Deep Phenotyping of Parkinson’s Disease
E. Ray Dorsey, Larsson Omberg, Emma Waddell, Jamie Adams, Roy J. Adams, Mohammad Rafayet Ali, Katherine Amodeo, Abigail Arky, Erika F. Augustine, Karthik Dinesh, Mohammed Ehsan Hoque, Alistair M. Glidden, Stella Jensen-Roberts, Zachary Kabelac, Dina Katabi, Karl Kieburtz, Daniel Kinel, Max A. Little, Karlo J. Lizárraga, Taylor Myers, Sara Riggare, Spencer Rosero, Suchi Saria, Giovanni Schifitto, Ruth B. Schneider, Gaurav Sharma, Ira Shoulson, E. Anna Stevenson, Christopher G. Tarolli, Jiebo Luo, Michael McDermott
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.