Frontiers in Neuroscience (May 2023)

In vivo18F-DOPA PET imaging identifies a dopaminergic deficit in a rat model with a G51D α-synuclein mutation

  • Victoria Morley,
  • Karamjit Singh Dolt,
  • Carlos J. Alcaide-Corral,
  • Tashfeen Walton,
  • Christophe Lucatelli,
  • Tomoji Mashimo,
  • Adriana A. S. Tavares,
  • Tilo Kunath

DOI
https://doi.org/10.3389/fnins.2023.1095761
Journal volume & issue
Vol. 17

Abstract

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Parkinson’s disease (PD) is a neurodegenerative condition with several major hallmarks, including loss of substantia nigra neurons, reduction in striatal dopaminergic function, and formation of α-synuclein-rich Lewy bodies. Mutations in SNCA, encoding for α-synuclein, are a known cause of familial PD, and the G51D mutation causes a particularly aggressive form of the condition. CRISPR/Cas9 technology was used to introduce the G51D mutation into the endogenous rat SNCA gene. SNCAG51D/+ and SNCAG51D/G51D rats were born in Mendelian ratios and did not exhibit any severe behavourial defects. L-3,4-dihydroxy-6-18F-fluorophenylalanine (18F-DOPA) positron emission tomography (PET) imaging was used to investigate this novel rat model. Wild-type (WT), SNCAG51D/+ and SNCAG51D/G51D rats were characterized over the course of ageing (5, 11, and 16 months old) using 18F-DOPA PET imaging and kinetic modelling. We measured the influx rate constant (Ki) and effective distribution volume ratio (EDVR) of 18F-DOPA in the striatum relative to the cerebellum in WT, SNCAG51D/+ and SNCAG51D/G51D rats. A significant reduction in EDVR was observed in SNCAG51D/G51D rats at 16 months of age indicative of increased dopamine turnover. Furthermore, we observed a significant asymmetry in EDVR between the left and right striatum in aged SNCAG51D/G51D rats. The increased and asymmetric dopamine turnover observed in the striatum of aged SNCAG51D/G51D rats reflects one aspect of prodromal PD, and suggests the presence of compensatory mechanisms. SNCAG51D rats represent a novel genetic model of PD, and kinetic modelling of 18F-DOPA PET data has identified a highly relevant early disease phenotype.

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