Peer-Reviewed. Population-Validated.

The Science of Myeloid Aging — and How We Measure It

Our scoring engine is calibrated against 128,000+ real NHANES research participants, three landmark clinical trials, and over 5,000 peer-reviewed studies on immune biology. The training dataset for the V23 engine is ~95,000 survey-weighted records.

128,000+ Total NHANES dataset records
~95,000 V23 engine training records
5,000+ Published NLR studies on PubMed
12 Validated wellness archetypes
The Problem with "Normal"

Your Lab Results Are Benchmarked Against Sick People

The "normal" ranges printed on your blood work are derived from the average of the general population — a population where 42% are obese, 37% have pre-diabetes, and chronic disease is the norm. "Normal" means you're not sicker than the average American. It tells you almost nothing about how fast your biology is aging.

"A 50-year-old with an NLR of 2.9 will be told their results are 'within normal limits.' Our model knows that for a 50-year-old, the optimal NLR is 2.3 — and that a 0.6-point elevation signals a measurably less favorable biological aging pattern over the next decade."
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The "Population Average" Trap

Standard reference ranges are built from a cross-section of whoever walked into the lab. We calibrate against the top-performing quartile of the NHANES national dataset.

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Age-Blindness

A flat NLR threshold of 3.0 ignores that expected NLR rises from 1.5 at age 20 to 3.0 at age 70. Our model corrects for your age cohort before scoring your result.

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Missing the Myeloid Signal

Your doctor looks at individual cell counts for signs of acute infection. We look at ratios as a proxy for hematopoietic stem cell drift — the primary cellular mechanism of immune aging.

The Core Biology

The Myeloid-Adaptive Bridge

As we age, the bone marrow's hematopoietic stem cells (HSCs) shift production away from adaptive immune cells (lymphocytes — your precision defenders) toward myeloid cells (neutrophils and monocytes — your blunt-force responders). This "myeloid skew" is the primary cellular signature of immune aging. It is measurable from a standard blood count.

Young Immune Landscape — Age 30

Lymphocytes (Adaptive)35%
Neutrophils (Myeloid)55%
NLR1.6 — Optimal

High adaptive capacity. Efficient, targeted immune response. Immune surveillance active.

Aged Immune Landscape — Age 65

Lymphocytes (Adaptive)22%
Neutrophils (Myeloid)70%
NLR3.2 — Elevated

Chronic myeloid activation. Blunted adaptive response. Immunosuppressive microenvironment.

This shift — quantified by the NLR, SIRI, and PIV ratios — is associated with accelerated biological aging patterns across thousands of peer-reviewed population studies. It is detectable from a standard blood count years before symptoms appear.

The Markers We Measure

Beyond Cholesterol. Into the Myeloid Code.

We score six primary immune signaling ratios, each independently validated as population-level wellness indicators in peer-reviewed research.

NLR
Neutrophil-to-Lymphocyte Ratio

The Primary Wellness Clock

The most widely studied immune ratio. A rising NLR signals myeloid skewing and correlates with accelerated biological aging patterns in large population cohort studies.

5,000+ PubMed studies
SIRI
Systemic Inflammation Response Index

Hematopoietic Drift Proxy

SIRI = (Neutrophils × Monocytes) / Lymphocytes. Models the aging of the bone marrow environment itself. A high SIRI signals the pro-inflammatory immunosuppressive microenvironment.

Studied in 12 major research contexts
PIV
Pan-Immune-Inflammation Value

Comprehensive Immune Load

Integrates Platelets, Neutrophils, Monocytes, and Lymphocytes into a single composite score. Higher sensitivity for detecting chronic low-grade systemic inflammation patterns.

Emerging research standard
CRP
C-Reactive Protein

The Inflammation Indicator

The most clinically accessible marker of systemic inflammation. Even "low-normal" CRP in the 1.0–3.0 mg/L range is associated with less favorable biological aging patterns over 10+ year follow-up in population studies.

Tier 1 inflammaging marker
RDW
Red Cell Distribution Width

Cellular Stress Indicator

High RDW indicates elevated cellular turnover stress and is independently associated with less favorable outcomes in multiple large cohort studies. Often overlooked in standard wellness reviews.

Key Aging Biomarker
HbA1c
Hemoglobin A1c

The Glycation Indicator

Reflects average blood sugar exposure over 90 days. Even sub-diabetic HbA1c above 5.4% drives Advanced Glycation End-products (AGEs) — a key mechanism of tissue cross-linking and structural aging.

Metabolic wellness marker
The Evidence Base

Three Landmark Studies Behind the Score

Fahy et al., 2019

TRIIM Trial: First Measured Epigenetic Age Improvement

The Thymus Regeneration, Immunorestoration, and Insulin Mitigation (TRIIM) trial was the first peer-reviewed study to demonstrate measurable reversal of epigenetic age using a pharmacological and nutritional protocol. Our biological wellness model uses the TRIIM biomarker framework as its foundational calibration reference.

