Periodic Reporting for period 2 - DohART-NET (Periconceptional Programming of Health Training Network)
Berichtszeitraum: 2021-07-01 bis 2023-11-30
Altered conditions during the periconceptional (PC) period of gamete maturation and early embryonic development have long lasting effects on the health of the progeny, including the childhood, adolescent and adult-life onset of cardiovascular, metabolic and neurological diseases (DOHaD concept). Increasing evidence from epidemiological and animal model studies shows that children worldwide exhibit conditions and disease risks associated with the exposures of their parents, including chemical stressors before and during pregnancy, reproductive failure, adverse pregnancy outcome, diabetes, obesity and nutritional compromise. Babies born following human Assisted Reproductive Technology (ART, “test-tube”) interventions render this population (over 8 million world-wide) one of the largest well-defined clinical cohorts to be studied for a better understanding of the future risk of disease for current and succeeding generations in Europe. The DohART-NET project focuses on the integration of pre-clinical (animal and stem cell-models) and clinical studies and applies data linkage, bioinformatics and network science for the identification and validation of mechanisms of diseases common in early development. We will exploit our new understanding to promote efficient disease prevention and potential personalised therapeutic interventions in both the general and ART populations to overcome adverse disease pathways.
DohART-NET project scientific activities have been efficiently concluded, 13 ESRs completed their own scientific projects and trainings as planned. The scientific progress was slightly impaired during the COVID epidemy due to restrictions, but overall the project successfully compensated such delays. The ESRs using all electronic communication means completed several literature reviews resulting in collaborative manuscripts for a journal special issue closely related to the topic and published numerous high-quality papers from their results, including various collaborative papers together with other ESRs. The ESRs contributed to promote the project results with dissemination and outreach activities very efficiently. Finally, the ESRs are progressing well to obtain their PhD degrees.
DohART-NET project members efficiently contributed to find new evidences using different models and datasets to prove that children physiological well-being and future disease risks are associated with the exposures of their parents and to decipher the exact mechanism and possibilities for prevention. Because the ART-born population is increasing in number and age, there is an urgent need to improve the current limited epidemiology-based risk assessment and ultimately modifying high risk ART factors to improve long term health of ART children. DohART-NET provided an in depth-analysis, using access to the UK National ART cohort which is the largest and oldest available and contains data on ART children into adulthood, and compaired detailed clinical cohorts of ART and normal pregnancies. Furthermore, the in-depth integration of rodent and large-animal models, clinical datasets with biomarker discovery and the appropriate human stem cell models and network science applied to such datasets has resulted in new findings published in several high-impact papers.
Significant progress beyond the current state-of-the-art have been made in all aspects of the project. Work package activities included human participants, mouse and pig (for example Type 1 diabetic humanized pig) in vivo models as well as human in vitro models, human birth cohorts and other databases, and in silico methods, including network science methods to analyse correlations among contributing factors and health outcomes. Furthermore, studies covered 3D measurements and mHealth data base analysis in the Smarter Pregnancy human cohort. Specifically, the individual projects of the students enhanced the knowledge of the scientific community and the public on DOHaD, for example students completed a full literature review of the impact of human ART on birthweight and child growth and started to analyse existing databases, including the impact of ART exposure on growth of twins from the Scottish linkage cohort, and complementing the data with a molecular level analysis of possible mechanisms underlying this effect. Results provided essential information on the impact of maternal lifestyle factors on foetal development, giving insights to better understand intrauterine developmental mechanisms and ultimately help clinicians to improve pregnancy care. The work identified the risk for pregnancy complications and outcome in obese women during the periconception period based on oxidative stress markers routinely used in clinical practice. The use of eHealth application „Smarter Pregnancy” tailored to lifestyle coaching platform for obese women to reach a healthier state of pregnancy. The impact of diet on reproduction and pregnancy, shown that higher maternal ultra-processed food intake was significantly associated with smaller embryo growth trajectories and was significantly associated with an increased risk of endometriosis in women, and oligozoospermia and low total motile sperm count in men. The generation of a new cohort of maternal high fat diet mice has taken place with results gathered on metabolic and cognitive behaviours. Neuronal and cardiac differentiation of human induced pluripotent stem cells allowed measurement of the effect of different stressors, including bisphenol A (BPA) during early differentiation events and cardiac and neuronal tissue lineage commitment. Students reported effects of maternal diabetes on physiological parameters and OMICs profiles in pig neonates, generated a biobank of body fluids and tissues and shown that maternal hyperglycemia without confounding obesity induces profound structural and molecular changes in liver and pancreas of neonatal offspring. The project integrated different sources of -omics data to evaluate the impact of ART on embryonic development. Specifically, students developed an integrated Machine Learning (ML) model that would combine the morphological features of a cell with its secreted proteins (secretome) to successfully predict its outcome in embryo implantation. Based on his predictions, it was possible to optimize the culture media conditions to increase the ART success rate avoiding ploidies. Students followed the transcriptomic changes of human preimplantation embryos identifying waves of differentiation that are related to the later-on child phenotype. Integration of various data modalities allowed to construct 120 ART-related disease modules (coordinated proteins that would be strictly connected to the genesis of a disease). By applying network analysis, students were able to identify potential biomarkers and related pathways that would contribute to the disease phenotype. The network analyses enabled to identify potential drugs that could help in the context of ART-related diseases and expanded this task to investigate the relationships between any possible environmental chemical compound and ART-related diseases. The long-term impact of the project can have a major impact on European society which is ageing and suffering from a dramatic increase in metabolic syndrome diseases. DohART-NET provides major added value by focusing on long-term consequences of periconceptional events and ART technologies on human health.
