Characterizing human postprandial metabolic response and revealing differences

There is an emerging need to analyze and extract insights from time-resolved metabolomics data collected through challenge tests since such data holds the promise to reveal both static and dynamic markers of metabolic diseases.

In our latest manuscript, using the challenge data collected from 299 individuals from the COPSAC2000 cohort, we demonstrate how to preserve the multiway nature of time-resolved metabolomics data and how to analyze such data in order to reveal underlying patterns that can be interpreted as static and dynamic markers.

The paper not only demonstrates an improved analysis approach for time-resolved data collected during challenge tests but also extracts novel insights such as sex differences and metabolites behaving differently in fasting and dynamic states - generating new hypotheses to be investigated further.

See the paper for details:

S. Yan, L. Li, D. Horner, P. Ebrahimi, B. Chawes, L. O. Dragsted, M. A. Rasmussen, A. K. Smilde, E. Acar. Characterizing human postprandial metabolic response using multiway data analysis, bioRxiv.