Your Lab Range Is Not a Target
A reference range describes the population that walked into the lab. The population is not healthy.
A lab reference range is usually the middle 95% of whoever walked into that lab. Which means "normal" encodes the diseases of the people being measured.
This isn't a technicality. It's the reason someone can be told their bloodwork is fine for fifteen years while a disease process runs quietly underneath it.
The one to order that nobody orders
Lipoprotein(a). It's roughly 90% genetically determined, elevated in about one in five people, and it independently multiplies cardiovascular risk. It is almost never on a standard panel.
You need it once. Ever. It doesn't meaningfully change across your life and lifestyle won't move it. But knowing it changes how aggressive every other cardiovascular target should be for the rest of your life — if it's high, the ApoB target tightens considerably.
One test, once, and most people never get it.
ApoB, not LDL-C
Atherosclerosis is a particle-driven disease. Every atherogenic lipoprotein — LDL, VLDL, IDL, Lp(a) — carries exactly one ApoB molecule. So ApoB is a direct particle count, while LDL-C measures the cholesterol cargo those particles happen to be carrying.
Two people with identical LDL-C can differ substantially in particle number, and it's the particles that penetrate the endothelium, get retained by proteoglycan binding, oxidise, and trigger the macrophage foam-cell cascade.
The exposure is cumulative — particle count multiplied by years. Which is precisely why the number matters most when you're young and it feels least relevant.
| Marker | Lab "normal" | Optimal | Elite |
|---|---|---|---|
| ApoB | < 130 mg/dL | < 80 | < 60 |
| Lp(a) | rarely tested | < 30 mg/dL | genetic — test once |
| Triglycerides | < 150 mg/dL | < 80 | < 60 |
| hs-CRP | < 3.0 mg/L | < 1.0 | < 0.5 |
One thing to stop optimising: HDL. Mendelian randomisation shows raising it pharmacologically doesn't reduce events. It's a marker, not a lever.
Fasting insulin is the most under-ordered test in medicine
Glucose stays normal for years while insulin climbs to keep it there. The compensation is the disease process, and it is completely invisible on a glucose-only panel. By the time fasting glucose rises, beta-cell function has usually been declining for a decade.
| Marker | Lab "normal" | Optimal | Elite |
|---|---|---|---|
| Fasting glucose | 70–99 mg/dL | 75–85 | 70–80 |
| HbA1c | < 5.7% | 4.9–5.3% | < 5.0% |
| Fasting insulin | 2–25 µIU/mL | < 6 | < 4 |
| HOMA-IR | < 2.5 | < 1.5 | < 1.0 |
Look at that insulin range. The upper bound of "normal" is more than six times the optimal value. If one extra test gets added to a standard panel, make it this one.
Two more worth knowing
ALT under 25 U/L, not under 40 — it's a usable proxy for hepatic fat, and the standard cutoff is far too permissive.
Omega-3 index above 8% of red blood cell fatty acids. It's one of the better-validated nutritional biomarkers, and below 4% associates with the highest cardiovascular risk. Almost no standard panel includes it.
And serum magnesium is near-useless — it's tightly buffered and stays normal during real deficiency. Red blood cell magnesium is the test that tells you something.
The honest caveats
Ranges are population statistics, not diagnoses. An abnormal value belongs in front of a doctor, not a spreadsheet. Trend across several draws at the same lab, fasted, at the same time of day, beats any single number — biological variation is larger than most people assume.
And some of these targets are adult-calibrated. If you're still developing, several of them — particularly anything involving aggressive body composition or hormone-axis intervention — need re-deriving for your age rather than copying.
This is one lever out of a larger system. The full protocol — every mechanism, every dose, every source tier, and an append-only record of everything it has gotten wrong — is at /protocol.
More writing
One Kinase, Two Answers
Endurance training and hypertrophy don't merely compete for time. They send opposing instructions to the same signalling node, and the conflict has a name: AMPK. Here's what it actually does, how big the effect is, and how to schedule around it.
Measurement Without a Decision Is a Hobby
More data makes the signal-to-noise problem worse, not better, unless the analysis accounts for it. A counterweight to my own tracking article, and the rule that decides whether a metric earns its place.