Researchers at the University of Galway have created digital babies to better understand the health of newborns in their first, critical, 180 days of life.
Better understanding newborn health through “digital babies”
The team created 360 advanced computer models that simulate each child’s unique metabolic processes. Digital Babies are the first sex-specific whole-body computational models representing infant and toddler metabolism with 26 organs, six cell types, and over 80,000 metabolic reactions.
Real-world data from 10,000 newborns, including sex, birth weight and metabolite concentrations, has enabled the creation and validation of models, which can be customized, allowing scientists to study an individual newborn’s metabolism for medical applications. precision.
The work on digital children was led by a team of scientists from the Digital Metabolic Twin Center at the University of Galway and the University of Heidelberg, led by Professor Ines Thiele, principal investigator of APC Microbiome Ireland.
The team’s research aims to advance precision medicine using computational modeling. They describe computational modeling of children as critical, as it improves understanding of infant metabolism and creates opportunities to improve the diagnosis and treatment of medical conditions during the first days of a child’s life, such as inherited metabolic diseases.
Lead author Elaine Zaunseder, Heidelberg University, said: “Children are not just small adults: they have unique metabolic characteristics that allow them to develop and grow healthily. For example, babies need more energy to regulate body temperature due, for example, to their high surface-to-mass ratio, but they cannot shiver in the first six months of life, so metabolic processes must ensure that the baby keep warm.
“Therefore, an essential part of this research work was to identify these metabolic processes and translate them into mathematical concepts that could be applied in the computational model of digital children.
We have captured metabolism in an organ-specific manner, offering the unique opportunity to model organ-specific energy demands that are very different in infants compared to adults.
“Because nutrition is the fuel for metabolism, we can use breast milk data from real babies in our models to simulate the associated metabolism throughout the baby’s body, including various organs. Based on their nutrition, we simulated the development of digital children over the age of six months and showed that they will grow at the same rate as real-world children.”
Professor Thiele, Study Leader on the Digital Babies Project, said: “Newborn screening programs are crucial for detecting metabolic diseases early, improving infant survival rates and health outcomes. However, the observed variability in how these diseases manifest in children highlights the urgent need for personalized approaches to disease management.
“Our digital babies allow researchers to study the metabolism of healthy newborns and newborns with inherited metabolic diseases, including those studied in newborn screening. When simulating the metabolism of newborns suffering from a disease, the models demonstrated that we can predict known biomarkers for these diseases. Additionally, the models accurately predicted metabolic responses to various treatment strategies, showing their potential in clinical settings. ”
Zaunseder added: “This work is a first step towards creating metabolic digital babies for newborns, providing detailed insight into their metabolic processes. Such digital babies have the potential to revolutionize pediatric healthcare by enabling disease management tailored to each child’s unique metabolic needs. “
The research was published on Cell Metabolism.
This work was led by the University of Galway and completed as part of a collaboration with Heidelberg University, the Heidelberg Institute for Theoretical Studies and Heidelberg University Hospital, Germany.
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