The Female Biomarker Challenge: Sex-Specific Network Robustness Constrains Biological Age Estimation and Geroscience Trial Design

Abstract

A current impediment to bringing anti-aging therapies to market is the lack of accepted clinical endpoints that fit within reasonable trial time horizons and budgets. Recent theoretical models predict that sparse sampling of interconnected physiological subsystems can capture the essential dynamics of aging, suggesting that sparse biomarker panels could serve as surrogate endpoints for geroscience clinical trials. Here, we test this prediction using NHANES 1999-2018 data linked to the National Death Index. To overcome variable dropout caused by between-subsystem collinearity, we developed a two-stage dimensionality reduction architecture: Generalized Additive Models first compress each multi-variable subsystem into a single non-linear mortality risk score, which is then integrated via Levine's biological age algorithm. The resulting biological age estimates outperformed chronological age in predicting mortality and all fourteen age-related diseases examined, and detected the effects of diet, sleep, and physical activity on biological aging. Sex-stratified analysis revealed that the mortality sex gap penetrates to every physiological subsystem measured, with males and females requiring different biomarker panels - consistent with sex-specific differences in physiological network topology. Critically, male biological age was substantially more sensitive to both mortality prediction and lifestyle interventions than female biological age, a robustness-sensitivity trade-off predicted by network resilience theory. These findings carry direct implications for trial design: older males currently offer the most favourable signal-to-noise ratio for proof-of-concept geroscience trials using standard pathology tests, while the development of validated female-specific biomarker panels - capable of resolving the more distributed aging signal imposed by greater female physiological robustness - should be treated as an urgent and independent research priority.