APOE Effect on Amyloid-β PET Spatial Distribution, Deposition Rate, and Cut-Points
Article type: Research Article
Authors: Toledo, Jon B.a; c; 1; * | Habes, Mohamadd; 1; * | Sotiras, Aristeidisd; e | Bjerke, Mariaa; b | Fan, Yongd | Weiner, Michael W.f | Shaw, Leslie M.a | Davatzikos, Christosd | Trojanowski, John Q.a | for the Alzheimer’s Disease Neuroimaging Initiative2
Affiliations: [a] Department of Pathology & Laboratory Medicine, Institute on Aging, Center for Neurodegenerative Disease Research, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA | [b] Center for Biological Markers of Dementia (BIODEM), Laboratory of Neurochemistry and Behavior, Institute Born-Bunge, University of Antwerp, Antwerp, Belgium | [c] Department of Neurology, Houston Methodist Hospital, Houston, TX, USA | [d] Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA, USA | [e] Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA | [f] Department of Radiology, Center for Imaging of Neurodegenerative Diseases, San Francisco VA Medical Center/University of California San Francisco, San Francisco, CA, USA
Correspondence: [*] Correspondence to: Jon B. Toledo Atucha, MD, PhD, Department of Pathology & Laboratory Medicine, University of Pennsylvania Medical Center, Philadelphia, PA, USA. E-mail: jbtoledoatucha@houstonmethodist.org and Mohamad Habes, PhD, Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA, USA. E-mail: habesm@uphs.upenn.edu.
Note: [1] These authors contributed equally to this work.
Note: [2] Data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (http://adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found at: http://adni.loni.usc.edu/wp-content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf.
Abstract: There are conflicting results regarding how APOE genotype, the strongest genetic risk factor for Alzheimer’s disease (AD), influences spatial and longitudinal amyloid-β (Aβ) deposition and its impact on the selection of biomarker cut-points. In our study, we sought to determine the impact of APOE genotype on cross-sectional and longitudinal florbetapir positron emission tomography (PET) amyloid measures and its impact in classification of patients and interpretation of clinical cohort results. We included 1,019 and 1,072 Alzheimer’s Disease Neuroimaging Initiative participants with cerebrospinal fluid Aβ1 - 42 and florbetapir PET values, respectively. 623 of these subjects had a second florbetapir PET scans two years after the baseline visit. We evaluated the effect of APOE genotype on Aβ distribution pattern, pathological biomarker cut-points, cross-sectional clinical associations with Aβ load, and longitudinal Aβ deposition rate measured using florbetapir PET scans. 1) APOE ɛ4 genotype influences brain amyloid deposition pattern; 2) APOE ɛ4 genotype does not modify Aβ biomarker cut-points estimated using unsupervised mixture modeling methods if white matter and brainstem references are used (but not when cerebellum is used as a reference); 3) findings of large differences in Aβ biomarker value differences based on APOE genotype are due to increased probability of having AD neuropathology and are most significant in mild cognitive impairment subjects; and 4) APOE genotype and age (but not gender) were associated with increased Aβ deposition rate. APOE ɛ4 carrier status affects rate and location of brain Aβ deposition but does not affect choice of biomarker cut-points if adequate references are selected for florbetapir PET processing.
Keywords: Alzheimer’s disease, amyloid-β, cerebrospinal fluid, diagnosis, mild cognitive impairment, positron emission tomography
DOI: 10.3233/JAD-181282
Journal: Journal of Alzheimer's Disease, vol. 69, no. 3, pp. 783-793, 2019