The seven biological axes

Not all genetic signals are the same strength. Some axes are near-deterministic — your genome has something clear and clinically validated to say, and environment doesn't change it much. Others are real but modulated. Others are genuine signals held lightly, where the honest answer is: this is a starting point, not a verdict.

Most genetic products treat every finding as equally authoritative. We don't. The layer structure exists to tell you exactly how much weight to put on each part of your archetype — and why.

If you haven't read Behind the archetypes yet, start there. It explains the polygenic model, the scoring approach, and the cohort thesis that makes this system work.

How the layers work

We score seven axes organised into four layers. The layers reflect two things: how strongly genetics determines the trait, and how much environment can override what your genome prefers.

Layers 1 and 2 define your cohort — the biological peers whose protocols and experience are most likely to transfer to you. Layer 3 adds useful self-knowledge but doesn't change your cohort assignment, for reasons we explain when we get there.

Two scoring methods run through the model. For axes with a small number of high-impact variants and clear biological mechanisms, we score those variants directly — they're the dominant signal. For axes where the trait is distributed across hundreds of genomic regions, we supplement targeted variant analysis with genome-wide pattern matching using data from studies of hundreds of thousands to over a million participants. Where we blend both, we give more weight to whichever signal is stronger for that particular trait.

Layer 1a: Structural constraints

These are the axes where your genome has the most to say. High-penetrance variants, well-understood mechanisms, clinical validation in some cases. Environment shapes expression at the margins — but the underlying architecture is largely fixed.

Metabolic Pacing

Metabolic pacing is the closest thing to deterministic in the model. Your CYP enzyme variants directly control how quickly your body clears compounds. The panel covers Phase I cytochrome P450 enzymes, Phase II conjugation enzymes (UGT1A1, NAT2), and glutathione S-transferases (GSTP1). Scoring is anchored to these high-impact variants, enriched by genome-wide findings from caffeine consumption studies involving 370,000+ participants.

This is also the most clinically validated domain we work with — pharmacogenomics is already standard of care for some medications. The implications are practical and immediate. If you're Slow-Metabolizing, compounds linger: caffeine keeps you wired longer, alcohol clears more slowly, medications may accumulate at doses designed for faster metabolisers. If you're Fast-Metabolizing, effects are shorter and thresholds are higher. Neither is better — they just call for different calibration.

One important note: if your profile has implications for medication metabolism, discuss them with your doctor. This is where the genetics is clearest and where personalisation matters most.

Physical Architecture

Anchored by ACTN3, one of the most replicated performance-associated variants in human genetics. The R577X variant determines whether you produce alpha-actinin-3, a protein found exclusively in fast-twitch muscle fibres. The panel adds COL5A1 (connective tissue stiffness and injury susceptibility), VEGFA (angiogenesis and VO2max training response), and MSTN regulatory variants (muscle mass regulation), enriched by genome-wide findings from grip strength and physical performance studies of 340,000+ participants.

A Power-Built knows that intensity suits them — explosive efforts, strength work, shorter intervals at higher loads. An Endurance-Built knows that long steady efforts are where their body does its best work. Neither is a ceiling. A Power-Built can build aerobic capacity; an Endurance-Built can develop strength. But training with your architecture rather than against it means faster gains, lower injury risk, and less time wondering why a programme that works for someone else isn't working for you.

Layer 1b: Directional tendencies

Real genetic signal, but more polygenic and more modulated by environment than Layer 1a. These axes reliably indicate tendencies — the direction your biology leans — without the near-deterministic clarity of metabolic or structural traits.

Sensory Gain

Captures genuine variation in how your nervous system processes incoming signal. Targeted variant analysis covering taste sensitivity (TAS2R38), pain processing pathways, and sensory gating, supplemented by genome-wide data from studies of over 200,000 participants across 50+ genomic regions associated with sensory processing traits.

The important reframe here is that high sensory gain is a feature, not a disorder. A Highly Sensitive nervous system detects signal that others miss — which is useful in many contexts and overwhelming in others. The practical question isn't how to reduce sensitivity; it's how to manage your noise floor so the signal stays useful. A Sensory-Filtered profile means higher thresholds across the board: you need more stimulus to register the same response, which has its own advantages and blind spots.

Strong signal for specific phenotypes like taste sensitivity and pain threshold. More variable for downstream behaviours, where environment and learned patterns play a larger role.

Fuel Partitioning

Mechanistically distinct from Metabolic Pacing (which covers how you clear compounds) and Physical Architecture (which covers muscle structure). This axis is specifically about energy economics: how your body decides to spend versus bank calories.

