HAI Book 2025 - Flipbook - Page 696
Rodrigues, Matheus
172
Effect of AD risk factors on tau-PET tracer uptake and its
association with amyloid-β pathology
Matheus Rodrigues1, Bruna Bellaver1, Guilherme Povala1, Guilherme Bauer-Negrini1, Firoza
Lussier1, Pamela Lulasewicz Ferreira1, Markley Silva Oliveira Junior1, Andreia Rocha1, Pampa
Saha1, Emma Rupert1, Marina Scop Medeiros1, Joseph Masdeu2, Dana Tudorascu1, David
Soleimani-Meigooni3, Juan Fortea4, Val Lowe5, Hwamee Oh6, Belen Pascual2, Brian Gordon7,
Pedro Rosa-Neto8, Suzanne Baker9, Tharick Pascoal1
1
University of Pittsburgh, Department of Psychiatry, Pittsburgh, PA, US
Houston Methodist Research Institute, Department of Neurology, Houston, TX, US
3
University of California San Francisco, San Francisco, CA, US
4
Hospital de la Santa Creu i Sant Pau, Barcelona, ES
5
Mayo Clinic, Department of Radiology, Rochester, MN, US
6
Brown University, Department of Psychiatry and Human Behavior, Providence, RI, US
7
Washington University in St. Louis, Department of Radiology, Saint Louis, MO, US
8
Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Montreal, QC, CA
9
Lawrence Berkeley National Laboratory, Berkeley, CA, US
2
Objective: We aim to investigate the influence of dementia risk factors and comorbidities on 18F-Flortaucipir (FTP)
and 18F-MK6240 (MK) tau-PET tracers9 uptake. Additionally, we will assess how these factors impact the
association between A´-PET and tau-PET.
Methods: We accessed 378 individuals across the aging and AD spectrum (219 cognitively unimpaired and 159
cognitively impaired) from the HEAD study, with available A´-PET, FTP, MK, and clinical assessments. Linear
regression models corrected for age, A´ PET pathology, clinical diagnosis, and study site tested the association
of factors with tau-PET tracers in the medial temporal lobe (MTL) and neotemporal cortex (NeoT). Lowess method
and voxel-wise analysis accounting for age, clinical diagnosis, and study site tested the influence of factors in the
association of A´-PET Centiloid values with tau-PET tracers. A Centiloid × factor term was added to test the
interactions between independent variables.
Results: We found that sleep disorder and high body mass index (BMI) were negatively associated with both tauPET tracers9 uptake in the MTL, while hypertension was negatively associated only with MK uptake (Fig. 1A, B) after
accounting for covariates. In the NeoT, sleep disorder was negatively associated with both FTP and MK uptake,
whereas visual loss was associated only with reduced MK uptake (Fig. 1C, D). Furthermore, voxel-wise interaction
analysis and Lowess curves supported that sleep disturbances, high BMI, and hypertension attenuated the
association between A´-PET and tau-PET tracer uptake. Visual loss negatively impacted the relationship between
A´ PET and FTP uptake, but not MK uptake, in the MTL (Fig. 2).
Conclusion: In this preliminary analysis, sleep disorders, hypertension, and high BMI were independently
associated with tau-PET tracer uptake. These prevalent factors in the elderly also weakened the association
between A´-PET and tau-PET, underscoring the need for further studies to better understand their role in
modulating this relationship.
HAI2025 - 696
