100-Year Human Aging Study

All currently existing longevity measures are surrogate endpoints that have not been prospectively validated against actual mortality and aging outcomes. The 100-Year Human Aging Study is a prospective, pragmatic, observational trial that addresses this gap by enrolling participants in comprehensive clinical screening and following them longitudinally until death to determine which measurements - alone and in combination - are predictive of mortality, serious disease, and functional disability.

The study prioritizes dynamic measurements: the physiological, cognitive, social, and environmental capacities that change with aging and are most likely to carry predictive signal for mortality and functional outcomes. These include cardiorespiratory fitness (cardiopulmonary exercise testing with ventilatory threshold analysis), strength (grip, explosive power, functional movement), mobility and balance, neurocognitive performance, sensory function (vision, hearing, smell, light touch), and metabolic function (oral glucose tolerance, continuous glucose monitoring), in addition to other testing. Structural and imaging assessments include body composition and bone mineral density by DEXA, echocardiography, resting and stress electrocardiography, spirometry, retinal fundus photography, and vascular ultrasound. Laboratory measures are drawn on-site and processed through a CLIA-certified reference laboratory. Complete medical, surgical, family, social, occupational, and environmental histories are obtained at each visit.

Participation ranges from single-service visits - including standalone DEXA, cardiopulmonary exercise testing, laboratory panel testing, and sleep studies - to the full two-visit comprehensive screening battery. All participation pathways contribute clinical data to the longitudinal mortality and aging outcomes linkage framework regardless of service level. Participants are encouraged to return for repeat testing to build longitudinal health trajectories across the lifespan.

At enrollment and across longitudinal follow-up, the study platform generates individualized investigational constructs including biological age estimate, predicted death age, and predicted cause of death profile. These are explicitly investigational hypotheses, not validated clinical standards. Their predictive validity relative to actual mortality, aging outcomes, and functional disability is a central scientific question this study is designed to answer, both for individual measures and for composite multi-system models.

All data are archived in their highest-dimensional raw form to preserve the ability to apply future analytical methods retroactively. Participants are followed with periodic contact and offered repeat screening throughout the lifespan. Longitudinal outcomes ascertainment includes all-cause mortality, cause-specific mortality, incident serious health events, chronic disease diagnosis, functional independence, disability status, and health behavior change.

Study sites and participation pathways. The 100-Year Human Aging Study is conducted across all Longevity Metrics participation pathways, current and future: the Boulder Human Performance Lab (fixed flagship laboratory); mobile screening units including the Health Ahead Bus; any additional fixed or mobile Longevity Metrics laboratory established during the study period; and an online participation pathway through which participants enroll and contribute structured data without in-person screening. All pathways operate under a single protocol with identical procedures, data management, informed consent, and safety standards.

This study is one of four that compound into one system. The Human Observatory Study (NCT07646782) validates sociodemographic and environmental data against the same outcomes, and receives each model's geographic residuals. The Health Ahead Comparative Effectiveness Study (NCT07669168) moves the screening toward increasing automation and mobility while maintaining quality. The Longevity Metrics AI/ML Development Study (NCT pending approval) builds the models that make automation, prediction, and broad utilization possible. This study supplies the clinical data and validates what it means for health, disease, disability, and death.