Artificial neural network inference analysis identified novel genes and gene interactions associated with skeletal muscle aging.

Journal: Journal of cachexia, sarcopenia and muscle
PMID: 39210538

Abstract

BACKGROUND: Sarcopenia is an age-related muscle disease that increases the risk of falls, disabilities, and death. It is associated with increased muscle protein degradation driven by molecular signalling pathways including Akt and FOXO1. This study aims to identify genes, gene interactions, and molecular pathways and processes associated with muscle aging and exercise in older adults that remained undiscovered until now leveraging on an artificial intelligence approach called artificial neural network inference (ANNi).

Authors

  • Janelle Tarum
    Department of Sport Science, Sport, Health and Performance Enhancement Research Centre (SHAPE), School of Science and Technology, Nottingham Trent University, Nottingham, UK.
  • Graham Ball
    John van Geest Cancer Research Centre, School of Science and Technology, Nottingham Trent University, Nottingham, United Kingdom.
  • Thomas Gustafsson
    Department of Laboratory Medicine, Section of Clinical Physiology, Karolinska Institutet Huddinge, Huddinge, Sweden.
  • Mikael Altun
    Department of Laboratory Medicine, Section of Clinical Physiology, Karolinska Institutet Huddinge, Huddinge, Sweden.
  • Lívia Santos
    Department of Sport Science, Sport, Health and Performance Enhancement Research Centre (SHAPE), School of Science and Technology, Nottingham Trent University, Nottingham, UK.

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