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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.

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.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,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).LRRK2-PD is distinguished from iPD by absent or less retinal nerve involvement, both in clinical and preclinical stages.

Objective Low serum uric acid (UA) levels have been associated with a worse cognitive function later in life and also with a higher risk and faster progression of Parkinson's disease (PD). Here we studied whether serum UA levels and the genetic variants related to its variability are associated with the presence of dementia in a cohort of patients with PD. Methods The study included 343 PD patients, which were examined for the presence of dementia according to the MDS Task Force criteria (level 1). The predominant PD phenotype and UPDRS-III and Hoehn-Yahr scales were recorded. Serum UA levels were determined in each participant. Genotyping of SLC2A9 rs734553, ABCG2 rs2231142, SLC17A1 rs1183201, SLC22A11 rs17300741, SLC22A12 rs505802, GCKR rs780094, PDZK1 rs12129861, LRRC16A + SCGN rs742132, and SLC16A9 rs12356193 was carried out by Taqman analysis. For each subject we calculated a cumulative genetic risk score (GRS), defined as the total number of risk alleles (range 2–15) associated to lower serum UA levels. Results 72 out of 343 PD patients (21%) presented dementia. Serum UA levels were not different between PD patients with or without dementia. No significant association was detected between any single SNP and the risk of PD-dementia. When we analyzed the combined effect of the eight SNPs using the cumulative GRS no significant association between the number of risk alleles and the risk of PD was observed. Conclusions Our data suggest that serum UA levels have not a significant impact on the risk of dementia in PD.