University of Galway researchers have made ‘digital babies’ to figure out the first 180 days of an infant’s health. 360 computer models that are advanced enough, act out the unique metabolic processes of each baby. Data from 10,000 newborns that include the sex, the birth weight and the metabolic reactions facilitates and accepts an invention of modelling that allows scientists to investigate an infant’s metabolism individually for the exact medicine applications.
This is a first sex-specific computational whole-body model that represents the newborn and the infant metabolism with 26 organs, six cell types, and more than 80,000 metabolic reactions. Their work was conducted at the University of Galway’s Digital Metabolic Twin Centre and the Heidelberg University. Prof Ines Thiele was the leader and the APC Microbiome Ireland Principal Investigator. This research improves on our understanding of the inherited metabolic diseases in newborns and infants, and helps formulate a diagnosis and treatment of the medical conditions that occur during the early days of a baby’s life.
The research was published in the 1st week of June of this year in Cell Metabolism. According to the lead author Elaine Zaunseder, “Babies are not just small adults-they have unique metabolic features that allow them to develop and grow up healthy. For instance, babies need more energy for regulating body temperature due to, for example, their high surface-area-to-mass ratio, but they cannot shiver in the first six months of life, so metabolic processes must ensure the infant keeps warm.” She continues to add, “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. We captured metabolism in an organ-specific manner, which offers the unique opportunity to model organ-specific energy demands that are very different in infants compared to adults. As nutrition is the fuel for metabolism, we can use breast milk data from real newborns in our models to stimulate the associated metabolism throughout the baby’s entire body, including various organs. Based on their nutrition, we simulated the development of digital babies over six months and showed that they will grow at the same rate as real-world infants.”
Prof Thiele says, “New-born screening programs are crucial for detecting metabolic diseases early on, enhancing infant survival rates and health outcomes. However, the variability observed in how these diseases manifest in babies underscores the urgent need for personalised approaches to disease management. Our models allow researchers to investigate the metabolism of healthy infants as well as infants suffering from inherited metabolic diseases, including those investigated in newborn screening. When simulating the metabolism of infants with a disease, the models showed we can predict known biomarkers for these diseases. Furthermore, the models accurately predicted metabolic responses to various treatment strategies, showcasing their potential in clinical settings.”
Zaunseder added, “This work is a first step towards establishing digital metabolic twins for infants providing a detailed view of their metabolic processes. Such digital twins have the potential to revolutionise paediatric healthcare by enabling tailored disease management for each infant’s unique metabolic needs.”
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