Center for Health + Technology, University of Rochester Medical Center, Rochester, NY, USA.
Department of Neurology, University of Rochester Medical Center, Rochester, NY, USA.
J Parkinsons Dis. 2020;10(3):855-873. doi: 10.3233/JPD-202006.
Phenotype is the set of observable traits of an organism or condition. While advances in genetics, imaging, and molecular biology have improved our understanding of the underlying biology of Parkinson's disease (PD), clinical phenotyping of PD still relies primarily on history and physical examination. These subjective, episodic, categorical assessments are valuable for diagnosis and care but have left gaps in our understanding of the PD phenotype. Sensors can provide objective, continuous, real-world data about the PD clinical phenotype, increase our knowledge of its pathology, enhance evaluation of therapies, and ultimately, improve patient care. In this paper, we explore the concept of deep phenotyping-the comprehensive assessment of a condition using multiple clinical, biological, genetic, imaging, and sensor-based tools-for PD. We discuss the rationale for, outline current approaches to, identify benefits and limitations of, and consider future directions for deep clinical phenotyping.
表型是生物体或状况的可观察特征的集合。尽管遗传学、影像学和分子生物学的进步提高了我们对帕金森病 (PD) 潜在生物学的理解，但 PD 的临床表型仍主要依赖于病史和体格检查。这些主观的、偶发的、分类的评估对于诊断和护理很有价值，但在我们对 PD 表型的理解上仍存在空白。传感器可以提供有关 PD 临床表型的客观、连续、真实世界的数据，增加我们对其病理的了解，增强对疗法的评估，并最终改善患者护理。在本文中，我们探讨了使用多种临床、生物学、遗传学、影像学和基于传感器的工具对 PD 进行全面评估的深表型概念。我们讨论了深临床表型的合理性、概述了当前的方法、确定了其优势和局限性，并考虑了未来的方向。
