[A machine learning model using gut microbiome data for predicting changes of trimethylamine-N-oxide in healthy volunteers after choline consumption].

Journal: Nan fang yi ke da xue xue bao = Journal of Southern Medical University

PMID: 28377341

Abstract

OBJECTIVE: To establish a machine learning model based on gut microbiota for predicting the level of trimethylamine N-oxide (TMAO) metabolism in vivo after choline intake to provide guidance of individualized precision diet and evidence for screening population at high risks of cardiovascular disease.

Authors

Jun-Qi Lu

Department of Environmental Health, School of Public Health, Southern Medical University, Guangzhou 510515, China.E-mail: goodlujunqi@163.com.
Shan Wang

Department of Echocardiography & Noninvasive Cardiology Laboratory, Sichuan Academy of Medical Sciences, Sichuan Provincial People's Hospital, Chengdu, Sichuan, 610047, China.
Jia Yin
Shan Wu

Department of Endoscopy, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China.
Yan He

School of Biology & Engineering, Guizhou Medical University, Guiyang, Guizhou Province, China.
Hui-Min Zheng
Hua-Fang Sheng
Hong-Wei Zhou

Keywords

Algorithms Choline Eggs Gastrointestinal Microbiome Healthy Volunteers Humans Machine Learning Methylamines Oxides RNA, Ribosomal, 16S

External Resources

View on PubMed Access via DOI PubMed (28377341)

[A machine learning model using gut microbiome data for predicting changes of trimethylamine-N-oxide in healthy volunteers after choline consumption].

Abstract

Authors

Keywords

External Resources

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