Temporal metabolic response yields a dynamic biosignature of inflammation

Jesse T Peach; Stephanie M Wilson; Logan D Gunderson; Lizzi Frothingham; Tan Tran; Seth T Walk; Carl J Yeoman; Brian Bothner; Mary P Miles

doi:10.1016/j.isci.2021.102817

Temporal metabolic response yields a dynamic biosignature of inflammation

iScience. 2021 Jul 7;24(8):102817. doi: 10.1016/j.isci.2021.102817. eCollection 2021 Aug 20.

Authors

Jesse T Peach¹, Stephanie M Wilson², Logan D Gunderson¹, Lizzi Frothingham¹, Tan Tran³, Seth T Walk⁴, Carl J Yeoman⁵, Brian Bothner¹, Mary P Miles²

Affiliations

¹ Department of Chemistry and Biochemistry, Montana State University, Bozeman, MT 59718, USA.
² Department of Health and Human Development, Montana State University, Bozeman, MT 59718, USA.
³ Department of Math, Montana State University, Bozeman, MT 59718, USA.
⁴ Department of Microbiology and Immunology, Montana State University, Bozeman, MT 59718, USA.
⁵ Department of Range and Animal Sciences, Montana State University, Bozeman, MT 59718, USA.

Abstract

Chronic low-grade inflammation is a subclinical condition directly and indirectly linked to the development of a wide range of diseases responsible for the vast majority of morbidity. To examine mechanisms coupled to chronic disease, a group of overweight and obese human subjects without known inflammatory diseases participated in a high-fat meal challenge as an acute inflammation stimulus. Analysis of serum metabolites grouped by baseline cytokine levels revealed that single samples had little power in differentiating groups. However, an analysis that incorporated temporal response separated inflammatory response phenotypes and allowed us to create a metabolic signature of inflammation which revealed metabolic components that are crucial to a cytokine-mediated inflammation response. The use of temporal response, rather than a single time point, improved metabolomic prediction of high postprandial inflammation responses and led to the development of a dynamic biosignature as a potential tool for stratifying risk to a wide range of diseases.

Keywords: Metabolomics; Pathophysiology; Systems biology.