Scaling Up Scientific Discovery in Sleep Medicine: The National Sleep Research Resource

Abstract

Professional sleep societies have identified a need for strategic research in multiple areas that may benefit from access to and aggregation of large, multidimensional datasets. Technological advances provide opportunities to extract and analyze physiological signals and other biomedical information from datasets of unprecedented size, heterogeneity, and complexity. The National Institutes of Health has implemented a Big Data to Knowledge (BD2K) initiative that aims to develop and disseminate state of the art big data access tools and analytical methods. The National Sleep Research Resource (NSRR) is a new National Heart, Lung, and Blood Institute resource designed to provide big data resources to the sleep research community. The NSRR is a web-based data portal that aggregates, harmonizes, and organizes sleep and clinical data from thousands of individuals studied as part of cohort studies or clinical trials and provides the user a suite of tools to facilitate data exploration and data visualization. Each deidentified study record minimally includes the summary results of an overnight sleep study; annotation files with scored events; the raw physiological signals from the sleep record; and available clinical and physiological data. NSRR is designed to be interoperable with other public data resources such as the Biologic Specimen and Data Repository Information Coordinating Center Demographics (BioLINCC) data and analyzed with methods provided by the Research Resource for Complex Physiological Signals (PhysioNet). This article reviews the key objectives, challenges and operational solutions to addressing big data opportunities for sleep research in the context of the national sleep research agenda. It provides information to facilitate further interactions of the user community with NSRR, a community resource.

Keywords: big data; electrocardiography; polysomnography; precision medicine; signal processing; spectral analysis.

Figure 1

Addressing elements of the Sleep Research Strategic Plan with the National Sleep Research Resource (NSRR). The NSRR is designed to facilitate research in line with national research initiatives in the areas of clinical effectiveness, identification of physiological mechanisms associated with healthy and disturbed sleep, stratification of public health outcomes analyses, creation of new sleep analytics that include information across multiple physiological systems, and to serve as a focus for the training of interdisciplinary researchers. The NSRR is designed to work with other National Institutes of Health research resources such as the Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC) and the Research Resource for Complex Signals (PhysioNet). The NSRR is planning to support the data and analysis needs of individuals, research groups, and collaborations as well as to play a role in the training in the next generation of researchers. The NSRR is actively generating an academic user's group of innovators and early adopters from the research community to help guide NSRR development and to ensure NSRR remains relevant and responsive to the research community's current and future needs.

Figure 2

National Sleep Research Resource (NSRR) overview schematic. The NSRR teams include the Web Access Resource (Port) Team, Data Structure and Standardization of Terminology (Terms) Team, and the Signal Tools Resource (Tool's) team. Data for each study contain study protocol, overnight polysomnograph, manually and automatically scored annotations, covariates, and outcomes.

Figure 3

Query Explorer allows users to query across study datasets. The Query Explorer is an interface that allows users to query across multiple datasets. The query is built from terms common to the selected databases. Defining a query across datasets requires the users to complete three steps: 1. Select datasets for which to query. 2. Select core terms that are defined across the selected datasets to build the query. 3. Specify ranges for each selected term. Selecting the ‘Query’ button initiates a search across the selected datasets and produces a summary. The numbers of subjects by study that meet the selection criteria are shown in the lower right hand corner.