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

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 biomarkers. 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 β 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.

Keywords: Alzheimer disease; PET modeling; synaptic density.

Graphical abstract

FIGURE 1.

Association between age and SUV for Cereb_GM (A), Cereb_whole (B), and WM_eroded (C). Line shows least-squares best fit.

FIGURE 2.

SRTM2 goodness of fit for different reference regions. Within-subject SSE of SRTM2 predicted time–activity curves and observed time–activity curves using Cereb_GM, Cereb_whole, or WM_eroded reference region.

FIGURE 3.

Optimal window for SUVR derivation. (A) Relationship between SUVR and DVR in each cortical ROI for each subject using 60- to 80-min acquisition. Text shows equation of least-squares fit of SUVR to DVR as well as shared variance (R²) between measures. (B) Within-subject shared variance between SUVR and DVR within cortical ROIs for different windows used for SUVR derivation.

FIGURE 4.

Group differences in DVR (A and C) and SUVR (B and D) in temporal lobes (A and B) and parietal lobes (C and D). Two O did not have PET acquisition within 60- to 80-min window, and SUVR could not be derived. P values for groupwise contrasts within each ROI are shown above plots.

FIGURE 5.

Relationship between [¹⁸F]SynVesT-1 uptake and AD pathology. (A) [¹⁸F]SynVesT-1 and tau PET binding patterns for 3 patients with typical amnestic AD (top), logopenic variant of primary progressive aphasia due to AD (middle), or posterior cortical atrophy due to AD (bottom). Arrows show regions of high tau PET uptake (lower panel) and corresponding regions of low [¹⁸F]SynVesT-1 uptake (upper panel). (B) Association between Aβ centiloid and cortical [¹⁸F]SynVesT-1 uptake. Solid line is least-squares fit between Aβ centiloid and [¹⁸F]SynVesT-1; dashed lines are 95% CIs of this fit. (C) Interaction between average temporal meta-ROI volume and [¹⁸F]SynVesT-1 uptake in predicting MMSE. Individual lines indicate predicted MMSE at different level of temporal meta-ROI volume for 3 different levels of temporal meta-ROI [¹⁸F]SynVesT-1 uptake: minimum [¹⁸F]SynVesT-1 DVR in sample (red), average [¹⁸F]SynVesT-1 DVR in sample (yellow), and maximum [¹⁸F]SynVesT-1 DVR in sample (purple). MMSEs on y-axes are adjusted for age.