Shanker Swaminathan1, Shannon L Risacher2, Karmen K Yoder2, John D West2, Li Shen3, Sungeun Kim3, Mark Inlow4, Tatiana Foroud5, William J Jagust6, Robert A Koeppe7, Chester A Mathis8, Leslie M Shaw9, John Q Trojanowski9, Holly Soares10, Paul S Aisen11, Ronald C Petersen12, Michael W Weiner13, Andrew J Saykin14. 1. Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA. 2. Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA. 3. Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA. 4. Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Mathematics, Rose-Hulman Institute of Technology, Terre Haute, IN, USA. 5. Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA; Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA. 6. Helen Wills Neuroscience Institute, University of California at Berkeley, Berkeley, CA, USA. 7. Division of Nuclear Medicine, Department of Radiology, University of Michigan, Ann Arbor, MI, USA. 8. Department of Radiology, University of Pittsburgh, Pittsburgh, PA, USA. 9. Department of Pathology and Laboratory Medicine, University of Pennsylvania School of Medicine, Philadelphia, PA, USA. 10. Bristol Myers Squibb Co., Wallingford, CT, USA. 11. Department of Neurosciences, University of California at San Diego, San Diego, CA, USA. 12. Department of Neurology, Mayo Clinic and Foundation, Rochester, MN, USA. 13. Department of Veterans Affairs Medical Center, Center for Imaging of Neurodegenerative Diseases, San Francisco, CA, USA. 14. Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA; Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA. Electronic address: asaykin@iupui.edu.
Abstract
BACKGROUND: Apolipoprotein E (APOE) ε4 allele's role as a modulator of the relationship between soluble plasma amyloid beta (Aβ) and fibrillar brain Aβ measured by Pittsburgh compound B positron emission tomography ([(11)C]PiB PET) has not been assessed. METHODS: Ninety-six Alzheimer's Disease Neuroimaging Initiative participants with [(11)C]PiB scans and plasma Aβ1-40 and Aβ1-42 measurements at the time of PET scanning were included. Regional and voxelwise analyses of [(11)C]PiB data were used to determine the influence of APOE ε4 allele on association of plasma Aβ1-40, Aβ1-42, and Aβ1-40/Aβ1-42 with [(11)C]PiB uptake. RESULTS: In APOE ε4- but not ε4+ participants, positive relationships between plasma Aβ1-40/Aβ1-42 and [(11)C]PiB uptake were observed. Modeling the interaction of APOE and plasma Aβ1-40/Aβ1-42 improved the explained variance in [(11)C]PiB binding compared with using APOE and plasma Aβ1-40/Aβ1-42 as separate terms. CONCLUSIONS: The results suggest that plasma Aβ is a potential Alzheimer's disease biomarker and highlight the importance of genetic variation in interpretation of plasma Aβ levels.
BACKGROUND:Apolipoprotein E (APOE) ε4 allele's role as a modulator of the relationship between soluble plasma amyloid beta (Aβ) and fibrillar brain Aβ measured by Pittsburgh compound B positron emission tomography ([(11)C]PiB PET) has not been assessed. METHODS: Ninety-six Alzheimer's Disease Neuroimaging Initiative participants with [(11)C]PiB scans and plasma Aβ1-40 and Aβ1-42 measurements at the time of PET scanning were included. Regional and voxelwise analyses of [(11)C]PiB data were used to determine the influence of APOE ε4 allele on association of plasma Aβ1-40, Aβ1-42, and Aβ1-40/Aβ1-42 with [(11)C]PiB uptake. RESULTS: In APOE ε4- but not ε4+ participants, positive relationships between plasma Aβ1-40/Aβ1-42 and [(11)C]PiB uptake were observed. Modeling the interaction of APOE and plasma Aβ1-40/Aβ1-42 improved the explained variance in [(11)C]PiB binding compared with using APOE and plasma Aβ1-40/Aβ1-42 as separate terms. CONCLUSIONS: The results suggest that plasma Aβ is a potential Alzheimer's disease biomarker and highlight the importance of genetic variation in interpretation of plasma Aβ levels.
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