Profound Perturbation of the Metabolome in Obesity Is Associated with Health Risk.

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Version: Final published version
License: Not specified
Serval ID
serval:BIB_D194EFF94799
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Profound Perturbation of the Metabolome in Obesity Is Associated with Health Risk.
Journal
Cell metabolism
Author(s)
Cirulli E.T., Guo L., Leon Swisher C., Shah N., Huang L., Napier L.A., Kirkness E.F., Spector T.D., Caskey C.T., Thorens B., Venter J.C., Telenti A.
ISSN
1932-7420 (Electronic)
ISSN-L
1550-4131
Publication state
Published
Issued date
05/02/2019
Peer-reviewed
Oui
Volume
29
Number
2
Pages
488-500.e2
Language
english
Notes
Publication types: Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
Publication Status: ppublish
Abstract
Obesity is a heterogeneous phenotype that is crudely measured by body mass index (BMI). There is a need for a more precise yet portable method of phenotyping and categorizing risk in large numbers of people with obesity to advance clinical care and drug development. Here, we used non-targeted metabolomics and whole-genome sequencing to identify metabolic and genetic signatures of obesity. We find that obesity results in profound perturbation of the metabolome; nearly a third of the assayed metabolites associated with changes in BMI. A metabolome signature identifies the healthy obese and lean individuals with abnormal metabolomes-these groups differ in health outcomes and underlying genetic risk. Specifically, an abnormal metabolome associated with a 2- to 5-fold increase in cardiovascular events when comparing individuals who were matched for BMI but had opposing metabolome signatures. Because metabolome profiling identifies clinically meaningful heterogeneity in obesity, this approach could help select patients for clinical trials.
Keywords
Adult, Aged, Aged, 80 and over, Body Mass Index, Cohort Studies, Female, Humans, Male, Metabolomics/methods, Middle Aged, Obesity/epidemiology, Obesity/genetics, Obesity/metabolism, Risk Factors, Twins, Whole Genome Sequencing/methods, MC4R, health, human genetics, metabolomics, obesity, polygenic risk scores, rare variants
Pubmed
Web of science
Open Access
Yes
Create date
30/10/2018 12:42
Last modification date
21/11/2022 8:25
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