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

doi:10.3389/fnagi.2020.00136

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

Research output: Contribution to journal › Article › peer-review

21 Citations (Scopus)

2 Downloads (Pure)

Abstract

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 language	English
Article number	136
Number of pages	12
Journal	Frontiers in Genetics
Volume	12
DOIs	https://doi.org/10.3389/fnagi.2020.00136
Publication status	Published - 25 May 2020

Keywords

propagation of aging
network analysis
digital medicine
aging
inflammaging
DNA METHYLATION
CHRONIC INFLAMMATION
CELLULAR SENESCENCE
PYRAMIDAL NEURONS
LIFE-SPAN
DYNAMICS
CANCER
MODELS
MECHANISMS
BIOMARKERS

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.3389/fnagi.2020.00136Licence: CC BY

Whitwell_etal_fnagi_Human_body_VOR
Copyright © 2020 Whitwell, Bacalini, Blyuss, Chen, Garagnani, Gordleeva, Jalan, Ivanchenko, Kanakov, Kustikova, Mariño, Meyerov, Ullner, Franceschi and Zaikin. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. https://creativecommons.org/licenses/by/4.0/
Final published version, 1.31 MBLicence: CC BY

Cite this

Whitwell, H. J., Bacalini, M. G., Blyuss, O., Chen, S., Garagnani, P., Gordleeva, S. Y., Jalan, S., Ivanchenko, M., Kanakov, O., Kustikova, V., Mariño, I. P., Meyerov, I., Ullner, E., Franceschi, C., & Zaikin, A. (2020). The Human Body as a Super Network: Digital Methods to Analyze the Propagation of Aging. Frontiers in Genetics, 12, [136]. https://doi.org/10.3389/fnagi.2020.00136

@article{479b504c634246b6bf5704d86692fc54,

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

abstract = "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.",

keywords = "propagation of aging, network analysis, digital medicine, aging, inflammaging, DNA METHYLATION, CHRONIC INFLAMMATION, CELLULAR SENESCENCE, PYRAMIDAL NEURONS, LIFE-SPAN, DYNAMICS, CANCER, MODELS, MECHANISMS, BIOMARKERS",

author = "Whitwell, {Harry J.} and Bacalini, {Maria Giulia} and Oleg Blyuss and Shangbin Chen and Paolo Garagnani and Gordleeva, {Susan Yu} and Sarika Jalan and Mikhail Ivanchenko and Oleg Kanakov and Valentina Kustikova and Mari{\~n}o, {Ines P.} and Iosif Meyerov and Ekkehard Ullner and Claudio Franceschi and Alexey Zaikin",

note = "We acknowledge support by the grant of the Ministry of Education and Science of the Russian Federation Agreement No. 074-02-2018-330. SG acknowledges the grant of the Ministry of Education and Science of the RT No. 075-15-2019-1192 and RFBR No. 20-32-70081. HW and AZ thank MRC grant MR/R02524X/1. IM also acknowledges partial support by the Agencia Estatal de Investigaci{\'o}n of Spain (TEC2017-86921-C2_1_R and RTI2018-099655-B-I00). All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication. CF established this research collaboration. CF, AZ, SG, MI and HW conceived the manuscript. All authors contributed to writing the manuscript. SG created the figures. HW compiled and edited the manuscript. ",

year = "2020",

month = may,

day = "25",

doi = "10.3389/fnagi.2020.00136",

language = "English",

volume = "12",

journal = "Frontiers in Genetics",

issn = "1664-8021",

publisher = "Frontiers Media S.A.",

}

TY - JOUR

T1 - The Human Body as a Super Network

T2 - Digital Methods to Analyze the Propagation of Aging

AU - Whitwell, Harry J.

AU - Bacalini, Maria Giulia

AU - Blyuss, Oleg

AU - Chen, Shangbin

AU - Garagnani, Paolo

AU - Gordleeva, Susan Yu

AU - Jalan, Sarika

AU - Ivanchenko, Mikhail

AU - Kanakov, Oleg

AU - Kustikova, Valentina

AU - Mariño, Ines P.

AU - Meyerov, Iosif

AU - Ullner, Ekkehard

AU - Franceschi, Claudio

AU - Zaikin, Alexey

N1 - We acknowledge support by the grant of the Ministry of Education and Science of the Russian Federation Agreement No. 074-02-2018-330. SG acknowledges the grant of the Ministry of Education and Science of the RT No. 075-15-2019-1192 and RFBR No. 20-32-70081. HW and AZ thank MRC grant MR/R02524X/1. IM also acknowledges partial support by the Agencia Estatal de Investigación of Spain (TEC2017-86921-C2_1_R and RTI2018-099655-B-I00). All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication. CF established this research collaboration. CF, AZ, SG, MI and HW conceived the manuscript. All authors contributed to writing the manuscript. SG created the figures. HW compiled and edited the manuscript.

PY - 2020/5/25

Y1 - 2020/5/25

N2 - 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.

AB - 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.

KW - propagation of aging

KW - network analysis

KW - digital medicine

KW - aging

KW - inflammaging

KW - DNA METHYLATION

KW - CHRONIC INFLAMMATION

KW - CELLULAR SENESCENCE

KW - PYRAMIDAL NEURONS

KW - LIFE-SPAN

KW - DYNAMICS

KW - CANCER

KW - MODELS

KW - MECHANISMS

KW - BIOMARKERS

UR - http://www.scopus.com/inward/record.url?scp=85086269052&partnerID=8YFLogxK

U2 - 10.3389/fnagi.2020.00136

DO - 10.3389/fnagi.2020.00136

M3 - Article

VL - 12

JO - Frontiers in Genetics

JF - Frontiers in Genetics

SN - 1664-8021

M1 - 136

ER -

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

Abstract

Keywords

UN SDGs

Access to Document

Other files and links

Fingerprint

Cite this