Identification and prognostication of pre-symptomatic Alzheimer´s disease using blood-based biomarkers
Description: Alzheimer´s disease (AD) is a major health challenge, with a lifetime risk of 20% in women and 10% in men. Early intervention is crucial for optimal prevention. I aim to develop methods to identify individuals who may benefit from very early intervention.I will prospectively examine 7000 cognitively unimpaired individuals over 3 years, using plasma sampling, digital cognitive tests, and β-amyloid (Aβ) PET imaging. Specifically, I will 1) validate an algorithm to predict early Aβ accumulation using baseline plasma biomarkers; 2) characterize progression from negative to positive plasma p-tau217; 3) develop prediction models for cognitive decline in pre-symptomatic AD; and 4) examine longitudinal correlations between plasma biomarkers and cognition.I hypothesize that: 1) baseline plasma biomarkers can distinguish stable Aβ-negatives from those likely to accumulate Aβ; 2) longitudinal increases in plasma p-tau217 predict Aβ PET positivity; 3) baseline biomarkers and other features can predict cognitive decline in early AD; and 4) longitudinal plasma biomarker changes associate with subtle cognitive decline.My approach combines a prospective design, validation of plasma-based algorithms, and utilization of longitudinal biomarkers and digital cognitive tests. This research will advance the identification and prognostication of pre-symptomatic AD using scalable tools, informing both clinical trials and future early AD screening in clinical practice.
Funder: Vetenskapsrådet
Amount: SEK 5,400,000
Funding type: research
Funder scheme: Project grant
Start date: 2026-01-01
End date: 2029-12-31
Investigator: Niklas Mattsson-Carlgren
Institution: Lund University
Funded outputs count: 0
Funder award ID: 2025-02840
OpenAlex ID: G8971225931