Activities of Daily Living, Aging, Aging Well, All-Cause Mortality, Cardiovascular Diseases, Cognitive Dysfunction, Dementia, Disability Physical, Frailty, Health-Related Quality of Life, Metabolic Syndrome, Mortality, Musculoskeletal Diseases, Neoplasms, Neuro-Degenerative Disease
Conditions
Keywords
Longevity, Cardiopulmonary Exercise Testing, Body Composition, Preventive Medicine, Surrogate Endpoint Validation, Mortality Prediction, Functional Decline, Healthspan, Life Expectancy, Biological Aging, Preventive Screening, Longitudinal Cohort, Biomarker Validation, Human Performance, Population Health, Centenarian
Brief summary
The 100-Year Human Aging Study is a prospective, pragmatic, observational trial enrolling participants across fixed clinical sites, mobile clinical sites, and an online participation pathway (current and future) to undergo comprehensive multi-system health screening and longitudinal follow-up until death. Participants are followed to determine whether measurements taken at enrollment and repeated across the lifespan - individually and in combination - predict all-cause mortality, cause-specific mortality, incident serious disease, and functional disability. The study is designed to generate the surrogate endpoint validation data that longevity medicine currently lacks.
Detailed description
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.
Interventions
DIAGNOSTIC_TESTComprehensive Multi-System Clinical Screening
Comprehensive multi-system clinical screening battery including cardiopulmonary exercise testing, body composition assessment by DEXA, echocardiography, electrocardiography, spirometry, neurocognitive testing, sensory assessment, metabolic testing, physical examination, and detailed medical, social, occupational, and environmental history. Participants receive individualized clinical findings and investigational longevity constructs at the conclusion of screening.
Sponsors
Longevity Metrics, Inc.
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
Yes
Inclusion criteria
* Age 18 years or older * Willing and able to provide written informed consent, or enrollment with consent of a legally authorized representative * Willing to participate in longitudinal follow-up
Exclusion criteria
* Age under 18 years
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| All-Cause Mortality | From enrollment until death, assessed periodically, up to 100 years | Vital status ascertained through longitudinal follow-up contact, mortality record linkage, and health data network linkage using probabilistic matching on name, date of birth, and address history. |
| Cause-Specific Mortality | From enrollment until death, assessed periodically, up to 100 years | Cause of death ascertained via death certificate and mortality record linkage. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Cause-Specific Mortality Prediction Accuracy | From enrollment until death, assessed periodically, up to 100 years | Concordance between predicted cause of death profile generated at enrollment and actual cause of death ascertained at follow-up. |
| Incident Serious Adverse Health Events | Periodically from enrollment until death, up to 100 years | New diagnosis of myocardial infarction, stroke, cancer, dementia, heart failure, atrial fibrillation, sepsis, venous thromboembolism, COPD, chronic hypoxia, or major fracture ascertained via periodic follow-up contact and health data network linkage. |
| Incident Chronic Disease | Periodically from enrollment until death, up to 100 years | New diagnosis of type 2 diabetes, hypertension, COPD, chronic kidney disease, metabolic syndrome, or osteoporosis ascertained via self-report and health data network linkage. |
| Functional Independence and Disability Status | Periodically from enrollment until death, up to 100 years | Activities of daily living, instrumental activities of daily living, and self-reported disability status ascertained via periodic health survey using validated open-source instruments. Higher composite scores indicate greater functional independence. Specific instruments will be selected prior to first follow-up contact and documented in the statistical analysis plan. |
| Biological Age Estimate Prediction Accuracy | Periodically from enrollment until death, up to 100 years | Concordance between investigational biological age estimate and actual mortality outcomes at longitudinal follow-up. |
| Health Behavior Change: Composite Self-Report and Repeat Screening Index | Periodically from enrollment until death, up to 100 years | Health behavior change assessed through two complementary measures aggregated into a single index: validated composite self-report survey administered at periodic follow-up, and change in pre-specified clinical measurements at repeat screening. Improvement in objective clinical measurements (cardiorespiratory fitness, body composition, metabolic biomarkers, and related parameters) serves as the primary behavioral activation signal. Self-report domains including health behaviors and preventive care utilization provide supporting context. Both are combined into a single participant-level health activation index. Higher scores indicate greater engagement with health-promoting behaviors and measurable clinical improvement. |
| Multi-System Predictor Modeling: Predictive Performance | Periodically from enrollment until death, up to 100 years | Performance of a unified multi-domain measurement framework in predicting all-cause mortality and incident serious disease. The framework integrates clinical, biological, behavioral, social, occupational, and environmental data into a single composite model. Performance is reported for the full composite model, with pre-specified secondary reporting for individual predictor domains and domain combinations to identify which inputs are independently predictive, which are redundant, and which combinations provide additive or synergistic predictive value. Metrics are specified in the statistical analysis plan. |
Countries
United States
Contacts
CONTACTWilliam E Brandenburg, MD
PRINCIPAL_INVESTIGATORWilliam E Brandenburg, MD
Longevity Metrics, Inc.
Outcome results
None listed