Advanced glycation end-products and metabolomics are independently associated with frailty: the longitudinal Doetinchem Cohort Study.

Skin autofluorescence (SAF), reflecting advanced glycation end-products' accumulation in tissue, has been proposed as a non-invasive aging biomarker. Yet, SAF has not been compared to well-established blood-based aging biomarkers such as MetaboHealth in association with frailty. Furthermore, no previous study determined the longitudinal association of SAF with frailty.

Association between metabolomics-based biomarker scores and 10-year cognitive decline in men and women. The Doetinchem Cohort Study.

Background: Metabolomic scores based on age (MetaboAge) and mortality (MetaboHealth) are considered indicators of overall health, but their association with cognition in the general population is unknown. Therefore, the association between MetaboAge/MetaboHealth and level and decline in cognition was studied, as were differences between men and women.

Methods: Data of 2821 participants (50% women, age range 45-75) from the Doetinchem Cohort Study was used.

Comparison of dopamine release and uptake parameters across sex, species and striatal subregions.

For over four decades, fast-scan cyclic voltammetry (FSCV) has been used to selectively measure neurotransmitters such as dopamine (DA) with high spatial and temporal resolution, providing detailed information about the regulation of DA in the extracellular space. FSCV is an optimal method for determining concentrations of stimulus-evoked DA in brain tissue. When modelling diseases involving disturbances in DA transmission, preclinical rodent models are especially useful because of the availability of specialized tools and techniques that serve as a foundation for translational research.

NMR metabolomics-guided DNA methylation mortality predictors.

Background: H-NMR metabolomics and DNA methylation in blood are widely known biomarkers predicting age-related physiological decline and mortality yet exert mutually independent mortality and frailty signals.

Methods: Leveraging multi-omics data in four Dutch population studies (N = 5238, ∼40% of which male) we investigated whether the mortality signal captured by H-NMR metabolomics could guide the construction of DNA methylation-based mortality predictors.

Findings: We trained DNA methylation-based surrogates for 64 metabolomic analytes and found that analytes marking inflammation, fluid balance, or HDL/VLDL metabolism could be accurately reconstructed using DNA-methylation assays.

Lifestyle factors and metabolomic aging biomarkers: Meta-analysis of cross-sectional and longitudinal associations in three prospective cohorts.

Biological age uses biophysiological information to capture a person's age-related risk of adverse outcomes. MetaboAge and MetaboHealth are metabolomics-based biomarkers of biological age trained on chronological age and mortality risk, respectively. Lifestyle factors contribute to the extent chronological and biological age differ.