A database of human exposomes and phenomes from the US National Health and Nutrition Examination Survey

Abstract

The National Health and Nutrition Examination Survey (NHANES) is a population survey implemented by the Centers for Disease Control and Prevention (CDC) to monitor the health of the United States whose data is publicly available in hundreds of files. This Data Descriptor describes a single unified and universally accessible data file, merging across 255 separate files and stitching data across 4 surveys, encompassing 41,474 individuals and 1,191 variables. The variables consist of phenotype and environmental exposure information on each individual, specifically (1) demographic information, physical exam results (e.g., height, body mass index), laboratory results (e.g., cholesterol, glucose, and environmental exposures), and (4) questionnaire items. Second, the data descriptor describes a dictionary to enable analysts find variables by category and human-readable description. The datasets are available on DataDryad and a hands-on analytics tutorial is available on GitHub. Through a new big data platform, BD2K Patient Centered Information Commons (http://pic-sure.org), we provide a new way to browse the dataset via a web browser (https://nhanes.hms.harvard.edu) and provide application programming interface for programmatic access.

CLARITE Facilitates the Quality Control and Analysis Process for EWAS of Metabolic-Related Traits

“…The survey consists of dietary, socioeconomic, and general health measurements obtained through both questionnaire responses and clinical laboratory measurements. Curated data for 41,474 individuals and 1,191 variables across four survey periods (1999-2000, 2001-2002, 2003-2004, 2005-2006), are freely available on GitHub (https://github.com/chiragjp/nhanes_scidata) and through the NHANES Dataset Explorer (Patel et al, 2016;Kohane and Avilach, 2018).…”

“…To demonstrate this, we applied CLARITE to a novel EWAS of body mass index (BMI) using data from the National Health and Nutrition Examination Survey (NHANES), obtained from https://github. com/chiragjp/nhanes_scidata (Patel et al, 2016;Kohane and Avilach, 2018), which contains over 1,100 measures on a total of 22,624 adult samples across four surveys from 1999-2006. Here, we present our QC pipeline and EWAS on categorical, binary, and continuous exposures (including questionnaire, nutrient, and pharmaceutical measures, among others) on BMI in Discovery and Replication datasets.…”

Phelan‐McDermid syndrome data network: Integrating patient reported outcomes with clinical notes and curated genetic reports

“…PMS_DN leverages the capabilities of the i2b2/tranSMART knowledge management platform (Patel et al, 2016; Perakslis, van Dam, & Szalma, 2010; Scheufele et al, 2014; Szalma, Koka, Khasanova, & Perakslis, 2010) to integrate heterogeneous datasets—including phenome, exposome, and genome data—and to facilitate browsing and comparative analysis of these datasets. The i2b2/tranSMART platform is layered upon the Informatics for Integrating Biology with Bedside (i2b2) clinical and biomedical data integration platform (Kohane, Churchill, & Murphy, 2012; Murphy et al, 2010).…”

Informatics and Data Analytics to Support Exposome-Based Discovery for Public Health

“…However, individual-level exposome data sets must also be archived and shared for their continued use and integration for data-driven discovery (e.g., 44). Progress in archiving and sharing these types of data is dependent on the continued development, adoption, and dissemination of standardized data dictionaries and ontologies that enable exposure nomenclature (analogous to gene names) and that catalog how exposures are measured (e.g., Figure 2).…”