HAI Book 2025 - Flipbook - Page 480
Bluma, Marina
Tracking plasma biomarker abnormalities with amyloid time accumulation
Marina Bluma1, Konstantinos Chiotis1,6,7, Marco Bucci1,2, Irina Savitcheva5, Anna Matton1, Miia
Kivipelto1,2, Andreas Jeromin3, Giovanni De Santis4, Guglielmo Di Molfetta4, Nicholas J.
Ashton4, Kaj Blennow4, Henrik Zetterberg4, Agneta K Nordberg1,2
1
Karolinska Institutet, Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Center
of Alzheimer Research, Stockholm, SE
2
Karolinska University Hospital, Theme Inflammation and Aging, Stockholm, SE
3
ALZPath, Inc, ALZPath, Inc, Carlsbad, CA, US
4
University of Gothenburg, Department of Psychiatry and Neurochemistry, Molndal, SE
5
Karolinska University Hospital, Medical Radiation Physics and Nuclear Medicin, Stockholm, SE
6
Department of Neurology, Karolinska University Hospital, Stockholm, SE
7
Memory and Aging Center; Department of Neurology;University of California, San Francisco, CA, US
Aim: Plasma pTau fragments and GFAP are potential candidates for early detection and screening of patients for
anti-amyloid therapies. Although it has been shown that these plasma biomarkers change early, the specific
timing at which these changes become significant to identify A´+ individuals has yet to be determined.
Methods: Data were acquired from a memory clinic cohort (N=138) assessed at the Memory Clinic, Karolinska
University Hospital, Stockholm, Sweden. Using a nonlinear model of relationship between amyloid accumulation
time and load (Schindler et al., (2021)), we estimated the duration of amyloid accumulation (AmyloidTime) based on
centiloid values from amyloid PET scans. We then predicted the AmyloidTime linked with the threshold of plasma
biomarkers becoming abnormal to detect individuals with A´+ scan with 90% sensitivity. By subtracting
AmyloidTime from each patient9s age, we estimated their amyloid accumulation onset age ('age-of-A´-onset'),
identifying young accumulators as those with age-of-A´-onset under 50 years, which would correspond to a
minimum of 15 years of A´-accumulation at age 65.
Results: The AmyloidTime corresponding to 100% accuracy of positive visual read for A´-PET scan was 4.8 years
(and 90%-1year before 0 AmyloidTime). The AmyloidTime required for plasma biomarker levels become abnormal
enough to provide 90% sensitivity in identifying amyloid positive PET scans was: 5.4 years for pTau217, 8.7 - for
GFAP, 9.2 - for pTau181, and 10.5 - for pTau231 (Fig.1). Plasma pTau217 and pTau181 levels, but not plasma GFAP or
pTau231, were significantly higher in early amyloid accumulators, even after adjusting for the effect of amyloid
load or AmyloidTime (Fig.2).
Conclusions: Plasma pTau217 levels show a significant change, enabling the identification of A´+ individuals with
90%sensitivity 5.4 years after reaching the A´-accumulation tipping point. Young-age A´-accumulators showed
higher levels of pTau217 and pTau181, suggesting an exacerbation of tau pathology within this patient subgroup.
HAI2025 - 480
