The Human Body as a Super Network: Digital Methods to Analyze the Propagation of Aging

Harry J. Whitwell, Maria Giulia Bacalini, Oleg Blyuss, Shangbin Chen, Paolo Garagnani, Susan Yu Gordleeva, Sarika Jalan, Mikhail Ivanchenko, Oleg Kanakov, Valentina Kustikova, Ines P. Mariño, Iosif Meyerov, Ekkehard Ullner, Claudio Franceschi, Alexey Zaikin

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    10 Citations (Scopus)
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    Biological aging is a complex process involving multiple biological processes. These can be understood theoretically though considering them as individual networks—e.g., epigenetic networks, cell-cell networks (such as astroglial networks), and population genetics. Mathematical modeling allows the combination of such networks so that they may be studied in unison, to better understand how the so-called “seven pillars of aging” combine and to generate hypothesis for treating aging as a condition at relatively early biological ages. In this review, we consider how recent progression in mathematical modeling can be utilized to investigate aging, particularly in, but not exclusive to, the context of degenerative neuronal disease. We also consider how the latest techniques for generating biomarker models for disease prediction, such as longitudinal analysis and parenclitic analysis can be applied to as both biomarker platforms for aging, as well as to better understand the inescapable condition. This review is written by a highly diverse and multi-disciplinary team of scientists from across the globe and calls for greater collaboration between diverse fields of research.
    Original languageEnglish
    Article number136
    Number of pages12
    JournalFrontiers in Aging Neuroscience
    Publication statusPublished - 25 May 2020


    • aging
    • digital medicine
    • inflammaging
    • network analysis
    • propagation of aging


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