Identifying Datasets for Cross-Study Analysis in dbGaP using PhenX.

Identifying relevant studies and harmonizing datasets are major hurdles for data reuse. Common Data Elements (CDEs) can help identify comparable study datasets and reduce the burden of retrospective data harmonization, but they have not been required, historically. The collaborative team at PhenX and dbGaP developed an approach to use PhenX variables as a set of CDEs to link phenotypic data and identify comparable studies in dbGaP. Variables were identified as either comparable or related, based on the data collection mode used to harmonize data across mapped datasets. We further added a CDE data field in the dbGaP data submission packet to indicate use of PhenX and annotate linkages in the future. Some 13,653 dbGaP variables from 521 studies were linked through PhenX variable mapping. These variable linkages have been made accessible for browsing and searching in the repository through dbGaP CDE-faceted search filter and the PhenX variable search tool. New features in dbGaP and PhenX enable investigators to identify variable linkages among dbGaP studies and reveal opportunities for cross-study analysis.

Using the PhenX Toolkit to Select Standard Measurement Protocols for Your Research Study.

The goals of PhenX (consensus measures for Phenotypes and eXposures) are to promote the use of standard measurement protocols and to help investigators identify opportunities for collaborative research and cross-study analysis, thus increasing the impact of individual studies. The PhenX Toolkit (https://www.phenxtoolkit.org/) offers high-quality, well-established measurement protocols to assess phenotypes and exposures in studies with human participants. The Toolkit contains protocols representing 29 research domains and 6 specialty collections of protocols that add depth to the Toolkit in specific research areas (e.g., COVID-19, Social Determinants of Health [SDoH], Blood Sciences Research [BSR], Mental Health Research [MHR], Tobacco Regulatory Research [TRR], and Substance Abuse and Addiction [SAA]). Protocols are recommended for inclusion in the PhenX Toolkit by Working Groups of domain experts using a consensus process that includes input from the scientific community. For each PhenX protocol, the Toolkit provides a detailed description, the rationale for inclusion, and supporting documentation. Users can browse protocols in the Toolkit, search the Toolkit using keywords, or use Browse Protocols Tree to identify protocols of interest. The PhenX Toolkit provides data dictionaries compatible with the database of Genotypes and Phenotypes (dbGaP), Research Electronic Data Capture (REDCap) data submission compatibility, and data collection worksheets to help investigators incorporate PhenX protocols into their study design. The PhenX Toolkit provides resources to help users identify published studies that used PhenX protocols. © 2021 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol: Using the PhenX Toolkit to support or extend study design.

Dynamic changes in lung responses after single and repeated exposures to cigarette smoke in mice.

Cigarette smoke is well recognized to cause injury to the airways and the alveolar walls over time. This injury usually requires many years of exposure, suggesting that the lungs may rapidly develop responses that initially protect it from this repetitive injury. Our studies tested the hypotheses that smoke induces an inflammatory response and changes in mRNA profiles that are dependent on sex and the health status of the lung, and that the response of the lungs to smoke differs after 1 day compared to 5 days of exposure. Male and female wildtype (WT) and Scnn1b-transgenic (ßENaC) mice, which have chronic bronchitis and emphysematous changes due to dehydrated mucus, were exposed to cigarette smoke or sham air conditions for 1 or 5 days. The inflammatory response and gene expression profiles were analyzed in lung tissue. Overall, the inflammatory response to cigarette smoke was mild, and changes in mediators were more numerous after 1 than 5 days. ßENaC mice had more airspace leukocytes than WT mice, and smoke exposure resulted in additional significant alterations. Many genes and gene sets responded similarly at 1 and 5 days: genes involved in oxidative stress responses were upregulated while immune response genes were downregulated. However, certain genes and biological processes were regulated differently after 1 compared to 5 days. Extracellular matrix biology genes and gene sets were upregulated after 1 day but downregulated by 5 days of smoke compared to sham exposure. There was no difference in the transcriptional response to smoke between WT and ßENaC mice or between male and female mice at either 1 or 5 days. Taken together, these studies suggest that the lungs rapidly alter gene expression after only one exposure to cigarette smoke, with few additional changes after four additional days of repeated exposure. These changes may contribute to preventing lung damage.