The Pandemic Response Commons.

Objectives: A data commons is a software platform for managing, curating, analyzing, and sharing data with a community. The Pandemic Response Commons (PRC) is a data commons designed to provide a data platform for researchers studying an epidemic or pandemic. Methods: The PRC was developed using the open source Gen3 data platform and is based upon consortium, data, and platform agreements developed by the not-for-profit Open Commons Consortium. A formal consortium of Chicagoland area organizations was formed to develop and operate the PRC. Results: The consortium developed a general PRC and an instance of it for the Chicagoland region called the Chicagoland COVID-19 Commons. A Gen3 data platform was set up and operated with policies, procedures, and controls for a NIST SP 800-53 revision 4 Moderate system. A consensus data model for the commons was developed, and a variety of datasets were curated, harmonized and ingested, including statistical summary data about COVID cases, patient level clinical data, and SARS-CoV-2 viral variant data. Discussion and conclusions: Given the various legal and data agreements required to operate a data commons, a PRC is designed to be in place and operating at a low level prior to the occurrence of an epidemic, with the activities increasing as required during an epidemic. A regional instance of a PRC can also be part of a broader data ecosystem or data mesh consisting of multiple regional commons supporting pandemic response through sharing regional data.

Economical Utilization of Health Information with Learning Healthcare System Data Commons.

Finding, accessing, sharing, and analyzing patient data from a clinical setting for collaborative research has continually proven to be a challenge in healthcare organizations. The human and technological architecture required to perform these services exist at the largest academic institutions but are usually under-funded. At smaller, less academically focused healthcare organizations across the United States, where the majority of care is delivered, they are generally absent. Here we propose a solution called the Learning Healthcare System Data Commons where cost is usage-based and the most basic elements are designed to be extensible, allowing it to evolve with the changing landscape of healthcare. Herein we also discuss our reference implementation of this platform tailored specifically for operational sustainability and governance using the data generated in a hospital setting for research, quality, and educational purposes.

Phylogenetic footprinting and genome scanning identify vertebrate BMP response elements and new target genes.

The complex gene regulatory networks governed by growth factor signaling are still poorly understood. In order to accelerate the rate of progress in uncovering these networks, we explored the usefulness of interspecies sequence comparison (phylogenetic footprinting) to identify conserved growth factor response elements. The promoter regions of two direct target genes of Bone Morphogenetic Protein (BMP) signaling in Xenopus, Xvent2 and XId3, were compared with the corresponding human and/or mouse counterparts to identify conserved sequences. A comparison between the Xenopus and human Vent2 promoter sequences revealed a highly conserved 21 bp sequence that overlaps the previously reported Xvent2 BMP response element (BRE). Reporter gene assays using Xenopus animal pole ectodermal explants (animal caps) revealed that this conserved 21 bp BRE is both necessary and sufficient for BMP responsiveness. We combine the same phylogenetic footprinting approach with luciferase assays to identify a highly conserved 49 bp BMP responsive region in the Xenopus Id3 promoter. GFP reporters containing multimers of either the Xvent2 or XId3 BREs appear to recapitulate endogenous BMP signaling activity in transgenic Xenopus embryos. Comparison of the Xvent2 and the XId3 BRE revealed core sequence features that are both necessary and sufficient for BMP responsiveness: a Smad binding element (SBE) and a GC-rich element resembling an OAZ binding site. Based on these findings, we have implemented genome scanning to identify over 100 additional putative target genes containing 2 or more BRE-like sequences which are conserved between human and mouse. RT-PCR and in situ analyses revealed that this in silico approach can effectively be used to identify potential BMP target genes.