The geometry of clinical labs and wellness states from deeply phenotyped humans.
Nat Commun
; 12(1): 3578, 2021 06 11.
Article
em En
| MEDLINE
| ID: mdl-34117230
ABSTRACT
Longitudinal multi-omics measurements are highly valuable in studying heterogeneity in health and disease phenotypes. For thousands of people, we have collected longitudinal multi-omics data. To analyze, interpret and visualize this extremely high-dimensional data, we use the Pareto Task Inference (ParTI) method. We find that the clinical labs data fall within a tetrahedron. We then use all other data types to characterize the four archetypes. We find that the tetrahedron comprises three wellness states, defining a wellness triangular plane, and one aberrant health state that captures aspects of commonality in movement away from wellness. We reveal the tradeoffs that shape the data and their hierarchy, and use longitudinal data to observe individual trajectories. We then demonstrate how the movement on the tetrahedron can be used for detecting unexpected trajectories, which might indicate transitions from health to disease and reveal abnormal conditions, even when all individual blood measurements are in the norm.
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Base de dados:
MEDLINE
Assunto principal:
Fenótipo
/
Biologia de Sistemas
Idioma:
En
Ano de publicação:
2021
Tipo de documento:
Article
País de afiliação:
Estados Unidos