BMI heritability is approximately 40–70% in twin studies. The panel is anchored by FTO and MC4R, with supporting variants in PPARG (adipogenesis), ADRB2 (lipolysis rate), and LEPR (leptin receptor sensitivity). Well-replicated across obesity GWAS meta-analyses and UK Biobank body composition studies. Individual variant effects are modest — this trait is highly polygenic — but the aggregate signal is meaningful.

An Energy-Storing profile means your body banks efficiently. Meal timing, feeding windows, and glycaemic load matter more for you than for an Energy-Burning profile, where the body tends to spend readily and the levers are different. Neither is a body composition destiny — but understanding the direction your metabolism leans changes which interventions are worth trying first.

Layer 2: Regulatory dynamics

These axes cover how your system regulates itself over time — daily cycles and stress cycles. The genetic signal is real and confirmed by large-scale studies, but modern environments frequently override what your biology prefers. The gap between your genetic tendency and how you're actually living is often where the most useful insight lives.

Circadian Pacing

One of the strongest genome-wide signals in the model. Core clock genes (CLOCK, PER2, PER3, CRY1) provide interpretable anchors, supplemented by genome-wide data from chronotype studies of nearly 700,000 participants identifying over 350 genomic regions associated with sleep-wake timing. Chronotype heritability is estimated at 40–50%.

Your circadian pacing describes when your biology wants to be awake, alert, and performing — not just when you prefer to sleep. A Morning-Wired profile peaks early and fades in the evening. A Late-Wired profile is slow to activate and hits its stride later in the day. Most people know intuitively which they are. What the genetics adds is the confirmation that this isn't laziness or habit — it's architecture — and that fighting it has real costs in cognitive performance and recovery.

The important caveat: light exposure and social schedule are powerful overrides. Someone Late-Wired who keeps a strict early schedule will function — but they're doing it against their grain, and the cumulative cost shows up in sleep quality and cognitive performance over time.

Stress Recovery

The stress axis uses two-dimensional modelling because stress biology involves distinct systems. Dimension 1 is activation — how readily your stress response engages. Dimension 2 is recovery — how quickly it clears, primarily driven by FKBP5 variants which regulate glucocorticoid receptor sensitivity. Targeted variant analysis is supplemented by genome-wide data from studies of nearly 700,000 participants, strengthening the signal beyond what candidate genes alone can capture.

A Slow-Recovering absorbs stress and releases it slowly — effects linger, recovery needs to be structured. A Fast-Recovering resets quickly.

Important boundary: This axis describes physiological recovery dynamics only. No psychological, historical, or experiential inference is made or permitted from genetic data.

Layer 3: Exploratory modifiers

Drive Profile

Anchored on GWAS-replicated risk tolerance loci (CADM2, LINC00961/LRFN2) with supporting evidence from dopaminergic pathway variants. Supplemented by genome-wide data on self-regulation and attention patterns across hundreds of thousands of participants. Effect sizes are modest at the individual level.

A Novelty-Driven might lean toward novelty, but that's a tendency to explore, not an excuse. A Depth-Driven leans toward mastery and consistency.

Drive Profile is excluded from core clustering because behavioural traits have fundamentally different gene-environment interaction profiles than physiological constraints. Treat this as a starting point for self-experimentation, not a verdict about who you are.

Qualifiers (Experimental)

Qualifiers suggest potential gene-gene interactions that modify primary archetypes. They are explicitly experimental — hypothesis-generating, not validated for predictive use.

Qualifier assignments can now be cross-referenced against genome-wide signal for consistency, increasing confidence when both targeted variants and population-scale data agree. They should not be used to guide protocol decisions without personal validation.

Reliability Summary

Body / Mind / Spirit

The seven axes group into three domains:

These give you a speakable profile: Power-Built body · Highly Sensitive mind · Fast-Recovering spirit. Your archetype code is the searchable shorthand — PHHMDB becomes your key to everything built for people with your biology.

Valid and Invalid Use Cases

Valid: "I am a Slow-Metabolizing/Late-Wired. Here is my protocol for morning alertness."

Invalid: "I am a Novelty-Driven, therefore I cannot hold a steady job."

The archetypes describe biological tendencies, not destinies. They are most useful as context for experimentation, not as explanations for life outcomes.

Layer 1a and 1b profiles describe constraints worth respecting. Layer 3 profiles describe tendencies worth exploring. Know the difference.

Previous: Behind the archetypes — the problem, the model, and the cohort thesis.

Next: The discovery network — how cohorts, expression tracking, and biomarker validation turn genetics into measurable, evolving insight.

For scoring methodology, variant panel details, and calibration approach, see Technical documentation.