Xu Zhiheng, Shen Bo, Tang Yilin, Wu Jianjun, Wang Jian
Department of Neurology and National Research Center for Aging and Medicine & National Center for Neurological Disorders, State Key Laboratory of Medical Neurobiology, Huashan Hospital, Fudan University, Shanghai, 200040 China.
Phenomics. 2022 May 21;2(5):349-361. doi: 10.1007/s43657-022-00051-4. eCollection 2022 Oct.
Despite recent advances in technology, clinical phenotyping of Parkinson's disease (PD) has remained relatively limited as current assessments are mainly based on empirical observation and subjective categorical judgment at the clinic. A lack of comprehensive, objective, and quantifiable clinical phenotyping data has hindered our capacity to diagnose, assess patients' conditions, discover pathogenesis, identify preclinical stages and clinical subtypes, and evaluate new therapies. Therefore, deep clinical phenotyping of PD patients is a necessary step towards understanding PD pathology and improving clinical care. In this review, we present a growing community consensus and perspective on how to clinically phenotype this disease, that is, to phenotype the entire course of disease progression by integrating capacity, performance, and perception approaches with state-of-the-art technology. We also explore the most studied aspects of PD deep clinical phenotypes, namely, bradykinesia, tremor, dyskinesia and motor fluctuation, gait impairment, speech impairment, and non-motor phenotypes.
尽管近年来技术有所进步,但帕金森病(PD)的临床表型分析仍然相对有限,因为目前的评估主要基于临床的经验观察和主观分类判断。缺乏全面、客观和可量化的临床表型数据阻碍了我们进行诊断、评估患者病情、发现发病机制、识别临床前期阶段和临床亚型以及评估新疗法的能力。因此,对PD患者进行深入的临床表型分析是理解PD病理和改善临床护理的必要步骤。在这篇综述中,我们提出了关于如何对这种疾病进行临床表型分析的越来越多的社区共识和观点,即通过将能力、表现和感知方法与最先进的技术相结合,对疾病进展的整个过程进行表型分析。我们还探讨了PD深度临床表型研究最多的方面,即运动迟缓、震颤、异动症和运动波动、步态障碍、言语障碍以及非运动表型。