Lincoln Cannon LLC

PhenoAge Scientific Foundation

PhenoAge Scientific Foundation

PhenoAge is designed to calculate an individual’s biological age based on various biometric inputs. It provides insights into a person’s health status by comparing their biological age to their chronological age. The algorithm is based on peer-reviewed scientific research by Dr. Morgan Levine and colleagues. It has been validated across diverse populations and is widely used in clinical research, population studies, and preventive medicine.

For practical use cases, read more about our PhenoAge Calculator. For API documentation and technical details, refer to the PhenoAge Calculator API. Or read about our entire Biometric Calculator suite.

Key Publications

Publication Summaries

Levine, M. E. et al. (2018). “A new aging measure captures morbidity and mortality risk across diverse subpopulations from NHANES IV: A cohort study.” PhenoAge is a measure based on clinical biomarkers that estimates a person’s biological age in relation to their mortality risk, providing insight into their rate of aging. In this study, researchers assessed its usefulness across diverse populations using data from over 11,000 adults in the NHANES IV survey. PhenoAge was strongly associated with all-cause and cause-specific mortality, even after adjusting for chronological age, and was predictive across subgroups, including healthy individuals and the oldest-old. The findings support its potential as a clinical and research tool for identifying at-risk individuals and evaluating aging-related interventions, though more research in other cohorts is needed.

Levine, M. E. et al. (2019). “Correction: A new aging measure captures morbidity and mortality risk across diverse subpopulations from NHANES IV: A cohort study.” A correction was issued for a study on the PhenoAge measure, which estimates biological aging and predicts health risks across diverse U.S. populations. The original article omitted a crucial step in the equation used to calculate PhenoAge, making it unsolvable as published. The corrected formula now includes the proper transformation of clinical variables, such as albumin, glucose, and white blood cell count, alongside chronological age. This clarification ensures accurate computation of PhenoAge for research and clinical applications in aging and mortality risk assessment.

Adjustment Summary

Cramer, J. G. (2018). “New blood tests can reveal your life expectancy.” Although data for very old individuals is limited, the Levine data consistently falls below the expected linear trend, prompting further analysis. The author extracted points from Levine’s graph and used Mathematica to fit a correction formula that adjusts PhenoAge (P) to estimate DNAm PhenoAge (D) and a corresponding Mortality Score (MS). For example, using these corrections, an 84-year-old with a spreadsheet-calculated PhenoAge of 79.73 gets a DNAm PhenoAge estimate of 76.86 and a Mortality Score reduced from 0.498 to 0.413. These results are approximate and should be interpreted cautiously.

Required Biomarkers

PhenoAge requires the following clinical biomarkers for calculation:

All biomarkers are required for accurate PhenoAge calculation. CRP values are log-transformed during the calculation process.

Algorithm Overview

PhenoAge uses a Cox proportional hazards regression model to predict mortality risk based on clinical biomarkers. The algorithm:

  1. Converts biomarkers to standardized units
  2. Applies weighted coefficients to each biomarker
  3. Calculates a mortality score using the weighted sum
  4. Converts the mortality score to biological age using a mathematical transformation
  5. Applies an adjustment formula to correct for age-related bias

The final result provides both the raw PhenoAge and an adjusted version that accounts for age-related systematic errors.

Validation and Limitations

PhenoAge has been validated in multiple studies:

Current Limitations:

The algorithm performs best in middle-aged to older adults and should be used alongside other clinical assessments.

Technical Implementation

Our PhenoAge implementation includes:

The algorithm returns both PhenoAge1 and PhenoAge2 variants, with the adjusted PhenoAge2 being the recommended final result.

Usage Guidelines

When to use PhenoAge:

Interpretation:

Clinical Considerations: