- Design
- Longitudinal cohort with untreated and amyloid-negative comparison groups
- Population
- 197 patients with early symptomatic Alzheimer's disease on lecanemab
- Primary outcome
- Change in 130 plasma protein biomarkers
- Effect
- 34 markers changed (FDR <0.05) in four trajectories; p-tau217 normalised, NfL unchanged
At Washington University in St Louis, 197 patients with early symptomatic Alzheimer's disease receiving lecanemab in routine care gave blood about every six months for up to two years. Their panel of 130 plasma proteins was compared with untreated patients with cognitive impairment and amyloid-negative controls.
Thirty-four biomarkers changed significantly, in four patterns. Some normalised towards amyloid-negative levels, including p-tau217, MAPT and GFAP. Amyloid peptides overshot past normal. Some moved further away from normal, including TREM2, NPTXR and neurogranin, which may reflect an immune response to plaque removal or effects on synapses. Neurofilament light and APOE did not change.
The practical implication is that no single blood test will tell you whether lecanemab is 'working'. p-tau217 falling is consistent with amyloid clearance, but neurofilament light staying flat and inflammatory markers rising mean the biology is more complicated than plaque removal.
- Expect plasma p-tau217 and GFAP to fall towards normal on lecanemab.
- Neurofilament light did not change, so it is not a marker of treatment response here.
- Some inflammatory and synaptic markers moved away from normal on treatment; their meaning is unknown.
- Do not use any single plasma biomarker to decide whether to continue lecanemab yet.
Why it matters
Clinics want a blood test to monitor anti-amyloid therapy, and this shows which markers respond and which do not.
Don't overread it
This is an observational cohort from one centre, almost entirely White, without matched clinical outcomes for each marker.
The statistics, in plain English
A false discovery rate below 0.05 corrects for testing 130 markers at once, so the 34 flagged changes are unlikely to be chance findings from multiple testing.
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