Comparison Of Synaptic Density Assessed By [¹¹C]UCB-J Pet Imaging Between Early- And Late-onset Alzheimer’s Disease

Inès Arino¹, Albertine Dubois¹, Pauline Testard², Pauline Olivieri², Matteo Tonietto³, Gregory Klein³, Philippe Gervais¹, Antoine Pinon¹, Thibaud Lebouvier⁴, David Wallon⁵, Bastian Zinnhardt³, Irene Gerlach⁶, Myriam Ly Le Moal⁷, Alexandra Petiet⁷, Guillaume Dorothée⁸, Marie-Claude Potier⁹, Aurélie Kas¹⁰, Michel Bottlaender¹, Marie Sarazin², Julien Lagarde²

1 Université Paris-Saclay, BioMaps, CEA, Inserm Service Hospitalier Frédéric Joliot, Orsay, France,
2 Neurology of Memory and Language, GHU Paris Psychiatrie & Neurosciences, Paris, France,
3 Roche Pharma Researchand Early Development, Neuroscience and Rare Diseases, Roche Innovation Center, Basel, Switzerland,
4 UnivLille, Inserm U1172, Lille, France ; CHU de Lille, DISTALZ, Lille, France,
5 Normandie Univ, UNIROUEN, Inserm U1245; CHU Rouen, Department of Neurology and CNR-MAJ, Rouen, France,
6 Roche Pharma Research and Early Development, Neuroscience and Rare Diseases, Roche Innovation Center, Basel, France,
7 Institut Roche, 4 cours de l'île Seguin, Boulogne Billancourt, France,
8 Sorbonne Université, Inserm ; Centre deRecherche Saint-Antoine, CRSA, Immune System and Neuroinflammation Laboratory, Hôpital Saint-Antoine,Paris, France,
9 Paris Brain Institute (ICM), Centre National de la Recherche Scientifique (CNRS) UMR 7225, INSERM U1127, Hôpital de la Pitié-Salpêtrière, Sorbonne Université, Paris, France,
10 Service de médecine nucléaire, Hôpital Pitié-Salpêtrière, Paris, France.

Abstract:
Background:
Data supporting clinical and biological differences between early-onset Alzheimer’s Disease (EOAD, age<65) and late-onset AD (LOAD, age≥65) are accumulating based on cognitive profiles, corticalatrophy and hypometabolism. Using [¹¹C]UCB-J PET we aimed to investigate the extent and distribution of synaptic loss in EOAD and LOAD in order to test the hypothesis of distinct regional patterns.
Methods:
Nineteen EOAD patients and 25 LOAD patients (clinical-biological diagnosis based on CSFbiomarkers) at early stage (CDR=0,5-1) and 26 age-matched healthy controls underwent [¹¹C]-UCB-J PETimaging (Table 1). We calculated the standardized uptake value ratio (SUVr, 50-70 minutes post-injection) with the whole cerebellum as the reference region. We defined 14 cortical meta-regions-of-interest. We compared SUVr values between EOAD and LOAD, as well as between each patient subgroup and age-matched controls. We also calculated a temporal/parietal ratio (inferomedial temporal meta-region/lateral parietal cortex). We then explored the effect of the APOE4 genotype on tracer uptake in each patient subgroup, and correlations of regional tracer uptake with MMSE and CDR-SB.
Results:
Each patient subgroup showed lower tracer uptake than age-matched controls in the temporo-parietal regions, with a parietal predominance in EOAD and a temporal predominance in LOAD (Figure 1A). Direct comparison of SUVr values between EOAD and LOAD showed no significant difference. Thetemporal/parietal ratio was higher in EOAD than in LOAD (p=0.003) (Figure 1B). No significant difference intracer binding was found between patients carrying at least one APOE4 allele and those carrying none, bothin EOAD (n=5 and 7) and LOAD (n=20 and 3). In LOAD, MMSE and CDR-SB were correlated with tracerbinding, with no significant results in EOAD (Figure 2).
Conclusion:
This study shows an alteration in synaptic density with a parietal predominance in EOAD and atemporal predominance in LOAD, consistent with previous clinical and neuropathological data showing adifference in the distribution of neurodegeneration and tau pathology depending on the age of symptom onset. These results highlight the potential of synaptic PET to capture phenotypic variations in AD. Furtherstudies are needed to understand its relationship with proteinopathies and clinical symptoms, in order toimprove the design of therapeutic trials.