@article{10902/26628,
year = {2022},
month = {5},
url = {https://hdl.handle.net/10902/26628},
abstract = {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.},
organization = {This work was supported by Fondo de Investigaci´on Sanitaria-ISCIII (Grant number PI17/00936) to JI.},
publisher = {Elsevier},
publisher = {Parkinsonism & Related Disorders 
Volume 98, May 2022, Pages 21-26},
title = {Sensor-based gait analysis in the premotor stage of LRRK2 G2019S-associated Parkinson's disease},
author = {Sánchez Rodríguez, Antonio and Tirnauca, Cristina and Salas Gómez, Diana and Fernández Gorgojo, Mario and Martínez Rodríguez, Mª Isabel and Sierra Peña, María and González Aramburu, Isabel and Stan, Diana and Gutiérrez-González, Ángela and Meissner Blanco, Johannes Mario and Andrés-Pacheco, Javier and Rivera-Sánchez, María and Sánchez-Peláez, María Victoria and Sánchez-Juan, Pascual and Infante Ceberio, Jon},
}