Significant progress beyond the current state-of-the-art have been made in all aspects of the project. Work package activities included human participants, mouse and pig (for example Type 1 diabetic humanized pig) in vivo models as well as human in vitro models, human birth cohorts and other databases, and in silico methods, including network science methods to analyse correlations among contributing factors and health outcomes. Furthermore, studies covered 3D measurements and mHealth data base analysis in the Smarter Pregnancy human cohort. Specifically, the individual projects of the students enhanced the knowledge of the scientific community and the public on DOHaD, for example students completed a full literature review of the impact of human ART on birthweight and child growth and started to analyse existing databases, including the impact of ART exposure on growth of twins from the Scottish linkage cohort, and complementing the data with a molecular level analysis of possible mechanisms underlying this effect. Results provided essential information on the impact of maternal lifestyle factors on foetal development, giving insights to better understand intrauterine developmental mechanisms and ultimately help clinicians to improve pregnancy care. The work identified the risk for pregnancy complications and outcome in obese women during the periconception period based on oxidative stress markers routinely used in clinical practice. The use of eHealth application „Smarter Pregnancy” tailored to lifestyle coaching platform for obese women to reach a healthier state of pregnancy. The impact of diet on reproduction and pregnancy, shown that higher maternal ultra-processed food intake was significantly associated with smaller embryo growth trajectories and was significantly associated with an increased risk of endometriosis in women, and oligozoospermia and low total motile sperm count in men. The generation of a new cohort of maternal high fat diet mice has taken place with results gathered on metabolic and cognitive behaviours. Neuronal and cardiac differentiation of human induced pluripotent stem cells allowed measurement of the effect of different stressors, including bisphenol A (BPA) during early differentiation events and cardiac and neuronal tissue lineage commitment. Students reported effects of maternal diabetes on physiological parameters and OMICs profiles in pig neonates, generated a biobank of body fluids and tissues and shown that maternal hyperglycemia without confounding obesity induces profound structural and molecular changes in liver and pancreas of neonatal offspring. The project integrated different sources of -omics data to evaluate the impact of ART on embryonic development. Specifically, students developed an integrated Machine Learning (ML) model that would combine the morphological features of a cell with its secreted proteins (secretome) to successfully predict its outcome in embryo implantation. Based on his predictions, it was possible to optimize the culture media conditions to increase the ART success rate avoiding ploidies. Students followed the transcriptomic changes of human preimplantation embryos identifying waves of differentiation that are related to the later-on child phenotype. Integration of various data modalities allowed to construct 120 ART-related disease modules (coordinated proteins that would be strictly connected to the genesis of a disease). By applying network analysis, students were able to identify potential biomarkers and related pathways that would contribute to the disease phenotype. The network analyses enabled to identify potential drugs that could help in the context of ART-related diseases and expanded this task to investigate the relationships between any possible environmental chemical compound and ART-related diseases. The long-term impact of the project can have a major impact on European society which is ageing and suffering from a dramatic increase in metabolic syndrome diseases. DohART-NET provides major added value by focusing on long-term consequences of periconceptional events and ART technologies on human health.