Lincoln Cannon LLC

LinAge Scientific Foundation

LinAge Scientific Foundation

LinAge 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. Sheng Fong and colleagues. It has been validated by demonstrating consistent ability to predict all-cause mortality and stratify survival trajectories across diverse populations, showcasing predictive power comparable to or exceeding other established aging clocks.

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

Key Publications

Fong S, Pabis K, Latumalea D, Dugersuren N, Unfried M, Tolwinski N, Kennedy B, Gruber J. “Principal component-based clinical aging clocks identify signatures of healthy aging and targets for clinical intervention.” Nat Aging. 2024 Aug; 4(8):1137-1152. doi: 10.1038/s43587-024-00646-8. Epub 2024 Jun 19. PMID: 38898237; PMCID: PMC11333290.

This study introduces a clinical aging clock (PCAge) built using principal component analysis on routine clinical data to distinguish healthy from unhealthy aging trajectories. It identifies signatures (such as metabolic dysregulation, cardiac and renal dysfunction, and inflammation) that not only predict poor aging outcomes but also correspond to pathways that can be modified by existing drugs. From PCAge, the authors derive LinAge, a streamlined clock with similar predictive accuracy but requiring far fewer measurements. They even retrain a version tailored to the CALERIE caloric-restriction study (CALinAge), showing that two years of mild caloric restriction significantly reduces biological age.

Fong S, Denisov KA, Nefedova AA, Kennedy BK, Gruber J. “LinAge2: providing actionable insights and benchmarking with epigenetic clocks. NPJ Aging.” 2025 Apr 23; 11(1):29. doi: 10.1038/s41514-025-00221-4. PMID: 40268972; PMCID: PMC12019333.

LinAge2 is a refined, clinically based “aging clock” developed to better predict mortality and functional aging than both chronological age and existing epigenetic clocks, like PhenoAge DNAm and DunedinPoAm. When tested using NHANES data, it outperformed chronological age and several other clocks in forecasting 10- and 20-year all-cause mortality, with higher predictive accuracy (AUC values). Lower LinAge2 biological age correlated with better healthspan indicators—like cognitive performance, gait speed, and the ability to perform everyday tasks. Crucially, LinAge2’s design—based on principal component analysis of clinical parameters—makes it more interpretable and potentially actionable, letting clinicians identify specific physiological contributors to accelerated aging and tailor interventions accordingly.

The first paper (2024) introduced PCAge, a clinical aging clock built from principal component analysis of standard lab measures, and from it derived LinAge, a simpler but accurate version that could even detect the age – slowing effects of caloric restriction. It showed that key physiological signatures of aging (like metabolic, cardiac, renal, and inflammatory markers) are predictive of poor outcomes but also potentially modifiable. Building on that foundation, the second paper (2025) developed LinAge2, a refined model trained on broader NHANES data to improve mortality prediction over both chronological age and earlier clocks, including LinAge. LinAge2 not only outperformed previous models in predicting 10- and 20-year survival but also offered interpretability, linking biological age shifts to specific physiological systems and actionable interventions.

Algorithm Overview

LinAge uses a principal component-based approach to calculate biological age from clinical biomarkers and health assessments. The algorithm:

  1. Standardizes biomarkers using sex-specific median values and median absolute deviations
  2. Calculates derived indices including comorbidity index (LinAgeCI), healthcare use index (LinAgeHUI), and self-health index (LinAgeSHI)
  3. Applies sex-specific weights to each standardized biomarker
  4. Computes age acceleration using weighted biomarker scores
  5. Calculates biological age by adding age acceleration to chronological age

The algorithm incorporates both objective clinical measurements and subjective health assessments to provide a comprehensive view of biological aging.

Required Biomarkers

While LinAge requires only chronological age and sex to initiate a calculation, for accurate and meaningful results, it is highly recommended to provide as many of the following biomarkers and health assessments as possible. The algorithm is designed to accept any combination of available parameters, with missing values contributing a median or zero z-score to the calculation, though this will reduce accuracy.

Core Demographics

Blood Biomarkers

Urine Biomarkers

Health Assessments

Comorbidity Diagnoses

Derived Indices

LinAge calculates three derived indices that enhance the biological age assessment:

LinAge Comorbidity Index (LinAgeCI)

Quantifies the total burden of 22 specific chronic diseases by summing the number of reported diagnoses and dividing by 22. Can be provided directly or calculated automatically from individual diagnostic parameters.

LinAge Healthcare Use Index (LinAgeHUI)

Records the number of times an individual has seen a healthcare professional in the past 12 months, excluding overnight hospitalizations.

LinAge Self-Health Index (LinAgeSHI)

A weighted score derived from subjective health assessments, incorporating both general health status and perceived health changes over the past year.

Validation and Limitations

LinAge has been validated in multiple studies:

Current Limitations:

The algorithm performs best with comprehensive biomarker data but can provide estimates with minimal parameters.

Technical Implementation

Our LinAge implementation includes:

The algorithm returns both LinAge1 and LinAge2 variants, with the LinAge2 being the recommended final result.

LinAge1 (Original)

API Outputs:

Usage Guidelines

When to use LinAge:

Interpretation:

Clinical Considerations:

Minimum Requirements: