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Causative mechanisms & integrative models linking early-life-stress to psycho-cardio-metabolic multi-morbidity

Periodic Reporting for period 3 - EarlyCause (Causative mechanisms & integrative models linking early-life-stress to psycho-cardio-metabolic multi-morbidity)

Berichtszeitraum: 2023-01-01 bis 2024-06-30

Early life stress (ELS) is the experience of stressful or adverse conditions during a child’s development, beginning anywhere from pregnancy to adolescence. When prenatal, ELS may be experienced because of maternal stress during pregnancy, while after birth, it can result from adverse events such as child abuse (sexual, physical, emotional) and neglect (emotional, physical), parental loss (death, separation), disease, accidents, exposure to war or terrorism-related events and/or natural disasters. ELS matters because it can have a long-lasting impact on a child’s development, health and wellbeing. For example, ELS can affect a child’s neurodevelopment increasing the risk of cognitive, emotional and behavioural problems. In addition, ELS can dysregulate important physiological functions affecting the way a child may respond to future stressors.

ELS is a key determinant of health, not just early in life, but across the lifespan. It is known to dramatically increase the risk to develop a mental or physical illness and has been repeatedly associated with depression, anxiety, personality disorder but also cardiovascular, metabolic and autoimmune diseases, and possibly cancer. However, the biological mechanisms through which ELS affects health remain unclear.

EarlyCause is investigating how ELS causes diseases in adulthood. Its approach is original and novel because it examines which aspects of ELS are linked to the concomitant development of psychological, cardiovascular and metabolic diseases together, a phenomenon called co-morbidity, which is responsible for the increased mortality linked to ELS. Further, EarlyCause assesses whether these co-morbid symptoms can be diminished or prevented by intervention to avoid disease.
EarlyCause integrates research across large European human cohorts and validated cellular and animal models to uncover the molecular and biological pathways triggered by early life stress (ELS) that lead to clinical symptoms in both the brain and body. By employing a genetically informed approach, the project evaluates the relationships and potential causal links between childhood maltreatment and various physical and mental health outcomes. Additionally, EarlyCause has begun intervention studies to assess how exposure to enriched environments after postnatal stress might moderate impacts on behavior and cardiometabolic health.

WP2 produced two key outputs: Deliverable Report D2.6 a guide on data standards and FAIR data sharing for EarlyCause research, created with input from 22 members across 9 organizations, and Deliverable Report D2.7 detailing the completion of the EarlyCause Data Portal. The portal integrates diverse data types, automates third-party dataset searches, and serves as a central resource for ELS-related research.

WP3 completed tasks 3.2 and 3.3 with all deliverables finalized and follow-up studies on ELS and multimorbidity conducted. Findings confirmed that prenatal and postnatal ELS increase the risk of poor cardiometabolic health and depression. Additional studies linked cardiovascular markers to brain structure, neurodevelopment, and cardiac changes. Analyses of biological correlates, such as epigenetics, inflammation, and neuroendocrine markers, revealed specific gene-by-stress interactions and associations with inflammatory markers, while the gut microbiome showed limited evidence of impact. Moderation analyses suggested lifestyle factors like diet and exercise may not mitigate ELS effects on health.

WP4 explored ELS as a causal risk factor for multimorbidity using Mendelian randomization, identifying 11 genetic variants and 18 genes involved, mainly through immune and inflammatory pathways. Further studies focused on epigenetic mechanisms, relevant genes, and the development of biomarkers for the Arctic Biobank to improve molecular measures of ELS.

WP5 investigated long-term ELS effects using rodent models, revealing persistent changes in body weight, behavior, and cardiovascular health. Environmental enrichment interventions showed promise in reversing these effects. Molecular analyses identified potential epigenetic factors and pathways, and a CRISPR-dCas9 system was developed to explore causal links between gene expression and phenotypes.

WP6 finalized experiments with various cell types to examine the molecular impacts of ELS, with RNA sequencing data revealing candidate genetic markers and ELS-related genes. Studies also explored the effects of cytokines and hormones on cell function and gene expression.

WP7 developed predictive models for multimorbidity, identifying multi-OMICS signatures associated with ELS and using machine learning to outline six distinct trajectories. A new assessment tool outperformed traditional models for predicting cardiovascular disease and diabetes, demonstrating potential for personalized healthcare.

WP8 identified and prioritized EarlyCause assets and value streams, updated the socio-economic impact framework, and conducted a literature review on ELS biomarkers and intervention strategies, highlighting new targets and addressing knowledge gaps in ELS-related multimorbidity prevention and treatment.

As an overview of the project, notable achievements include the development of a centralized data portal, insights into gene-environment interactions, and innovative predictive models that outperform traditional health risk assessments. Intervention studies, such as those exploring environmental enrichment, have demonstrated potential strategies to mitigate ELS effects, while new biomarkers and genetic tools offer pathways for personalized healthcare approaches. These findings provide a comprehensive foundation for future research and interventions aimed at preventing and treating the long-term effects of ELS, with a focus on improving health outcomes and guiding policy and clinical practice.
The EarlyCause project has advanced beyond the current state of the art by developing predictive models and tools that integrate multi-OMICS data, machine learning, and novel biomarkers to better understand the long-term impacts of early-life stress (ELS) on multimorbidity. Key achievements include identifying unique molecular signatures, validating a multi-morbidity assessment tool that outperforms existing models, and exploring new intervention strategies, such as environmental enrichment. Expected results by the project's end include refined models, new insights into ELS-related health outcomes, and the development of advanced, viable technologies for personalized healthcare approaches. The project has also contributed to filling critical knowledge gaps about the links between ELS and health, providing new intervention targets.

The potential socio-economic impact includes enhanced risk assessment tools, better-targeted preventive and therapeutic strategies, and reduced healthcare costs. Additionally, the project's wider societal implications involve promoting healthier life trajectories, raising awareness about the long-term consequences of ELS, and supporting future collaborations aimed at mitigating ELS effects on public health, ultimately contributing to more resilient healthcare systems and improved quality of life.
EarlyCause Project Flow Chart Figure
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