Shakya Shamatree, Prevett Julia, Hu Xiao, Xiao Ran
School of Nursing, Duke University, Durham, NC, United States.
School of Nursing, Emory University, Atlanta, GA, United States.
Front Neurol. 2022 May 23;13:810038. doi: 10.3389/fneur.2022.810038. eCollection 2022.
Parkinson's disease is a progressive neurodegenerative disease with complex, heterogeneous motor and non-motor symptoms. The current evidence shows that there is still a marked heterogeneity in the subtyping of Parkinson's disease using both clinical and data-driven approaches. Another challenge posed in PD subtyping is the reproducibility of previously identified PD subtypes. These issues require additional results to confirm previous findings and help reconcile discrepancies, as well as establish a standardized application of cluster analysis to facilitate comparison and reproducibility of identified PD subtypes. Our study aimed to address this gap by investigating subtypes of Parkinson's disease using comprehensive clinical (motor and non-motor features) data retrieved from 408 Parkinson's disease patients with the complete clinical data in the Parkinson's Progressive Marker Initiative database. A standardized k-means cluster analysis approach was developed by taking into consideration of common practice and recommendations from previous studies. All data analysis codes were made available online to promote data comparison and validation of reproducibility across research groups. We identified two distinct PD subtypes, termed the severe motor-non-motor subtype (SMNS) and the mild motor- non-motor subtype (MMNS). SMNS experienced symptom onset at an older age and manifested more intense motor and non-motor symptoms than MMNS, who experienced symptom onset at a younger age and manifested milder forms of Parkinson's symptoms. The SPECT imaging makers supported clinical findings such that the severe motor-non-motor subtype showed lower binding values than the mild motor- non-motor subtype, indicating more significant neural damage at the nigral pathway. In addition, SMNS and MMNS show distinct motor (ANCOVA test: = 47.35, < ) and cognitive functioning ( = 33.93, < ) progression trends. Such contrast between SMNS and MMNS in both motor and cognitive functioning can be consistently observed up to 3 years following the baseline visit, demonstrating the potential prognostic value of identified PD subtypes.
帕金森病是一种具有复杂、异质性运动和非运动症状的进行性神经退行性疾病。目前的证据表明,使用临床和数据驱动方法对帕金森病进行亚型分类时,仍然存在明显的异质性。帕金森病亚型分类面临的另一个挑战是先前确定的帕金森病亚型的可重复性。这些问题需要更多结果来证实先前的发现、帮助调和差异,以及建立聚类分析的标准化应用,以促进已确定的帕金森病亚型的比较和可重复性。我们的研究旨在通过使用从帕金森病进展标记物倡议数据库中检索到的408例具有完整临床数据的帕金森病患者的综合临床(运动和非运动特征)数据来研究帕金森病的亚型,以填补这一空白。通过考虑先前研究的常见做法和建议,开发了一种标准化的k均值聚类分析方法。所有数据分析代码都在网上公开,以促进不同研究组之间的数据比较和可重复性验证。我们确定了两种不同的帕金森病亚型,分别称为严重运动-非运动亚型(SMNS)和轻度运动-非运动亚型(MMNS)。SMNS发病年龄较大,运动和非运动症状比MMNS更严重,MMNS发病年龄较小,帕金森症状较轻。单光子发射计算机断层扫描(SPECT)成像指标支持临床发现,即严重运动-非运动亚型的结合值低于轻度运动-非运动亚型,表明黑质通路的神经损伤更严重。此外,SMNS和MMNS在运动(协方差分析检验:F = 47.35,P < )和认知功能(F = 33.93,P < )进展趋势上表现出明显差异。在基线访视后的3年内,均可持续观察到SMNS和MMNS在运动和认知功能方面的这种差异,这表明已确定的帕金森病亚型具有潜在的预后价值。