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

• Published in: Cell metabolism Vol. 29; no. 2; pp. 488 - 500.e2
• Main Authors: Cirulli, Elizabeth T., Guo, Lining, Leon Swisher, Christine, Shah, Naisha, Huang, Lei, Napier, Lori A., Kirkness, Ewen F., Spector, Tim D., Caskey, C. Thomas, Thorens, Bernard, Venter, J. Craig, Telenti, Amalio
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 05.02.2019; Cell Press
• Subjects: Adult; Aged; Aged, 80 and over; Body Mass Index; Cohort Studies; Female; health; human genetics; Humans; Male; MC4R; metabolomics; Metabolomics - methods; Middle Aged; obesity; Obesity - epidemiology; Obesity - genetics; Obesity - metabolism; polygenic risk scores; rare variants; Risk Factors; Twins; Whole Genome Sequencing - methods; rare variants; MC4R; human genetics; metabolomics; health; obesity; polygenic risk scores
• ISSN: 1550-4131; 1932-7420; 1932-7420
• DOI: 10.1016/j.cmet.2018.09.022

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. [Display omitted] •Obesity results in a profound perturbation of the plasma metabolome•At any given BMI, abnormal metabolomes associate with different health outcomes•At any given BMI, different genetic obesity risks do not change the metabolome•A metabolome signature effectively tracks changes in obesity Obesity is a heterogeneous and complex disease that is imprecisely measured by BMI. Cirulli et al. used non-targeted metabolomics and whole-genome sequencing to identify metabolic and genetic signatures of obesity and find that the metabolome captures clinically relevant phenotypes of obesity and is a better health predictor than genetic risk.