Summary
EarlyCause will identify and demonstrate causative mechanisms and molecular pathways linking early life stress (ELS) to depression and two of its main physical comorbidities, namely coronary heart disease and diabetes. The consortium will disentangle the complex biological contributions from four key interconnected domains linked to ELS, namely epigenetics, inflammation, neuroendocrine system, and microbiome. Furthermore, modifying effects of environmental factors such as sex/gender, socioeconomics, lifestyle and behavior will be quantified, thus uncovering potential intervention targets that may reverse the causative mechanisms and reduce the impact of ELS on multi-morbidity development in high-risk individuals.
To achieve the goals of the project, this highly multi-disciplinary and experienced consortium will combine state-of-the-art and novel approaches from basic, pre-clinical and clinical research, including causal inference methods such as Mendelian randomisation, animal models of prenatal and postnatal stress, cellular models in various tissues, and integrative bioinformatics and machine learning methods. The consortium members will also enable access and exploitation of the largest set of European cohorts, comprising rich information on early stressors, biological and omics data, as well as depressive, cardiovascular and metabolic phenotypes. Generated data, tissue samples, experimental protocols and cell lines, as well as best practices, will be compiled and integrated into a new open-access research platform within ELIXIR to support future researchers in the emerging topics of ELS and multi-morbidity.
Finally, the project will ensure the research, clinical and socioeconomic impacts are adequately quantified and translated to allow full exploitation of the identified biomarkers and innovation outputs, in particular in relation to new integrated care pathways taking into account ELS-induced multi-morbidity in clinical practice.
To achieve the goals of the project, this highly multi-disciplinary and experienced consortium will combine state-of-the-art and novel approaches from basic, pre-clinical and clinical research, including causal inference methods such as Mendelian randomisation, animal models of prenatal and postnatal stress, cellular models in various tissues, and integrative bioinformatics and machine learning methods. The consortium members will also enable access and exploitation of the largest set of European cohorts, comprising rich information on early stressors, biological and omics data, as well as depressive, cardiovascular and metabolic phenotypes. Generated data, tissue samples, experimental protocols and cell lines, as well as best practices, will be compiled and integrated into a new open-access research platform within ELIXIR to support future researchers in the emerging topics of ELS and multi-morbidity.
Finally, the project will ensure the research, clinical and socioeconomic impacts are adequately quantified and translated to allow full exploitation of the identified biomarkers and innovation outputs, in particular in relation to new integrated care pathways taking into account ELS-induced multi-morbidity in clinical practice.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/848158 |
| Start date: | 01-01-2020 |
| End date: | 30-06-2024 |
| Total budget - Public funding: | 5 997 381,00 Euro - 5 997 381,00 Euro |
Cordis data
Original description
EarlyCause will identify and demonstrate causative mechanisms and molecular pathways linking early life stress (ELS) to depression and two of its main physical comorbidities, namely coronary heart disease and diabetes. The consortium will disentangle the complex biological contributions from four key interconnected domains linked to ELS, namely epigenetics, inflammation, neuroendocrine system, and microbiome. Furthermore, modifying effects of environmental factors such as sex/gender, socioeconomics, lifestyle and behavior will be quantified, thus uncovering potential intervention targets that may reverse the causative mechanisms and reduce the impact of ELS on multi-morbidity development in high-risk individuals.To achieve the goals of the project, this highly multi-disciplinary and experienced consortium will combine state-of-the-art and novel approaches from basic, pre-clinical and clinical research, including causal inference methods such as Mendelian randomisation, animal models of prenatal and postnatal stress, cellular models in various tissues, and integrative bioinformatics and machine learning methods. The consortium members will also enable access and exploitation of the largest set of European cohorts, comprising rich information on early stressors, biological and omics data, as well as depressive, cardiovascular and metabolic phenotypes. Generated data, tissue samples, experimental protocols and cell lines, as well as best practices, will be compiled and integrated into a new open-access research platform within ELIXIR to support future researchers in the emerging topics of ELS and multi-morbidity.
Finally, the project will ensure the research, clinical and socioeconomic impacts are adequately quantified and translated to allow full exploitation of the identified biomarkers and innovation outputs, in particular in relation to new integrated care pathways taking into account ELS-induced multi-morbidity in clinical practice.
Status
SIGNEDCall topic
SC1-BHC-01-2019Update Date
26-10-2022
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