How to read your bloodwork like a longevity nerd

A standard lab report flags a value when it falls outside the reference range. A reference range is usually the middle 95 percent of a healthy-ish population, not the level at which risk starts. That gap is what the longevity world lives in: the argument that "normal" is not the same as "good." Sometimes the argument is backed by guidelines. Sometimes it is one clinician's opinion repeated until it sounds like a guideline. This page tries to keep the two apart. For the mechanics of a lab report itself, start with how to read a lab report.

The markers, with the guideline numbers

Lipids: ApoB and Lp(a)

Each atherogenic particle (LDL, VLDL, IDL and Lp(a)) carries one ApoB molecule, so ApoB counts particles where LDL cholesterol estimates their cargo. The two usually agree. They diverge in people with high triglycerides, diabetes, obesity or very low LDL, which is where the 2019 European guideline says ApoB may be preferred. Longevity clinicians often argue for ApoB well below the guideline goals. That is a defensible extrapolation from the lipid trials, but it is an opinion about primary prevention, not a guideline target.

Lp(a) is mostly set by your genes and barely moves with diet or exercise. That is exactly why the European consensus says to test it once: a high result changes how aggressively everything else is managed. Note the units. mg/dL and nmol/L are not interchangeable by a simple factor, so compare like with like.

Glucose: HbA1c and insulin

HbA1c is the most standardised glucose marker you can get. It runs falsely low or high with anything that changes red cell lifespan, including anaemia, recent blood loss and some haemoglobin variants, which is why a CBC belongs next to it.

Fasting insulin and HOMA-IR (fasting glucose in mg/dL times fasting insulin, divided by 405) are popular because they can show insulin resistance years before HbA1c moves. They have no guideline threshold, insulin assays differ between labs, and a single value is noisy. Single-digit fasting insulin targets you will see online are opinion. A trend in your own numbers, measured at the same lab, is more useful than any one cut-off.

Inflammation: hs-CRP

hs-CRP has the most outcome data of any marker here outside the lipids. In the JUPITER trial, 17,802 people with normal LDL but hs-CRP of 2 mg/L or more were randomised to rosuvastatin or placebo, and the statin cut major cardiovascular events by 44 percent. hs-CRP spikes with any infection, injury or hard training session, so a value above 10 mg/L usually means "repeat it in two weeks," not "chronic inflammation."

Kidneys: eGFR and cystatin C

Standard eGFR is calculated from creatinine, which comes from muscle. Someone with a lot of muscle, or taking creatine, can show an eGFR that looks like early kidney disease and is not. Someone who has lost muscle, including on a GLP-1, can look better than they are. The 2024 KDIGO guideline recommends adding cystatin C, which does not depend on muscle, whenever creatinine-based eGFR is likely to be inaccurate and the result matters.

Liver, iron and vitamin D

Many lab reports still print ALT upper limits well above these. The American College of Gastroenterology set a lower "healthy" range in 2017 based on liver-related mortality data. Heavy resistance training can raise ALT and AST for days, so a post-workout draw can mislead.

Ferritin is both an iron store and an inflammation marker. A low value means low iron. A high value can mean iron overload, liver disease or simply inflammation, which is why it is read with hs-CRP and transferrin saturation.

Vitamin D is where the longevity world and the guidelines disagree most openly. The Endocrine Society's 2024 guideline advises against routine testing in healthy adults because trials have not shown that targeting a level improves outcomes. Many people test anyway. If you do, the 20 ng/mL figure is the one with evidence behind it; higher "optimal" targets are opinion.

How to use any of this

• Same lab, same conditions. Fasting, morning, no hard training for 48 hours, same lab if you can. Trends need consistent conditions.
• Baseline before you change anything. A drug, a peptide, a diet. Without the before, the after means little. See peptide blood testing and GLP-1 blood work.
• One value is a data point. Repeat anything surprising before acting on it.
• Bring it to a clinician. Particularly ApoB, Lp(a), eGFR and anything flagged. These are decisions that depend on your whole risk picture.

Tracking it over time

A single panel is a snapshot. The value comes from seeing the same markers move alongside what you changed. Peptide AI's bloodwork tracking stores each panel with its date and units and plots it on the same timeline as your dose log and nutrition, so the question "did this move after I started that?" has an answer.