TY - CHAP
T1 - Personal Dense Dynamic Data Clouds Connect Systems Biomedicine to Scientific Wellness
AU - Omenn, Gilbert S.
AU - Magis, Andrew T.
AU - Price, Nathan D.
AU - Hood, Leroy
N1 - Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.
PY - 2022
Y1 - 2022
N2 - The dramatic convergence of molecular biology, genomics, proteomics, metabolomics, bioinformatics, and artificial intelligence has provided a substrate for deep understanding of the biological basis of health and disease. Systems biology is a holistic, dynamic, integrative, cross-disciplinary approach to biological complexity that embraces experimentation, technology, computation, and clinical translation. Systems Medicine integrates genome analyses and longitudinal deep phenotyping with biological pathways and networks to understand mechanisms of disease, identify relevant blood biomarkers, define druggable molecular targets, and enhance the maintenance or restoration of wellness. Two programs initiated our understanding of data-driven population-based wellness. The Pioneer 100 Study of Scientific Wellness and the much larger Arivale commercial program that followed had two spectacular results: demonstrating the feasibility and utility of collecting longitudinal multiomic data, and then generating dense, dynamic data clouds for each individual to utilize actionable metrics for promoting health and preventing disease when combined with personalized coaching. Future developments in these domains will enable better population health and personal, preventive, predictive, participatory (P4) health care.
AB - The dramatic convergence of molecular biology, genomics, proteomics, metabolomics, bioinformatics, and artificial intelligence has provided a substrate for deep understanding of the biological basis of health and disease. Systems biology is a holistic, dynamic, integrative, cross-disciplinary approach to biological complexity that embraces experimentation, technology, computation, and clinical translation. Systems Medicine integrates genome analyses and longitudinal deep phenotyping with biological pathways and networks to understand mechanisms of disease, identify relevant blood biomarkers, define druggable molecular targets, and enhance the maintenance or restoration of wellness. Two programs initiated our understanding of data-driven population-based wellness. The Pioneer 100 Study of Scientific Wellness and the much larger Arivale commercial program that followed had two spectacular results: demonstrating the feasibility and utility of collecting longitudinal multiomic data, and then generating dense, dynamic data clouds for each individual to utilize actionable metrics for promoting health and preventing disease when combined with personalized coaching. Future developments in these domains will enable better population health and personal, preventive, predictive, participatory (P4) health care.
KW - Biological aging
KW - Correlation networks
KW - Dense dynamic data clouds
KW - Metabolome
KW - Microbiome
KW - P4 health care
KW - Personalized coaching
KW - Polygenic risk scores
KW - Scientific wellness
KW - Systems biology
UR - https://www.scopus.com/pages/publications/85128544786
U2 - 10.1007/978-1-0716-2265-0_15
DO - 10.1007/978-1-0716-2265-0_15
M3 - Chapter
C2 - 35437729
AN - SCOPUS:85128544786
T3 - Methods in Molecular Biology
SP - 315
EP - 334
BT - Methods in Molecular Biology
PB - Humana Press Inc.
ER -