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Personalized metabolic whole-body models for newborns and infants predict growth and biomarkers of inherited metabolic diseases

  • Elaine Zaunseder
  • , Ulrike Mütze
  • , Jürgen G. Okun
  • , Georg F. Hoffmann
  • , Stefan Kölker
  • , Vincent Heuveline
  • , Ines Thiele
  • University of Galway
  • Heidelberg University
  • Scientific Computing, Heidelberg Institute for Theoretical Studies (HITS)
  • Medical Faculty Mannheim
  • APC Microbiome Ireland

Research output: Contribution to a Journal (Peer & Non Peer)Articlepeer-review

16 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)1882-1897.e7
JournalCell Metabolism
Volume36
Issue number8
DOIs
Publication statusPublished - 6 Aug 2024

Keywords

  • constraint-based metabolic modeling
  • digital metabolic twins
  • infant metabolism
  • inherited metabolic diseases
  • metabolism
  • metabolomics
  • newborn screening

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