Five biomarkers to check before anyone takes bread off your plate

A nutrition plan that starts from what to remove is working backwards. First you look at what is happening; only then does it make sense to decide what to change. These are the five values that hold up most of those decisions, with what each one measures and why it is on the list.

01 · Glycated hemoglobin (HbA1c)

It measures what proportion of your hemoglobin has been glycated, and since the red blood cell lives about three months, it works as an average of your blood sugar over that period. That is both its virtue and its limit.

The virtue: it cannot be dressed up with two days of good behavior before the test, unlike a fasting glucose. The limit: it is an average, and an average hides the shape of the curve. Two people with the same HbA1c can have very different profiles of peaks and troughs — which is precisely what the study on individual responses shows.

02 · Fasting insulin, and with it HOMA-IR

Glucose tells you how much sugar is circulating. Insulin tells you how much effort it is taking to keep it there. And that is different, earlier information.

With fasting glucose and insulin you calculate HOMA-IR, an index of insulin resistance. Its interest is chronological: the pancreas can compensate for years by raising production, so insulin rises well before glucose leaves the normal range. Looking only at glucose is arriving late to a film that started some time ago.

03 · ApoB — the one almost nobody orders

This is the one that deserves the long paragraph, because it is where a standard check-up falls short systematically.

The LDL cholesterol that appears on any lipid panel measures mass: how much cholesterol the LDL particles carry. ApoB measures something else: how many particles there are. And it does so in an elegantly direct way, because every atherogenic particle — VLDL, IDL, LDL, Lp(a) — carries exactly one ApoB molecule. Counting ApoB is counting particles, one by one.

The distinction matters because particles are not all the same size. Two people with the same LDL cholesterol can have very different particle numbers: one with few large, loaded particles, another with many small ones. The value on the page is the same; the risk is not.

Discordance analyses — designed precisely to compare variables that are highly correlated with each other — found ApoB to be a more accurate marker of cardiovascular risk than LDL cholesterol and than non-HDL cholesterol. The review's conclusion is unusually direct: neither LDL cholesterol nor non-HDL is an adequate clinical substitute for ApoB.

And there is a reason this crosses into nutrition: discordance between the two values is more likely precisely on metabolic ground — raised triglycerides, insulin resistance — which is where the person asking for an eating plan usually is.

04 · High-sensitivity C-reactive protein (hs-CRP)

It is a measure of low-grade inflammation. It does not say where it comes from — it could be a recent infection, an autoimmune condition, visceral fat, a dental process — and that is why it is never interpreted alone.

Its value is in context: background chronic inflammation changes the meaning of almost everything else, including the response to other interventions. It is also, if you go back to the article on mesenchymal cells, one of the variables that determines the environment any regenerative therapy would land in.

05 · Vitamin D and ferritin

They go together here for the same reason: they are two frequent deficiencies, with nonspecific symptoms — tiredness, low performance, mood — that are attributed too easily to other things, and that are simple to correct once found.

Ferritin also has a double reading, and it is worth knowing: low speaks of depleted iron stores; high is not necessarily good news, because it also rises with inflammation. It is another value that only means something alongside the others.

What these five have in common

None of them is interpreted alone. A panel is not a list of independent traffic lights: it is a pattern, and the pattern is what guides the decision.

1. They are measured together, because each one changes the meaning of the others.
2. They are repeated, because an isolated value does not distinguish a trend from an odd day.
3. They are read against your medical history, not against a printed reference range.
4. And they turn into two or three priorities, not forty observations.

That last point is the difference between a panel of tests and a strategy. A panel gives you values; a strategy tells you what to address first and why. It is literally what the Precision Assessment does with what is described here.