Sports bioeconomy

Sport consumes biomarker testing faster than it consumes the science behind it, so the useful discipline is asking what each analyte mechanistically reports. Lactate is the cleanest case: it is produced by working muscle continuously and cleared continuously — by oxidation in muscle itself, heart and liver — and the famous “threshold” is not an event but a crossover, the workload where production outruns clearance and blood concentration inflects upward. Everything a lactate step-test reports follows from that balance, which is why it tracks sustainable pace better than any single fatigue molecule could.

Muscle-damage markers are leak arithmetic. Creatine kinase and myoglobin sit inside muscle fibres; they appear in blood when membranes and costameres are mechanically strained by unaccustomed eccentric work, and their decay curves follow clearance rates measured in days. The numbers are honest evidence of disruption — but disruption, not fitness, and the correlation between resting CK and performance is weak. Hormone panels are looser still: the cortisol-to-testosterone ratio is offered as a recovery gauge, yet cortisol responds to psychological load as readily as to physical training, and the ratio’s usefulness as an overtraining detector remains contested in the sports-science literature rather than established. Ferritin carries the field’s favourite confound: it stores iron, but it is also an acute-phase reactant that inflammation raises independently of stores, so an inflamed athlete’s “normal” ferritin can mask a genuine deficit.

Continuous glucose monitoring in non-diabetic athletes is the newest and most oversold instrument. The sensor itself — an interstitial-fluid enzymatic reading, described under home blood analysis kits — is sound; the interpretation is the problem, because the glucose excursions of a healthy person during and after exercise are normal physiology, not dysfunction, and no consensus metabolic argument converts a weekend athlete’s curve into a training instruction. What the data genuinely serve is individual variability: two people eating the same meal can produce different excursions, and that variance is real, even though its long-term performance consequence is unproven.

The pattern across all of these is that single-time panels answer almost nothing, because every marker above is a state variable with its own kinetics, and a snapshot confuses the state with the trend. Serial measurement with the athlete as their own control is the only design the physiology actually supports — which is also where the measurement economics bite, since home sampling exists precisely to make serial affordable. The regulatory frame matches the evidence: these products ride wellness-device exemptions and at-home lab rules, not diagnostic clearance, because their claims are about optimization — a category the evidence bar has not had to test. Where the same signals are held to clinical requirements, that is the territory of wearable biodiagnostics.