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Personalized metabolic whole-body models for newborns and infants predict growth and biomarkers of inherited metabolic diseases.
Zaunseder, Elaine; Mütze, Ulrike; Okun, Jürgen G; Hoffmann, Georg F; Kölker, Stefan; Heuveline, Vincent; Thiele, Ines.
Afiliación
  • Zaunseder E; School of Medicine, University of Galway, Galway, Ireland; Engineering Mathematics and Computing Lab (EMCL), Interdisciplinary Center for Scientific Computing (IWR), Heidelberg University, Heidelberg, Germany; Data Mining and Uncertainty Quantification (DMQ), Heidelberg Institute for Theoretical Stu
  • Mütze U; Division of Child Neurology and Metabolic Medicine, Center for Child and Adolescent Medicine, Heidelberg University, Medical Faculty, Heidelberg, Germany.
  • Okun JG; Division of Child Neurology and Metabolic Medicine, Center for Child and Adolescent Medicine, Heidelberg University, Medical Faculty, Heidelberg, Germany.
  • Hoffmann GF; Division of Child Neurology and Metabolic Medicine, Center for Child and Adolescent Medicine, Heidelberg University, Medical Faculty, Heidelberg, Germany.
  • Kölker S; Division of Child Neurology and Metabolic Medicine, Center for Child and Adolescent Medicine, Heidelberg University, Medical Faculty, Heidelberg, Germany.
  • Heuveline V; School of Medicine, University of Galway, Galway, Ireland; Engineering Mathematics and Computing Lab (EMCL), Interdisciplinary Center for Scientific Computing (IWR), Heidelberg University, Heidelberg, Germany.
  • Thiele I; School of Medicine, University of Galway, Galway, Ireland; Discipline of Microbiology, University of Galway, Galway, Ireland; Digital Metabolic Twin Centre, University of Galway, Ireland; Ryan Institute, University of Galway, Galway, Ireland; APC Microbiome Ireland, Cork, Ireland. Electronic address
Cell Metab ; 36(8): 1882-1897.e7, 2024 Aug 06.
Article en En | MEDLINE | ID: mdl-38834070
ABSTRACT
Comprehensive whole-body models (WBMs) accounting for organ-specific dynamics have been developed to simulate adult metabolism, but such models do not exist for infants. Here, we present a resource of 360 organ-resolved, sex-specific models of newborn and infant metabolism (infant-WBMs) spanning the first 180 days of life. These infant-WBMs were parameterized to represent the distinct metabolic characteristics of newborns and infants, including nutrition, energy requirements, and thermoregulation. We demonstrate that the predicted infant growth was consistent with the recommendation by the World Health Organization. We assessed the infant-WBMs' reliability and capabilities for personalization by simulating 10,000 newborns based on their blood metabolome and birth weight. Furthermore, the infant-WBMs accurately predicted changes in known biomarkers over time and metabolic responses to treatment strategies for inherited metabolic diseases. The infant-WBM resource holds promise for personalized medicine, as the infant-WBMs could be a first step to digital metabolic twins for newborn and infant metabolism.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Biomarcadores / Medicina de Precisión Límite: Female / Humans / Infant / Male / Newborn Idioma: En Revista: Cell Metab Asunto de la revista: METABOLISMO Año: 2024 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Biomarcadores / Medicina de Precisión Límite: Female / Humans / Infant / Male / Newborn Idioma: En Revista: Cell Metab Asunto de la revista: METABOLISMO Año: 2024 Tipo del documento: Article