PLIS

PLIS: A metabolomic response monitor to a lifestyle intervention study in older adults

Bogaards, Fatih A. (Leiden University Medical Center; Wageningen University & Research; Leiden Computational Biology Center)
Gehrmann, Thies (Leiden University Medical Center; Leiden Computational Biology Center)
Beekman, Marian (Leiden University Medical Center)
van den Akker, E.B. (TU Delft Pattern Recognition and Bioinformatics; Leiden University Medical Center; Leiden Computational Biology Center)
van de Rest, Ondine (Wageningen University & Research)
Hangelbroek, Roland W.J. (Wageningen University & Research)
Noordam, Raymond (Leiden University Medical Center)
Mooijaart, Simon P. (Leiden University Medical Center)
Reinders, M.J.T. (TU Delft Pattern Recognition and Bioinformatics; Leiden Computational Biology Center)

2022

The response to lifestyle intervention studies is often heterogeneous, especially in older adults. Subtle responses that may represent a health gain for individuals are not always detected by classical health variables, stressing the need for novel biomarkers that detect intermediate changes in metabolic, inflammatory, and immunity-related health. Here, our aim was to develop and validate a molecular multivariate biomarker maximally sensitive to the individual effect of a lifestyle intervention; the Personalized Lifestyle Intervention Status (PLIS). We used 1 H-NMR fasting blood metabolite measurements from before and after the 13-week combined physical and nutritional Growing Old TOgether (GOTO) lifestyle intervention study in combination with a fivefold cross-validation and a bootstrapping method to train a separate PLIS score for men and women. The PLIS scores consisted of 14 and four metabolites for females and males, respectively. Performance of the PLIS score in tracking health gain was illustrated by association of the sex-specific PLIS scores with several classical metabolic health markers, such as BMI, trunk fat%, fasting HDL cholesterol, and fasting insulin, the primary outcome of the GOTO study. We also showed that the baseline PLIS score indicated which participants respond positively to the intervention. Finally, we explored PLIS in an independent physical activity lifestyle intervention study, showing similar, albeit remarkably weaker, associations of PLIS with classical metabolic health markers. To conclude, we found that the sex-specific PLIS score was able to track the individual short-term metabolic health gain of the GOTO lifestyle intervention study. The methodology used to train the PLIS score potentially provides a useful instrument to track personal responses and predict the participant's health benefit in lifestyle interventions similar to the GOTO study.

bioinformatics
healthy ageing
lifestyle intervention
machine learning
metabolomics
response monitor

http://resolver.tudelft.nl/uuid:3788ac3f-5f2b-4820-8047-9ad7eaacf886

https://doi.org/10.1096/fj.202201037R

FASEB journal : official publication of the Federation of American Societies for Experimental Biology, 36 (11), e22578

Institutional Repository

journal article

© 2022 Fatih A. Bogaards, Thies Gehrmann, Marian Beekman, E.B. van den Akker, Ondine van de Rest, Roland W.J. Hangelbroek, Raymond Noordam, Simon P. Mooijaart, M.J.T. Reinders, More Authors