RESUMEN
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.
Asunto(s)
Estilo de Vida , Obesidad , Anciano , Biomarcadores , HDL-Colesterol , Femenino , Humanos , Insulina , MasculinoRESUMEN
Contractile properties of myofibers are dictated by the abundance of myosin heavy chain (MyHC) isoforms. MyHC composition designates muscle function, and its alterations could unravel differential muscle involvement in muscular dystrophies and aging. Current analyses are limited to visual assessments in which myofibers expressing multiple MyHC isoforms are prone to misclassification. As a result, complex patterns and subtle alterations are unidentified. We developed a high-throughput, data-driven myofiber analysis to quantitatively describe the variations in myofibers across the muscle. We investigated alterations in myofiber composition between genotypes, 2 muscles, and 2 age groups. We show that this analysis facilitates the discovery of complex myofiber compositions and its dependency on age, muscle type, and genetic conditions.-Raz, V., Raz, Y., van de Vijver, D., Bindellini, D., van Putten, M., van den Akker, E. B. High-throughput data-driven analysis of myofiber composition reveals muscle-specific disease and age-associated patterns.
Asunto(s)
Envejecimiento/metabolismo , Fibras Musculares Esqueléticas/metabolismo , Distrofias Musculares/metabolismo , Cadenas Pesadas de Miosina/genética , Envejecimiento/genética , Envejecimiento/patología , Animales , Genotipo , Masculino , Ratones , Ratones Endogámicos C57BL , Fibras Musculares Esqueléticas/clasificación , Fibras Musculares Esqueléticas/patología , Distrofias Musculares/genética , Distrofias Musculares/patología , Cadenas Pesadas de Miosina/metabolismo , Isoformas de Proteínas/genética , Isoformas de Proteínas/metabolismoRESUMEN
Progress in high-throughput metabolic profiling provides unprecedented opportunities to obtain insights into the effects of drugs on human metabolism. The Biobanking BioMolecular Research Infrastructure of the Netherlands has constructed an atlas of drug-metabolite associations for 87 commonly prescribed drugs and 150 clinically relevant plasma-based metabolites assessed by proton nuclear magnetic resonance. The atlas includes a meta-analysis of ten cohorts (18,873 persons) and uncovers 1,071 drug-metabolite associations after evaluation of confounders including co-treatment. We show that the effect estimates of statins on metabolites from the cross-sectional study are comparable to those from intervention and genetic observational studies. Further data integration links proton pump inhibitors to circulating metabolites, liver function, hepatic steatosis and the gut microbiome. Our atlas provides a tool for targeted experimental pharmaceutical research and clinical trials to improve drug efficacy, safety and repurposing. We provide a web-based resource for visualization of the atlas (http://bbmri.researchlumc.nl/atlas/).