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A population-based study of precision health assessments using multi-omics network-derived biological functional modules.
Zhang, Wei; Wan, Ziyun; Li, Xiaoyu; Li, Rui; Luo, Lihua; Song, Zijun; Miao, Yu; Li, Zhiming; Wang, Shiyu; Shan, Ying; Li, Yan; Chen, Bangwei; Zhen, Hefu; Sun, Yuzhe; Fang, Mingyan; Ding, Jiahong; Yan, Yizhen; Zong, Yang; Wang, Zhen; Zhang, Wenwei; Yang, Huanming; Yang, Shuang; Wang, Jian; Jin, Xin; Wang, Ru; Chen, Peijie; Min, Junxia; Zeng, Yi; Li, Tao; Xu, Xun; Nie, Chao.
Afiliación
  • Zhang W; BGI-Shenzhen, Shenzhen 518083, China; China National GeneBank, Shenzhen 518120, China.
  • Wan Z; BGI-Shenzhen, Shenzhen 518083, China; China National GeneBank, Shenzhen 518120, China.
  • Li X; BGI-Shenzhen, Shenzhen 518083, China; China National GeneBank, Shenzhen 518120, China; BGI Education Center, University of the Chinese Academy of Sciences, Shenzhen 518083, China.
  • Li R; BGI-Shenzhen, Shenzhen 518083, China; China National GeneBank, Shenzhen 518120, China.
  • Luo L; BGI-Shenzhen, Shenzhen 518083, China; China National GeneBank, Shenzhen 518120, China; BGI Education Center, University of the Chinese Academy of Sciences, Shenzhen 518083, China.
  • Song Z; The First Affiliated Hospital, Institute of Translational Medicine, School of Medicine, Zhejiang University, Hangzhou, China.
  • Miao Y; BGI-Shenzhen, Shenzhen 518083, China; China National GeneBank, Shenzhen 518120, China; BGI Education Center, University of the Chinese Academy of Sciences, Shenzhen 518083, China.
  • Li Z; BGI-Shenzhen, Shenzhen 518083, China; China National GeneBank, Shenzhen 518120, China.
  • Wang S; BGI-Shenzhen, Shenzhen 518083, China; China National GeneBank, Shenzhen 518120, China; BGI Education Center, University of the Chinese Academy of Sciences, Shenzhen 518083, China.
  • Shan Y; BGI-Shenzhen, Shenzhen 518083, China; China National GeneBank, Shenzhen 518120, China.
  • Li Y; BGI-Shenzhen, Shenzhen 518083, China; China National GeneBank, Shenzhen 518120, China.
  • Chen B; BGI-Shenzhen, Shenzhen 518083, China; China National GeneBank, Shenzhen 518120, China; School of Biology and Biological Engineering, South China University of Technology, Guangzhou 510006, China.
  • Zhen H; BGI-Shenzhen, Shenzhen 518083, China; China National GeneBank, Shenzhen 518120, China.
  • Sun Y; BGI-Shenzhen, Shenzhen 518083, China; China National GeneBank, Shenzhen 518120, China.
  • Fang M; BGI-Shenzhen, Shenzhen 518083, China; China National GeneBank, Shenzhen 518120, China.
  • Ding J; BGI-Shenzhen, Shenzhen 518083, China; China National GeneBank, Shenzhen 518120, China.
  • Yan Y; BGI-Shenzhen, Shenzhen 518083, China; China National GeneBank, Shenzhen 518120, China.
  • Zong Y; BGI-Shenzhen, Shenzhen 518083, China; China National GeneBank, Shenzhen 518120, China.
  • Wang Z; BGI-Shenzhen, Shenzhen 518083, China; China National GeneBank, Shenzhen 518120, China.
  • Zhang W; BGI-Shenzhen, Shenzhen 518083, China; China National GeneBank, Shenzhen 518120, China.
  • Yang H; BGI-Shenzhen, Shenzhen 518083, China; China National GeneBank, Shenzhen 518120, China; James D. Watson Institute of Genome Sciences, Hangzhou 310058, China.
  • Yang S; BGI-Shenzhen, Shenzhen 518083, China; China National GeneBank, Shenzhen 518120, China.
  • Wang J; BGI-Shenzhen, Shenzhen 518083, China; China National GeneBank, Shenzhen 518120, China; James D. Watson Institute of Genome Sciences, Hangzhou 310058, China.
  • Jin X; BGI-Shenzhen, Shenzhen 518083, China; China National GeneBank, Shenzhen 518120, China.
  • Wang R; School of Exercise and Health, Shanghai Frontiers Science Research Base of Exercise and Metabolic Health, Shanghai University of Sport, Shanghai, China.
  • Chen P; School of Exercise and Health, Shanghai Frontiers Science Research Base of Exercise and Metabolic Health, Shanghai University of Sport, Shanghai, China.
  • Min J; The First Affiliated Hospital, Institute of Translational Medicine, School of Medicine, Zhejiang University, Hangzhou, China.
  • Zeng Y; Center for Healthy Aging and Development Studies, National School of Development, Peking University, Beijing, China.
  • Li T; BGI-Shenzhen, Shenzhen 518083, China; China National GeneBank, Shenzhen 518120, China.
  • Xu X; BGI-Shenzhen, Shenzhen 518083, China; China National GeneBank, Shenzhen 518120, China.
  • Nie C; BGI-Shenzhen, Shenzhen 518083, China; China National GeneBank, Shenzhen 518120, China. Electronic address: niechao@genomics.cn.
Cell Rep Med ; 3(12): 100847, 2022 12 20.
Article en En | MEDLINE | ID: mdl-36493776
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.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Medicina de Precisión / Multiómica Tipo de estudio: Observational_studies / Prevalence_studies / Prognostic_studies / Risk_factors_studies Aspecto: Patient_preference Límite: Female / Humans Idioma: En Revista: Cell Rep Med Año: 2022 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Medicina de Precisión / Multiómica Tipo de estudio: Observational_studies / Prevalence_studies / Prognostic_studies / Risk_factors_studies Aspecto: Patient_preference Límite: Female / Humans Idioma: En Revista: Cell Rep Med Año: 2022 Tipo del documento: Article País de afiliación: China
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