Abstract

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.

中文翻译：

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帕金森病的深度表型分析。

摘要

表型是生物体或状况的一组可观察特征。虽然遗传学、影像学和分子生物学的进步提高了我们对帕金森病 (PD) 基础生物学的理解，但帕金森病的临床表型仍然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 表型的理解中留下了空白。传感器可以提供有关 PD 临床表型的客观、连续、真实的数据，增加我们对其病理学的了解，增强对治疗的评估，并最终改善患者护理。在本文中，我们探讨了 PD 深度表型分析的概念，即使用多种临床、生物、遗传、成像和基于传感器的工具对病情进行综合评估。我们讨论深度临床表型分析的基本原理，概述当前的方法，确定深度临床表型分析的优点和局限性，并考虑未来的方向。