# Metabolomic Signatures of Physical Function and Functional Trajectories in Older Adults: Insights from the ENRGISE Clinical Trial

## TL;DR

This study uses metabolomics to identify metabolic signatures linked to physical function and treatment response in older adults with chronic inflammation.

## Contribution

The study introduces novel metabolic signatures that predict functional trajectories and reveal pharmacologic effects of omega-3 supplementation.

## Key findings

- Baseline metabolomic profiles differed by physical function status, with low grip strength linked to vitamin A metabolism.
- Slower gait speed was associated with higher levels of prostaglandin and eicosanoid metabolites.
- Omega-3 supplementation induced distinct changes in lipid-related pathways despite no clinical outcomes.

## Abstract

Background: Chronic inflammation contributes to functional decline in older adults, yet interventions targeting inflammatory pathways have shown inconsistent results. Metabolomics offers a promising approach to identify biological heterogeneity and uncover molecular signatures underlying differential functional trajectories. Objective: Our objective was to examine whether untargeted serum metabolomics can identify metabolic signatures associated with baseline physical function, functional trajectories, and treatment response in older adults with chronic inflammation participating in the ENRGISE trial. Methods: We performed untargeted metabolomic profiling on serum samples (n = 731) collected at baseline, 6, and 12 months from participants (mean age ≥ 70) enrolled in the ENRGISE pilot randomized trial. Participants were randomized to losartan, omega-3 supplementation, both, or placebo. Functional measures included grip strength and 400 m gait speed. Group-based trajectory modeling classified participants into functional trajectories over 12 months. Partial least squares-discriminant analysis (PLS-DA) and pathway enrichment (mummichog algorithm) were used to identify differentially abundant metabolites and perturbed pathways. Results: Baseline metabolomic profiles differed by physical function status. Participants with low grip strength showed enrichment in vitamin A metabolism pathways, while slower gait speed was associated with higher levels of prostaglandin and eicosanoid metabolites. Baseline metabolic profiles distinguished individuals who later declined versus improved in functional performance. Omega-3 supplementation, but not losartan, induced distinct changes in lipid-related pathways, including fatty acid activation, omega-3 metabolism, and prostaglandin biosynthesis, indicating that individuals responded to these interventions metabolically despite null clinical outcomes. Conclusions: Serum metabolomic signatures were associated with baseline physical function, predicted functional trajectories, and revealed pharmacologic activity of omega-3 supplementation. These findings support the use of metabolomics to uncover biological heterogeneity and inform precision geroscience strategies in aging populations.