A population-based study of precision health assessments using multi-omics network-derived biological functional modules.
Cell Rep Med
; 3(12): 100847, 2022 12 20.
Article
em En
| MEDLINE
| ID: mdl-36493776
ABSTRACT
Recent technological advances in multi-omics and bioinformatics provide an opportunity to develop precision health assessments, which require big data and relevant bioinformatic methods. Here we collect multi-omics data from 4,277 individuals. We calculate the correlations between pairwise features from cross-sectional data and then generate 11 biological functional modules (BFMs) in males and 12 BFMs in females using a community detection algorithm. Using the features in the BFM associated with cardiometabolic health, carotid plaques can be predicted accurately in an independent dataset. We developed a model by comparing individual data with the health baseline in BFMs to assess health status (BFM-ash). Then we apply the model to chronic patients and modify the BFM-ash model to assess the effects of consuming grape seed extract as a dietary supplement. Finally, anomalous BFMs are identified for each subject. Our BFMs and BFM-ash model have huge prospects for application in precision health assessment.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Medicina de Precisão
/
Multiômica
Tipo de estudo:
Observational_studies
/
Prevalence_studies
/
Prognostic_studies
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Risk_factors_studies
Limite:
Female
/
Humans
Idioma:
En
Revista:
Cell Rep Med
Ano de publicação:
2022
Tipo de documento:
Article
País de afiliação:
China