Machine learning of human plasma lipidomes for obesity estimation in a large population cohort

Obesity is associated with changes in the plasma lipids. Although simple lipid quantification is routinely used, plasma lipids are rarely investigated at the level of individual molecules. We aimed at predicting different measures of obesity based on the plasma lipidome in a large population cohort...

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Veröffentlicht in:	PLoS biology 2019-10, Vol.17 (10), p.e3000443
Hauptverfasser:	Gerl, Mathias J, Klose, Christian, Surma, Michal A, Fernandez, Celine, Melander, Olle, Männistö, Satu, Borodulin, Katja, Havulinna, Aki S, Salomaa, Veikko, Ikonen, Elina, Cannistraci, Carlo V, Simons, Kai
Format:	Artikel
Sprache:	eng
Schlagworte:	Adipose Tissue - metabolism Analysis Artificial intelligence Automation Bioengineering Biology and Life Sciences Biomarkers Biomarkers - blood Blood lipids Blood plasma Body fat Body Fat Distribution - statistics & numerical data Body mass Body Mass Index Body size Cardiovascular disease Cholesterol Cohort Studies Correlation analysis Density Desaturase Diabetes Female Finland Genomes High density lipoprotein Hip Humans Insulin resistance Learning algorithms Lipid Metabolism Lipidomics Lipids Low density lipoprotein Low density lipoproteins Machine Learning Male Mass spectrometry Medicine and Health Sciences Metabolism Metabolites Modelling Models, Statistical Mortality Nutrition Obesity Obesity - blood Obesity - diagnosis Plasma Regression analysis Risk assessment Sex Factors Shotguns Software Species Spectrometry Sphingomyelin Sphingomyelins - blood Type 2 diabetes Waist Circumference Waist-Hip Ratio
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