Research result: average 2.5-year improvement in epigenetic age markers in 12 months
Fitzgerald et al., 2021

Diet & Lifestyle Intervention for DNA Methylation Age

This randomized controlled trial demonstrated that a structured diet, sleep, exercise, and supplement protocol produced statistically significant improvement in epigenetic age markers in healthy adults. The 8-week intervention required no drugs — the foundation of our lifestyle education protocol.

Research result: average 3.23-year improvement in epigenetic age markers in 8 weeks
NHANES, 1999–2020

128,000+ Person Population Reference Dataset

The National Health and Nutrition Examination Survey provides the population reference backbone for all ImmuneSpan Wellness Scores. Rather than comparing you to clinical "normal" ranges, we model your biomarkers against this large nationally representative sample — calibrated to optimal-performing age cohorts. The V23 engine trains on ~95,000 survey-weighted records.

128,000+ research participants · 20+ years of cross-sectional data
The V23 Methodology

How the Immune Age Is Calculated

The ImmuneSpan Engine V23.0.0 uses a Cox Proportional Hazards model trained on ~95,000 NHANES population records with survey weights to compute martingale residuals — age-adjusted population deviation scores. We do not hide our methodology.

ImmuneSpan Engine V23.0.0 — Immune Age Formula
# Cox PH model trained on ~95,000 NHANES records (survey-weighted)
# Martingale residual = age-adjusted population deviation score

martingale_residual = observed_event − expected_survival(biomarkers, age)
# Positive = accelerated pattern vs NHANES peers of same age
# Negative = favorable pattern vs NHANES peers of same age

ML_Delta = martingale_residual × 7.0 # scaled: 7 years per SD

Immune_Age = Chronological_Age + (ML_Delta × 0.60)
# 0.60 smoothing factor applied before integer rounding
# Displayed as integer
A positive deviation indicates an accelerated immune aging pattern relative to NHANES peers of the same age; a negative deviation indicates a favorable immune aging pattern. The 0.60 smoothing factor prevents extreme individual outliers from producing implausible Immune Age values.
Immune Age Compliance Note: Immune Age is an educational population-comparison metric, not a clinical measurement of biological age. It does not diagnose disease or predict individual health outcomes. Always consult a qualified healthcare provider. View our FDA compliance framework →

Full Report: Cox PH + K-means Phenotype Engine

The $99 Full Report uses the V23 Cox Proportional Hazards engine trained on ~95,000 survey-weighted NHANES records. Martingale residuals are scaled (7 years/SD) and smoothed (0.60 factor) to compute Immune Age. Phenotype assignment uses K-means clustering (k=12) on a PCA-transformed biomarker feature space. Missing values are handled via Bayesian iterative imputation with population-median fallback.

The Full Analysis

Five Independent Dimensions of Biological Wellness

NLR captures one dimension of immune wellness. The Full Report scores all five — each with its own validated biomarkers, threshold calibration, and educational context.

1

Inflammation Intensity

How active is systemic chronic inflammation right now? The primary driver of accelerated biological aging patterns across all tissues, detectable via immune ratio markers.

NLR CRP SIRI PIV
2

Metabolic Wellness

How efficient is glucose and lipid metabolism? Metabolic patterns drive glycation, oxidative stress, and vascular changes visible in standard blood biomarkers.

HbA1c Glucose Triglycerides HDL
3

Immune Profile

What is the overall composition and balance of your immune cell populations? This dimension captures the myeloid-adaptive balance at a population-comparison level.

Lymphocytes Monocytes Platelets WBC
4

Organ Wellness

How are the liver and kidneys performing? Organ wellness biomarkers reflect systemic burden and the body's filtering and processing capacity.

eGFR ALT AST Albumin
5

Cellular Wellness

What do red blood cell morphology markers reveal about cellular production and turnover? This dimension captures bone marrow health and red cell population stress patterns.

RDW MCV MPV Platelet Mass
Wellness Phenotype Assignment

12 Wellness Archetypes

The Full Report assigns you to one of 12 wellness archetypes via K-means clustering on your PCA-transformed biomarker profile. Each archetype has a distinct wellness pattern and education protocol.

Crimson Fox
Copper Bear
Green Tortoise
Violet Hawk
Amber Tiger
Blue Falcon
Jade Heron
Gold Monkey
Silver Crane
White Stag
Onyx Jaguar
Pearl Swan
Archetype assignment is an educational wellness classification, not a medical diagnosis or disease prediction. Archetypes describe population-level biomarker patterns, not individual health status.

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