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 Publication

Fong, S. et al. (2024). “Principal component-based clinical aging clocks identify signatures of healthy aging and targets for clinical intervention.” Nature Aging, 4(8), 1137-1152. https://doi.org/10.1038/s43587-024-00646-8

This study developed a biological aging clock called PCAge using principal component analysis on clinical data to distinguish healthy from unhealthy aging patterns. It identified key signatures – such as metabolic, cardiac, renal, and inflammatory dysfunction – that predict poor aging outcomes and can be influenced by existing drug treatments. A simplified version called LinAge retains the same predictive power with fewer biomarkers, and a custom version (CALinAge) was trained for the CALERIE study on caloric restriction. Results showed that two years of mild caloric restriction significantly reduced biological age, supporting the use of this method for personalized and preventive aging 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 zero z-score to the calculation, though this will reduce accuracy.

Core Demographics

• Age (chronological age in years) - Required
• Sex (male/female) - Required

Blood Biomarkers

• Albumin (g/dL)
• Alkaline Phosphatase (ALP) (U/L)
• Alanine Aminotransferase (ALT) (U/L)
• Aspartate Aminotransferase (AST) (U/L)
• Basophils (K/uL and %)
• Bilirubin (mg/dL)
• Blood Urea Nitrogen (BUN) (mg/dL)
• Body Mass Index (BMI) (kg/m²)
• Calcium (mg/dL)
• Chloride (mEq/L)
• Carbon Dioxide (CO2) (mEq/L)
• Cotinine (ng/mL)
• Creatinine (mg/dL)
• C-Reactive Protein (CRP) (mg/L)
• Diastolic Blood Pressure (DBP) (mmHg)
• Eosinophil Percentage (%)
• Iron (ug/dL)
• Ferritin (ug/L)
• Fibrinogen (g/L)
• Folate (B9) (ng/mL)
• Gamma-Glutamyl Transferase (GGT) (U/L)
• Globulin (g/dL)
• Glucose (mg/dL)
• Hemoglobin A1c (%)
• Hematocrit (%)
• Hemoglobin (g/dL)
• High-Density Lipoprotein (HDL) (mg/dL)
• Heart Rate (bpm)
• Potassium (mEq/L)
• Lactate Dehydrogenase (LDH) (U/L)
• Low-Density Lipoprotein (LDL) (mg/dL)
• Lymphocytes (K/uL and %)
• Mean Corpuscular Hemoglobin (MCH) (pg)
• Mean Corpuscular Hemoglobin Concentration (MCHC) (g/dL)
• Mean Corpuscular Volume (MCV) (fL)
• Mean Platelet Volume (MPV) (fL)
• Monocytes (K/uL and %)
• Sodium (mEq/L)
• Neutrophils (K/uL and %)
• N-terminal Pro-brain Natriuretic Peptide (NT-proBNP) (pg/mL)
• Phosphorus (mg/dL)
• Platelets (K/uL)
• Protein (g/dL)
• Red Blood Cell Count (M/uL)
• Red Blood Cell Distribution Width (RDW) (%)
• Systolic Blood Pressure (SBP) (mmHg)
• Triglycerides (mg/dL)
• Total Iron Binding Capacity (TIBC) (umol/L)
• Transferrin Saturation (%)
• Uric Acid (mg/dL)
• Vitamin B12 (pg/mL)
• White Blood Cell Count (WBC) (K/uL)

Urine Biomarkers

• Albumin (Urine) (mg/dL)
• Creatinine (Urine) (mg/dL)
• Albumin-Creatinine Ratio (Urine) (mg/g) - Calculated automatically if both urine values provided

Health Assessments

• General Health (“good” or better, “fair”, or “poor”)
• Current Health (“better” than, about the “same” as, or “worse” than last year)
• Healthcare Use Index (number of doctor visits in past 12 months, excluding overnight hospitalizations)

Comorbidity Diagnoses

• Anemia (AN_DX)
• Angina (AP_DX)
• Arthritis (AR_DX)
• Asthma (AS_DX)
• Malignancy (CA_DX)
• Chronic Bronchitis (CB_DX)
• Coronary Heart Disease (CHD_DX)
• Cognitive Impairment (CI_DX)
• Diabetes Mellitus (DM_DX)
• Emphysema (EMPH_DX)
• Hypertension (HTN_DX)
• Liver Disease (LD_DX)
• Obesity (OB_DX)
• Osteoporosis (OP_DX)
• Previous Hip Fracture (PHF_DX)
• Previous Myocardial Infarction (PMI_DX)
• Previous Overnight Hospitalization (POH_DX)
• Previous Stroke (PS_DX)
• Previous Spine Fracture (PSF_DX)
• Previous Wrist Fracture (PWF_DX)
• Renal Impairment (RI_DX)
• Thyroid Disease (TD_DX)

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:

• NHANES cohort: Validated across diverse U.S. populations
• CALERIE study: Demonstrated effectiveness in caloric restriction interventions
• Mortality prediction: Strong association with all-cause mortality
• Clinical outcomes: Predicts health trajectories and intervention effectiveness

Current Limitations:

• Requires comprehensive clinical data for optimal accuracy
• May be influenced by acute illness or inflammation
• Limited validation in very young (<20) or very old (>85) populations
• Results should be interpreted in clinical context

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

Technical Implementation

Our LinAge implementation includes:

• Sex-specific calculations: Separate median values, deviations, and weights for males and females
• Unit conversions: Automatic conversion between different measurement units
• Derived calculations: Automatic computation of comorbidity and health indices
• Validation checks: Negative biological ages are rejected
• Flexible input: Accepts any combination of available parameters

The algorithm uses principal component analysis to identify the most predictive biomarkers and applies sex-specific weighting to account for biological differences between males and females.

Usage Guidelines

When to use LinAge:

• Adults aged 20-85 years
• Comprehensive clinical laboratory results available
• Assessment of biological aging and health trajectories
• Research studies of aging interventions
• Preventive medicine and personalized health planning

Interpretation:

• LinAge < Chronological Age: Younger biological age
• LinAge > Chronological Age: Older biological age
• Difference: Years of accelerated or decelerated aging

Clinical Considerations:

• Results should be interpreted by healthcare professionals
• Consider alongside other clinical assessments
• Not a diagnostic tool for specific diseases
• May vary with acute illness, inflammation, or medication use
• Comorbidity index provides additional clinical context
• Self-health assessments enhance subjective health evaluation

Minimum Requirements:

• Age and sex are required for basic calculation
• More comprehensive results require additional biomarkers
• Derived indices enhance accuracy when available