Most‑Tracked Biomarkers (Biohacking)
The short list of metrics that most reliably guide biohacking decisions — and what tends to move them.
¶ Most‑Tracked Biomarkers
If you track everything, you learn nothing.
Start with metrics that (1) respond to change, (2) matter to health, and (3) can be measured consistently.
¶ The Short List
| Metric | Why biohackers track it | How to measure | What commonly moves it |
|---|---|---|---|
| Sleep timing + total sleep time | Drives energy, mood, appetite | Diary or wearable | Light timing, caffeine timing, stress, late meals |
| Resting heart rate (trend) | Stress/illness/training load signal | Wearable or manual | Sleep, training load, illness, alcohol |
| Blood pressure | High-signal CV risk marker | Home cuff | Weight trend, sodium/alcohol, sleep, training |
| Weight trend + waist | Body comp proxy | Scale + tape | Intake consistency, activity, sleep |
| HbA1c | Long-term glucose control | Lab | Diet pattern, training, sleep |
| Lipids (ApoB/LDL‑C) | Atherosclerosis risk signal | Lab | Diet pattern, body comp, meds (clinician) |
| hs‑CRP | Inflammation signal (context) | Lab | Illness, adiposity, training load, sleep |
¶ How to Use This Page
- Pick one primary metric that matches your goal: Biohacking Goals
- Add 1–3 supporting metrics (to detect confounding)
- Run a single-variable experiment: N‑of‑1 Experiments
¶ Next Steps
- Set up your baseline: Baseline & Measurement Setup
- Explore biomarker context: Biomarkers of Aging, Inflammaging Biomarkers
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