for healthier communities.
Involved work packages:
- WP7: Model simulation of high-resolution UFP data and development of kinetic models for UFP exposure in preclinical models of chronic diseases
- WP8: Translation of simulation data from large-scale and kinetic models to epidemiological studies and public information