Longevity Science
Research & Discovery.
We are building systems that accurately predict and prevent disease and death — before symptoms appear, before damage accumulates, before the window to intervene closes. Preventive health, at scale, available to everyone, at no cost.
Our Research
From Patients
to Populations.
Two independent research pipelines — one generating ground truth from individuals, one mapping the environmental forces shaping entire communities — each making the other more powerful.
Patients
Clinical Research
Prospective observational research through the 100-Year Human Aging Study. We measure biological aging, validate surrogate endpoints against mortality, and build a clinical testing platform that predicts future adverse health events.
Every patient at Longevity Metrics has the opportunity to contribute to research that will benefit future generations.
Populations
Population & Environmental Studies
Understanding what drives longevity at population scales. We study the socioeconomic, demographic, and environmental factors that predict life expectancy and disability-free survival across states, regions, and populations.
Environment is everything. The people, places, and conditions you're embedded in drive health trajectories in ways current medicine doesn't systematically measure. Our epidemiological research quantifies this.
Current Research
What variables predict life expectancy?
Interstate Disparities in U.S. Life Expectancy: Sociodemographic and Environmental Predictors
Brandenburg, W. · Cross-sectional ecological study · 50 States · 2018 & 2021 data
Interstate disparities in U.S. life expectancy have widened to nearly 8 years. This cross-sectional ecological study examines socioeconomic and demographic factors correlated with state-level life expectancy at birth across 50 states for 2018 and 2021. Predictors included obesity prevalence, healthcare expenditure per capita, income per capita, marriage rates, single-parent households, birth rates, educational attainment, disability rates, and demographic composition. Linear regression, multiple regression, dominance analysis, and Bayesian statistics were use to analyze data.
The Long Game
The purpose of the 100-Year Human Aging Study is to build a clinical testing platform that accurately measures aging, rate of aging, predicts longevity, predicts future adverse health events and death, and can be utilized to test therapeutics and interventions intended to slow or reverse aging.
The Problem
When studying human longevity, mortality is the ultimate endpoint. All other markers are surrogate endpoints that must be validated against the endpoint we actually care about — death. Because humans live approximately 78 years, studies lasting 5, 10, or even 20 years will likely be insufficient. A much longer trial is needed.
The Approach
A pragmatic-prospective observational clinical trial. Multi-generational by design. We measure comprehensively now and follow participants over decades. Our goal is to understand, prospectively and quantitatively, what diagnostic and combination of diagnostic results best predict mortality.
Why It Matters
Increasing age is the greatest risk factor for chronic disease, debility, and death. The ability to accurately measure and subsequently target aging therapeutically is of great importance to humanity — and will likely be required for humans to become a multi-planetary species.
Study Design
Pragmatic-Prospective Observational Clinical Trial
Time Horizon
100 years (multi-generational)
Principal Investigator
William Brandenburg, MD
Primary Endpoint
All-cause mortality
Registraction
IRB Oversight
Status
● Actively Enrolling
New Initiative
Most of what determines health happens outside the clinic. The clinic is a sliver — census data, death records, environmental exposures, social determinants, and family history account for far more of the disease picture than any office visit captures. The Colorado Human Observatory connects them all. Every patient screening generates clinically-derived biological data that is geolocated and fused with census, mortality, environmental, social, and family datasets — a living world model that grows more predictive with every data point added. The result is the most comprehensive disease and death prediction engine ever built at the population level. Learn more on clinicaltrials.gov.
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MICRO — The Clinic
Individual biological phenotyping from the Human Performance Lab. Longitudinal biomarker data geographically tagged to each participant's environment. Research-grade phenotypic ground truth acquired at clinical scale.
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MACRO — The World Model
Census, mortality, environmental, social, and family data — unified in a single geolocated model and linked to clinical ground truth from the lab. Causal, biological, and continuously updated.
Why Colorado
⛰️
Altitude Gradient
3,500 to 11,000+ feet of elevation variation creates graduated physiological stress across communities — a natural laboratory no other state offers at this scale.
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Wildfire Exposure
A decade of growing wildfire smoke exposure with well-documented cardiovascular and respiratory effects. One of the most measurable environmental health signals in the country.
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Front Range Contrast
The urban-mountain gradient creates sharp socioeconomic and environmental contrasts within a compact, scientifically tractable geography, anchored by CU Anschutz.
The Family Layer
The Fundamental Unit
of Human Health.
Families share geography, genetics, microbiome, behavior, and decades of environmental exposure. The Colorado Human Observatory builds genealogical profiles for enrolled participants — linking family trees across generations to measured environmental exposures and biological outcomes. Disease risk doesn't originate in individuals. It accumulates in families, across time, and across place.
Ethics & Oversight
Institutional
Review Board.
The Longevity Metrics Ethics Board approves and monitors all research activities for the safety and benefit of research participants. All clinical research requires informed consent and is conducted under IRB oversight.
Brittany Bonser
Chair
Sean Bonser
Board Member
Laura Capps
Board Member
Kevin Capps
Board Member
Karlee Brandenburg
Non-Voting Member
Maggie Mullen, MD, MSCI
Board Member
Paddy Mullen
Board Member
Meredith Jackson
Board Member
Connor Jackson
Board Member