Association between autonomic dysfunction with motor and non-motor symptoms in patients with Parkinson's disease

Qin, Yi; Meng, De-Tao; Jin, Zhao-Hui; Du, Wen-Jun; Fang, Bo-Yan

doi:10.1007/s00702-024-02745-7

Cited by 1 publication

(1 citation statement)

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“…Currently, research on motor dysfunction in PD primarily focuses on mechanisms, functional assessment, monitoring, and treatment, with relatively few studies investigating the trajectory of motor function in Parkinson’s patients. Currently, numerous studies have investigated the relationship between motor and non-motor functions, including depression ( Zahodne et al, 2012 ), autonomic dysfunction ( Qin et al, 2024 ), cognitive impairment ( Moustafa et al, 2016 ), olfactory dysfunction ( Nabizadeh et al, 2022 ), and sleep disturbances ( Bugalho and Viana-Baptista, 2013 ), all of which have demonstrated close associations with motor function. Among these factors, sleep disturbances are particularly intertwined with motor function, and a bidirectional relationship exists between sleep disturbances and depression, underscoring the importance of further exploring the relationship between depression and motor function ( Fang et al, 2019 ).…”

Section: Introductionmentioning

confidence: 99%

Motor dysfunction in Parkinson’s patients: depression differences in a latent growth model

Wang,

Bian,

Sun

et al. 2024

Front. Aging Neurosci.

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ObjectiveThis study aims to utilize latent growth model (LGM) to explore the developmental trajectory of motor dysfunction in Parkinson’s disease (PD) patients and investigate the relationship between depression and motor dysfunction.MethodsFour-year follow-up data from 389 PD patients were collected through the Parkinson’s Progression Marker Initiative (PPMI). Firstly, a univariate LGM was employed to examine the developmental trajectory of motor dysfunction in PD patients. Subsequently, depression levels were introduced as covariates into the model, and depression was further treated as a parallel growth latent variable to study the longitudinal relationship between motor dysfunction and depression.ResultsIn the trajectory analysis of motor dysfunction, the fit indices for the quadratic growth LGM model were χ2 = 7.419, df = 6, CFI = 0.998, TLI = 0.997, SRMR = 0.019, and RMSEA = 0.025, indicating that the growth trend of motor dysfunction follows a quadratic curve rather than a simple linear pattern. Introducing depression symptoms as time-varying covariates to explore their effect on motor dysfunction revealed significant positive correlations (β = 0.383, p = 0.026; β = 0.675, p < 0.001; β = 0.385, p = 0.019; β = 0.415, p = 0.014; β = 0.614, p = 0.003), suggesting that as depression levels increase, motor dysfunction scores also increase. Treating depression as a parallel developmental process in the LGM, the regression coefficients for depression intercept on motor dysfunction intercept, depression slope on motor dysfunction slope, and depression quadratic factor on motor dysfunction quadratic factor were 0.448 (p = 0.046), 1.316 (p = 0.003), and 1.496 (p = 0.038), respectively. These significant regression coefficients indicate a complex relationship between depression and motor dysfunction, involving not only initial level associations but also growth trends over time and possible quadratic effects.ConclusionThis study indicates a quadratic growth trajectory for motor dysfunction in PD, suggesting a continuous increase in severity with a gradual deceleration in growth rate. The relationship between depression and motor dysfunction is complex, involving initial associations, evolving trends over time, and potential quadratic effects. Exacerbation of depressive symptoms may coincide with motor function deterioration.

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