Chen Jia-Ru, Sun Yan, Ma Yu-Ju, Tan Lan
Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China.
Front Aging Neurosci. 2024 Nov 25;16:1452766. doi: 10.3389/fnagi.2024.1452766. eCollection 2024.
To investigate the associations between comorbidities and multimorbidity patterns with motor and neuropsychiatric symptoms in patients with Parkinson's disease (PD) in prodromal PD.
Multimorbidity is defined as the coexistence of two or more long-term conditions (LTCs) (also known as multiple comorbidities). A total of 921 participants without PD were included in the Parkinson's Progression Markers Initiative (PPMI) database and were categorized according to the LTC count. Participants were evaluated on motor and psychiatric symptoms. Pearson correlation to examine relationship of comorbidities and target symptoms. The baseline population was analyzed using Multiple linear regression model, while mixed effects model was utilized for longitudinal analysis. Fuzzy C-means clustering analysis was conducted to identify comorbidity patterns, followed by multiple linear regression for further analysis.
At baseline, a higher LTC count was significantly correlated with more severe motor (MDS-UPDRS I, II, ADL, all < 0.05) and neuropsychiatric symptoms (QUIP, < 0.001). Three multimorbidity patterns were identified. Among them, the cardiometabolic multimorbidity pattern (CAR) had the most significant correlation with the aforementioned symptoms. Our longitudinal analysis indicated that an increase in the LTC count was associated with the exacerbation of motor and neuropsychiatric symptoms.
Comorbidities were cross-sectionally and longitudinally associated with the motor and neuropsychiatric symptoms of patients with prodromal PD. Among the three multimorbidity patterns, CAR posed the highest threat to the risk of more severe motor and neuropsychiatric symptoms.
研究前驱期帕金森病（PD）患者的合并症及共病模式与运动和神经精神症状之间的关联。
共病定义为两种或更多种长期病症（LTCs）（也称为多重合并症）共存。帕金森病进展标志物计划（PPMI）数据库纳入了921名无PD的参与者，并根据LTC计数进行分类。对参与者的运动和精神症状进行评估。采用Pearson相关性分析来检验合并症与目标症状之间的关系。使用多元线性回归模型分析基线人群，纵向分析则采用混合效应模型。进行模糊C均值聚类分析以确定共病模式，随后进行多元线性回归以作进一步分析。
在基线时，较高的LTC计数与更严重的运动症状（MDS-UPDRS I、II、ADL，均P<0.05）和神经精神症状（QUIP，P<0.001）显著相关。确定了三种共病模式。其中，心脏代谢共病模式（CAR）与上述症状的相关性最为显著。我们的纵向分析表明，LTC计数的增加与运动和神经精神症状的加重有关。
合并症在前驱期PD患者的运动和神经精神症状方面存在横断面和纵向关联。在三种共病模式中，CAR对更严重的运动和神经精神症状风险构成的威胁最大。
