Parkinson’s disease (PD) is a complex neurodegenerative disorder with diverse clinical manifestations. To better understand this disease, research has been done to categorize, or subtype, patients, using an array of criteria derived from clinical assessments and biospecimen analyses. In this study, using data from the BioFIND cohort, we aimed at identifying subtypes of moderate-to-advanced PD via comprehensively considering motor and non-motor manifestations. A total of 103 patients were included for analysis. Through the use of a patient-wise similarity matrix fusion technique and hierarchical agglomerative clustering analysis, three unique subtypes emerged from the clustering results. Subtype I, comprised of 60 patients (~58.3%), was characterized by mild symptoms, both motor and non-motor. Subtype II, comprised of 20 (~19.4%) patients, was characterized by an intermediate severity, with a high tremor score and mild non-motor symptoms. Subtype III, comprised of 23 (~22.3%) patients, was characterized by more severe motor and non-motor symptoms. These subtypes show statistically significant differences when looking at motor (on and off medication) clinical features and non-motor clinical features, while there was no clear difference in demographics, biomarker levels, and genetic risk scores.

帕金森病 (PD) 是一种复杂的神经退行性疾病，具有多种临床表现。为了更好地了解这种疾病，已经进行了研究以使用来自临床评估和生物样本分析的一系列标准对患者进行分类或亚型。在这项研究中，我们使用来自 BioFIND 队列的数据，旨在通过综合考虑运动和非运动表现来确定中度至晚期 PD 的亚型。共纳入 103 名患者进行分析。通过使用基于患者的相似性矩阵融合技术和分层凝聚聚类分析，从聚类结果中出现了三种独特的亚型。亚型 I 由 60 名患者（~58.3%）组成，其特征是运动和非运动症状轻微。亚型 II，由 20 (~19.4%) 名患者组成，其特点是中等严重程度，具有高震颤评分和轻微的非运动症状。亚型 III 由 23 名（~22.3%）患者组成，其特征是更严重的运动和非运动症状。这些亚型在观察运动时显示出统计学上的显着差异（在和关药物）的临床特征和非机动车的临床特征，虽然在人口，生物标记物的水平，和遗传风险评分没有明显差异。