4.5 Article

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

期刊

PARKINSONISM & RELATED DISORDERS
卷 98, 期 -, 页码 21-26

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ELSEVIER SCI LTD
DOI: 10.1016/j.parkreldis.2022.03.020

关键词

LRRK2; Gait; Sensors; Asymptomatic carriers; G2019S mutation; Neural network; Parkinson's disease

资金

  1. Fondo de Investigacion Sanitaria-ISCIII [PI17/00936]

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This study examined early gait alterations in carriers of the LRRK2-G2019S mutation using an inertial sensor system. The results showed that significant and robust changes in gait were not detected in asymptomatic mutation carriers, but step or stride time during fast walking may serve as a potential biomarker.
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 (I-123-ioflupane) with semi-quantitative analysis was carried out. Motor and cognitive performance were evaluated using MDSUPDRS-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.

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