ProtFI, an efficient frailty-trained proteomics-based biomarker of aging, robustly predicts age-related decline.

Swier Garst, Lieke Kuiper, Erik van den Akker, Niels van den Berg, Mohsen Ghanbari, Simon Mooijaart, Marian Beekman, Marcel Reinders, P Eline Slagboom, Joyce van Meurs

Delft Bioinformatics Lab, Delft University of Technology, 2628 XE Delft, Zuid-Holland, the Netherlands; Section of Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands. · pubmed

Paper

Abstract

Many molecular aging biomarkers have been developed to capture heterogeneity in individual aging rates. Yet, systematic comparison of the modeling choices underlying these biomarkers has been limited. In this study, we trained aging biomarkers on the Rockwood frailty index (FI) and all-cause mortality using UK Biobank Olink proteomics and metabolomics (

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Research summary

The paper claims that ProtFI, a frailty-trained proteomics-based biomarker, can robustly predict age-related decline. This research is relevant as it addresses the heterogeneity in aging rates and aims to develop biomarkers that could potentially lead to a better understanding of the aging process itself.

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