What question did this study set out to answer?

This study aims to compare various markers of biological aging to evaluate their effectiveness in predicting health outcomes as individuals age.

March 29, 2026Open Access

Comprehensive cross-sectional and longitudinal comparison of sixteen markers of biological aging from the Berlin Aging Study II

Key Points

This study aims to compare various markers of biological aging to evaluate their effectiveness in predicting health outcomes as individuals age.
Analyzed 16 biological aging markers, including epigenetic clocks, proteomics, and telomere length.
Conducted cross-sectional and longitudinal evaluations of age-associated outcomes.
Included assessments of frailty, mobility, cognitive function, and chronic disease.
Studied a sample of 1083 participants with a mean age of 68.3 years over an average follow-up of 7.4 years.
Allostatic Load Index and DunedinPACE had the strongest correlations with age-related health outcomes.
Both biomarkers improved a logistic regression model’s accuracy by 24 percentage points for predicting metabolic syndrome and frailty.
The study provides insights into the strengths and weaknesses of different biological aging indicators.

Abstract

Abstract Background The disproportionate increase in lifespan compared to healthspan over the past decades results in a growing proportion of life marked by diseases, even if incidence rates are falling in some cases. However, not everyone ages at the same pace and some people remain in good health and preserve physical and cognitive function into old age. To quantify inter-individual differences in the biological aging process, numerous indicators of biological age have been developed. Methods In this study, we analyzed 16 measures of biological aging including epigenetic clocks, proteomics clock, telomere length, and SkinAge, laboratory composite markers (BioAge, Allostatic Load), psychological aging, and Brain Age. These age markers were evaluated cross-sectionally as well as longitudinally in the context of age-associated outcomes covering frailty, mobility, cognitive function, depressive symptoms, autonomy in daily life, nutrition, morbidity, and chronic disease in participants of the Berlin Aging Study II (BASE-II). Results Here, we analyze longitudinal data from 1083 participants (mean age of 68.3 years at baseline, 52% women) with an average follow-up period of 7.4 years. Allostatic Load Index and DunedinPACE show the strongest and most consistent cross-sectional and longitudinal associations with age-associated phenotypes. Furthermore, both biomarkers individually increase the accuracy of a logistic regression model trained to predict incident cases of Metabolic Syndrome, high cardiovascular risk (Lifes’s Simple 7) as well as incident frailty (Fried’s frailty index) 7.4 years after baseline examination by up to 24 percentage points. Conclusions Our findings support the previously shown distinction between indicators of aging and provide a comprehensive overview of their individual strengths and weaknesses in the context of wide variety of age-associated phenotypes.

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