Literature DB >> 32444562

Deep Phenotyping of Parkinson's Disease.

E Ray Dorsey1,2, Larsson Omberg3, Emma Waddell1, Jamie L Adams1,2, Roy Adams4, Mohammad Rafayet Ali5, Katherine Amodeo2, Abigail Arky1, Erika F Augustine1,2, Karthik Dinesh6, Mohammed Ehsan Hoque5, Alistair M Glidden1, Stella Jensen-Roberts1, Zachary Kabelac7, Dina Katabi7, Karl Kieburtz1,2, Daniel R Kinel1,2, Max A Little8,9, Karlo J Lizarraga1,2, Taylor Myers1, Sara Riggare10, Spencer Z Rosero11, Suchi Saria4,12, Giovanni Schifitto2, Ruth B Schneider1,2, Gaurav Sharma6,13, Ira Shoulson1,2,14, E Anna Stevenson1, Christopher G Tarolli1,2, Jiebo Luo5, Michael P McDermott1,13.   

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 created 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.

Entities:  

Keywords:  Autonomic nervous system; Parkinson’s disease; gait; natural history; observational study; phenotype; real-world data; sleep; smartphone; social behavior

Year:  2020        PMID: 32444562     DOI: 10.3233/JPD-202006

Source DB:  PubMed          Journal:  J Parkinsons Dis        ISSN: 1877-7171            Impact factor:   5.568


  14 in total

1.  Longitudinal Cohort Study of Verbatim-Reported Postural Instability Symptoms as Outcomes for Online Parkinson's Disease Trials.

Authors:  Ira Shoulson; Lakshmi Arbatti; Abhishek Hosamath; Shirley W Eberly; David Oakes
Journal:  J Parkinsons Dis       Date:  2022       Impact factor: 5.520

2.  Deep phenotyping for precision medicine in Parkinson's disease.

Authors:  Ann-Kathrin Schalkamp; Nabila Rahman; Jimena Monzón-Sandoval; Cynthia Sandor
Journal:  Dis Model Mech       Date:  2022-06-01       Impact factor: 5.732

3.  Digital Phenotyping in Clinical Neurology.

Authors:  Anoopum S Gupta
Journal:  Semin Neurol       Date:  2022-01-11       Impact factor: 3.212

Review 4.  Digital Technology in Movement Disorders: Updates, Applications, and Challenges.

Authors:  Jamie L Adams; Karlo J Lizarraga; Emma M Waddell; Taylor L Myers; Stella Jensen-Roberts; Joseph S Modica; Ruth B Schneider
Journal:  Curr Neurol Neurosci Rep       Date:  2021-03-03       Impact factor: 6.030

Review 5.  Challenges in Clinicogenetic Correlations: One Phenotype - Many Genes.

Authors:  Rahul Gannamani; Sterre van der Veen; Martje van Egmond; Tom J de Koning; Marina A J Tijssen
Journal:  Mov Disord Clin Pract       Date:  2021-03-02

6.  A real-world study of wearable sensors in Parkinson's disease.

Authors:  Jamie L Adams; Karthik Dinesh; Christopher W Snyder; Mulin Xiong; Christopher G Tarolli; Saloni Sharma; E Ray Dorsey; Gaurav Sharma
Journal:  NPJ Parkinsons Dis       Date:  2021-11-29

Review 7.  Review-Emerging Portable Technologies for Gait Analysis in Neurological Disorders.

Authors:  Christina Salchow-Hömmen; Matej Skrobot; Magdalena C E Jochner; Thomas Schauer; Andrea A Kühn; Nikolaus Wenger
Journal:  Front Hum Neurosci       Date:  2022-02-03       Impact factor: 3.169

Review 8.  The Disease Modification Conundrum in Parkinson's Disease: Failures and Hopes.

Authors:  Zoltan Mari; Tiago A Mestre
Journal:  Front Aging Neurosci       Date:  2022-02-28       Impact factor: 5.750

Review 9.  Will Artificial Intelligence Replace the Movement Disorders Specialist for Diagnosing and Managing Parkinson's Disease?

Authors:  Matt Landers; Suchi Saria; Alberto J Espay
Journal:  J Parkinsons Dis       Date:  2021       Impact factor: 5.568

Review 10.  A Long Way to Go: Patient Perspectives on Digital Health for Parkinson's Disease.

Authors:  Sara Riggare; Jon Stamford; Maria Hägglund
Journal:  J Parkinsons Dis       Date:  2021       Impact factor: 5.568

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