The ClimAIr project will expand the evidence-based understanding of climate change, air pollution, and non-communicable respiratory diseases by using Artificial Intelligence (AI) tools. It will gather data on greenhouse gases levels and disaster risks, information on serious air pollutants and respiratory diseases' prevalence. The AI powered tools will be employed to generate better intervention methods and improve public health outcomes. Federated Learning (FL) will be used to develop AI models to protect patients' privacy. By raising public awareness and delivering the ClimAIr tool - specifically designed to health workers, urban planners and policy makers - the project aims to influence policy decisions, promote healthier environments, and reduce respiratory diseases in Europe, which will be tested and validated the ClimAIr tool in specific municipalities that are part of the project. ClimAIr draws on a consortium of 21 partners from 15 European countries, including carefully selected health centres across Europe - in Spain, Luxembourg, Ukraine, Italy, France, Germany, Greece, Romania and Poland - focused on respiratory diseases, which will provide disease data and explore metabolic routes of the studied contaminants/diseases. ClimAIr is composed of an interdisciplinary team formed by research centres, ethical AI and modelling experts, SSH specialists, municipal governance, and a Communication \& Dissemination (C\&D) expert team dedicated to achieving and spread the results of the project.
Study Type
OBSERVATIONAL
Enrollment
1,906
Mean Symptom Score of Allergic Rhinitis Patients by Environmental Exposure
Mean allergic rhinitis symptom scores retrieved from electronic health records (EHR), stratified by environmental exposure levels (pollutants and climate factors), using the Observational Medical Outcomes Partnership (OMOP) common data model.
Time frame: Retrospective data collected over a 3-year period prior to study enrollment.
Proteomic Biomarker Levels (NPX) by Environmental Exposure
Proteomic profiles measured using Olink® assays in serum and nasal lavage of allergic rhinitis patients, stratified by environmental exposure.
Time frame: Samples collected prospectively between months 10 and 15 (October-March, out-of-pollen season).
SO1: Effect of air pollution on adaptive immune responses to allergenic pollen
Evaluation of the immune response of peripheral blood mononuclear cells (PBMCs) from allergic rhinitis patients exposed to different environmental conditions, after in vitro stimulation with pollen samples previously exposed to varying pollution levels. The response will be characterized by proliferation of allergen-specific lymphocyte subsets and cytokine production.
Time frame: Sample collection and analysis performed prospectively between months 10 and 24.
SO1: Proliferative responses of allergen-specific lymphocytes to pollen exposed to pollution
Measurement of lymphocyte proliferation using CFSE-labeled PBMCs incubated with pollen (Olea europaea, Phleum pratense, Betula pendula) grown under different pollution conditions.
Time frame: Assays conducted on samples collected between months 10 and 24.
SO1: Cytokine release from allergen-specific lymphocytes in response to polluted pollen
Quantification of cytokines released in the supernatants of PBMC cultures stimulated with pollen under different pollution conditions. A multiplex ELISA panel will be used to measure Th1, Th2, Th9, and regulatory cytokine
Time frame: Analysis performed between months 10 and 24, post-sample collection.
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