AUTHOR=Wang QiuShuang , Bian Jing , Sun Yi , Shi YaoZhou , Zhao ZiXuan , Zhao HuaShuo 

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

JOURNAL=Frontiers in Aging Neuroscience

VOLUME=Volume 16 - 2024

YEAR=2024

URL=https://www.frontiersin.org/journals/aging-neuroscience/articles/10.3389/fnagi.2024.1393887

DOI=10.3389/fnagi.2024.1393887

ISSN=1663-4365

ABSTRACT=Objective: This 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.Methods: We collected four-year follow-up data from 389 PD patients through the Parkinson's Progression Marker Initiative (PPMI). Firstly, we employed a univariate LGM to examine the developmental trajectory of motor dysfunction in PD patients. Subsequently, we introduced depression levels as covariates into the model and further treated depression as a parallel growth latent variable to study the longitudinal relationship between motor dysfunction and depression.Results: In the trajectory analysis of motor dysfunction, the fit indices for the quadratic growth LGM model were χ 2 = 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.Our findings indicate 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.