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Imaging Synaptic Density in Aging and Alzheimer Disease with [18F]SynVesT-1

  • Joseph Giorgio
  • , David N. Soleimani-Meigooni
  • , Mustafa Janabi
  • , Suzanne L. Baker
  • , Xi Chen
  • , Tyler N. Toueg
  • , Robby Weimer
  • , Bastian Zinnhardt
  • , Ari Green
  • , Gil D. Rabinovici
  • , William J. Jagust
  • University of California at Berkeley
  • University of Newcastle
  • University of California at San Francisco
  • Lawrence Berkeley National Laboratory
  • Genentech, Inc
  • F. Hoffmann-La Roche AG

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Synaptic density imaging with PET is a relatively new approach to monitoring synaptic injury in neurodegenerative diseases. However, there are remaining technical and clinical questions, including questions on reference region selection and on how specific phenotypic presentations and symptoms of Alzheimer disease (AD) are reflected in alterations in synaptic density. Methods: Using a synaptic vesicle glycoprotein 2A (SV2A) PET ligand radiolabeled with the 18F isotope ([18F]SynVesT-1), we performed sensitivity analyses to determine the optimal reference tissue modeling approach to derive whole-brain ratio images. Using these whole-brain images from a sample of young adults, older adults, and patients with varied phenotypic presentations of AD, we then contrasted regional SV2A density and in vivo AD bio-markers. Results: Reference tissue optimization concluded that a cerebellar gray matter reference region is best for deriving whole-brain ratio images. Using these images, we found a strong inverse association between [18F]SynVesT-1 PET uptake and amyloid b and tau PET deposition. Finally, we found that individuals with a lower temporal gray matter volume but higher temporal [18F]SynVesT-1 PET uptake show preserved performance on the mini-mental state examination. Conclusion: [18F]SynVesT-1 PET shows a close association with in vivo AD pathology, and preserved SV2A density may be a possible marker for resilience to neurodegeneration.

Original languageEnglish
Pages (from-to)620-625
Number of pages6
JournalJournal of Nuclear Medicine
Volume66
Issue number4
DOIs
StatePublished - Apr 1 2025

Keywords

  • Alzheimer disease
  • PET modeling
  • synaptic density

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