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Updated: Jan 7, 2026

Dried Blood Spot Collection of Health Biomarkers to Maximize Participation in Population Studies
Published on: January 28, 2014
Biomarkers
Tobey J Betthauser1, Hailey Bruzzone1, Jacob Morse1
1University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI, USA.
Background:
Recent studies demonstrate tau burden is heterogeneous after A+ onset and is temporally proximal to clinical impairment in sporadic AD. This study uses temporal modeling and neuroimaging data from three cohorts to investigate common factors that may hasten amyloid-related tau accumulation.
Methods:
Participants with available amyloid and tau PET imaging were included from ADNI (n = 880), OASIS (n = 445), and University of Wisconsin (WISC: WRAP and Wisconsin ADRC; n = 739) cohorts. The following steps were completed separately for each cohort. Amyloid and tau were quantified, respectively, using Centiloids (CL) and medial temporal and temporal neocortex standard uptake value ratios (SUVR). A+ and T+ thresholds were defined as the mean plus two standard deviations (SDs) of lower Gaussian mixture model distributions. Sampled iterative linear approximation (SILA) was used to estimate A+ onset age (EAOA) and A+ time (age at observation minus EAOA). To understand moderators of the relationship between A+ time and tau SUVR's, we excluded those deemed confidently A- (<1 SD below the lower GMM group mean) and used LMEs to characterize associations between A+ time and tau SUVR, and investigated whether age at tau baseline, APOE-e4 carriage, sex, or education category explained additional variation in tau, both as main effects and interactions with A+ time.
Results:
Cohort characteristics are shown in Table 1. Results (Figure 1) were mostly consistent between OASIS and WISC cohorts with A+ time having a significant positive association with tau SUVR in both medial temporal and temporal neocortex, and APOE-e4 carriage having a significant interaction with A+ time for the medial temporal SUVR (APOE-e4 carriers had faster tau trajectories). These effects were also significant in ADNI, and additionally interactions of A+ time by baseline tau age and by sex (females had faster tau trajectories) were significant for medial temporal tau, and A+ time by baseline tau age for temporal neocortex (younger age had faster tau trajectories). The education by A+ time interaction did not reach significance in any cohort/region.
Conclusion:
In three longitudinal cohorts, APOE-e4 carriage consistently accelerated tau trajectories relative to A+ onset. Future work will further investigate these relationships and cohort differences that may contribute to mixed findings.
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