What to Test
4 recipes.
Four data layers. That is the whole chapter. After working through dozens of tests, panels, and devices, the program kept coming back to the same four — and for the same reason every time: each layer adds something the other three can't, and each one survives the only question I ask of any test before ordering it. What decision does this change?
Most consumer longevity programs test too much. The problem isn't missing things — it's that the signal drowns in a panel no one has the discipline to read. Get these four right, once, and the rest is execution.
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Pick exome over microarray or WGS. Best information density per dollar at the consumer tier.
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The compact panel — ApoB, HOMA-IR, 25-OH vitamin D, hs-CRP, and the rest — that actually moves a decision.
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IgE, IgA, and a GI panel at baseline. How to combine them with bloodwork and genetics without crash-dieting.
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Apple Watch, Oura, or Whoop. Pick by fit, not marketing. Track HRV, sleep, and estimated VO₂ max.
If you are coming here before reading the preface, the short version: I ran exome sequencing, whole genome sequencing, and microarray against each other in Trial 2 (2023). Exome won. I ran premium 200-marker panels against focused <50-marker panels; the focused panel produced almost all of the same actionable signal at a fraction of the cost. The recipes above argue both decisions in detail.