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The Inaugural Issue
Author(s) -
E. Ray Dorsey
Publication year - 2017
Publication title -
digital biomarkers
Language(s) - English
Resource type - Journals
ISSN - 2504-110X
DOI - 10.1159/000479671
Subject(s) - library science , computer science
The inaugural issue of Digital Biomarkers discusses how mobile technologies are reshaping measurement of neurodegenerative conditions, introduces the Network of Digital Evidence in Health (NODE), and highlights perspectives from multiple disciplines and industries that the journal seeks to represent. The first issue has multiple pieces highlighting how digital biomarkers are increasingly providing insights into neurodegenerative disorders. Such applications are important for at least three reasons. First, neurodegenerative disorders are increasingly common and are now the leading source of disability globally. Second, unlike many other conditions, central nervous system disorders lack good functional (e.g., echocardiography), plasma (e.g., CD4 counts), and in many cases (e.g., Parkinson disease) imaging biomarkers. Third, the brain and spinal cord are difficult to access and while increasing in value, cerebrospinal fluid markers currently have limited utility in tracking disease progression. Consequently, subjective, insensitive, episodic rating scales dominate evaluations of many neurodegenerative disorders, including Alzheimer disease, amyotrophic lateral sclerosis, and Huntington disease. To help address these limitations, Giggins and colleagues conducted a review of physical activity monitors for individuals with neurological disorders. Heldman and colleagues investigated a FDA-cleared device for evaluation of Parkinson disease in the home. In addition, Adams and colleagues evaluated wearable accelerometers for individuals with Parkinson disease, Huntington disease, and prodromal Huntington disease in the clinic and at home. While Adams and colleagues did not find any differences in those with prodromal Huntington disease and controls in a small pilot study, their evaluation of prodromal states with digital biomarkers is likely to be replicated in a wide range of clinical disorders, including Alzheimer disease, diabetes, and hypertension. This work lays the foundation for possible identification of individuals with these prodromal states and evaluation of interventions aimed at preventing the onset of disease. Published online: August 16, 2017

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