Serial DaT-SPECT imaging in asymptomatic carriers of LRRK2 G2019S mutation: 8 years' follow-up.

BACKGROUND: Carriers of the G2019S mutation of LRRK2 provide a great opportunity to investigate the premotor stages of Parkinson's disease (PD). We have studied by serial clinical and dopamine transporter single photon emission computed tomography (DaT-SPECT) evaluations a cohort of asymptomatic carriers of the LRRK2-G2019S mutation in order to evaluate the usefulness of these tools as biomarkers. Here we report the results of the extended follow-up of this cohort at 8 years. METHODS: Seventeen participants, of the 25 available from the 4-year evaluation, completed the 8-year assessment. UPDRS-III, UPSIT test and DaT-SPECT imaging (123 I-ioflupane) were performed. We used repeated-measures linear mixed effects models to examine the changes in DaT binding over time. RESULTS: Three carriers had converted to PD at 4 years. One additional carrier converted at 8 years. PD-converters had lower striatal DaT binding at baseline than non-converters. There was a significant decline of DaT binding over time, with a mean annual rate of 3.5%, with somewhat inter-individual and intra-individual variability and comparable between PD-converters and non-converters. No carrier with DAT binding ratio above an undefined threshold between 0.5 and 0.8 developed PD symptoms. The age-adjusted UPSIT score did not change significantly over time. CONCLUSIONS: The rate of conversion to PD at 8 years in this cohort aged ~58 years at baseline was 16%. The observed decline of DaT binding over time and its association with the phenotype render DaT-SPECT a potentially useful tool for monitoring the premotor stage of the disease, although at the individual level its ability to predict phenoconversion is limited.

Analysis of retinal nerve layers in idiopathic, LRRK2-associated Parkinson's disease and unaffected carriers of G2019S mutation.

INTRODUCTION: In both prodromal and early symptomatic stages of idiopathic PD (iPD) peripapillary retinal nerve fiber layer (pRNFL) and macular ganglion cell layer (mGCL) thinning have been identified. Here we assessed whether these alterations can also be detected in symptomatic and presymptomatic stages of LRRK2-PD. METHODS: 218 eyes belonging to 20 iPD, 19 LRRK2-PD (L2PD), 24 LRRK2 non-manifesting carriers (L2NMC), and 46 controls (HCs). pRNFL, mGCL thickness (squares), and Bruch's membrane opening minimum rim width were evaluated by SD-OCT. In L2NMC, 123I-ioflupane SPECT (DaT-SPECT) with semi-quantitative analysis was carried out. RESULTS: Compared to HCs, iPD patients showed significant thinning of the temporal (BMO-MRW and pRNFL), superior-temporal (BMO-MRW), inferior-temporal (BMO-MRW), superior-nasal (BMO-MRW) and central sectors (BMO-MRW) (p < 0.05), as well as in five mGCL sectors (p < 0.05). No significant differences were found between the L2PD or L2NMC and HCs. BMO-MRW thickness in its temporal-superior, superior-nasal and middle sectors was influenced by disease duration (p < 0.05) and mGCL thickness in sectors TS1, TS2, TS3, NS1 and NS3 was influenced by UPDRSIII and age (p < 0.05). CONCLUSION: LRRK2-PD is distinguished from iPD by absent or less retinal nerve involvement, both in clinical and preclinical stages.

Sensor-based gait analysis in the premotor stage of LRRK2 G2019S-associated Parkinson's disease.

INTRODUCTION: There is a need for biomarkers to monitor the earliest phases of Parkinson's disease (PD), especially in premotor stages. Here, we studied whether there are early gait alterations in carriers of the G2019S mutation of LRRK2 that can be detected by means of an inertial sensor system. METHODS: Twenty-one idiopathic PD patients, 20 LRRK2-G2019S PD, 27 asymptomatic carriers of LRRK2-G2019S mutation (AsG2019S) and 36 controls walked equipped with 16 lightweight inertial sensors in three different experiments: i/normal gait, ii/fast gait and iii/dual-task gait. In the AsG2019S group, DaT-SPECT (123I-ioflupane) with semi-quantitative analysis was carried out. Motor and cognitive performance were evaluated using MDS-UPDRS-III and MoCA scales. We employed neural network techniques to classify individuals based on their walking patterns. RESULTS: PD patients and controls showed differences in speed, stride length and arm swing amplitude, variability and asymmetry in all three tasks (p < 0.01). In the AsG2019S group, the only differences were detected during fast walking, with greater step time on the non-dominant side (p < 0.05), lower step/stride time variability (p < 0.01) and lower step time asymmetry (p < 0.01). DaT uptake showed a significant correlation with step time during fast walking on the non-dominant side (r = -0.52; p < 0.01). The neural network was able to differentiate between AsG2019S and healthy controls with an accuracy rate of 82.5%. CONCLUSION: Our sensor-based analysis did not detect substantial and robust changes in the gait of LRRK2-G2019S asymptomatic mutation carriers. Nonetheless, step or stride time during fast walking, supported by the observed correlation with striatal DaT binding deserves consideration as a potential biomarker in future studies.