What We Do

The Data Management and Analysis Core (DMAC) team aims to discover, implement and promulgate best practices for fostering and enabling the interoperability of data among biomedical research projects, environmental science and engineering projects and stakeholders.

We coordinate the development and refinement of an integrated data management plan for the entire Center. The team will work closely with project and core leaders to identify data sharing platforms and to prioritize datasets for sharing across the program using Findable, Accessible, Interoperable and Reusable (FAIR) principles. The DMAC team will ensure statistically robust experimental design, data pipelines, data integration and data management across all research projects and cores as they define the links between PAH exposures and disease. Our data management structure will facilitate the use of integrated data in risk assessments and regulatory decisions.

Services We Offer

  • OSU/PNNL Superfund Research Program Analytics Portal (SRP Analytics Portal): The web-based portal is designed to provide public access to data generated by our OSU/PNNL Superfund Research Program using findable, accessible, interoperable and reusable (FAIR) compliant data standards.

    • This website is comprised of two main entry points: Explore Chemicals provides a summary statistic page that lists all of the chemicals that have been tested for biological activity in the zebrafish model, and Explore Environmental Samples page that characterizes the impact of the chemical mixture on the zebrafish. The individual chemical sample pages display the biological endpoints with dose response curves and summary metrics for benchmark dose (BMD), area under the curve (AUC) and effective concentration at 50% response (EC50) are depicted. The individual environmental sample pages display the location where the samples were collected, the concentration of chemicals measured and link to available zebrafish data for that sample.

  • srpAnalytics GitHub repository: The repository contains the code necessary to process any new data for the Superfund Research Program Analytics Portal.

Our Current Research

  1. Working with the Predicting Toxicity of Complex PAH Mixtures project, the DMAC team provided BMD calculations to support the evaluation of the zebrafish model to predict toxicity of flame retardant chemicals (FRCs) (Truong et al, 2020). The zebrafish assays detected bioactivity for 10 of the 12 previously classified developmental neurotoxic FRCs. A classification model using 13 physicochemical properties and 3 embryonic zebrafish assays achieved a balanced accuracy of 91.7% demonstrating sensitivity for the developmental zebrafish assay to detect FRC structure-bioactivity relationships. 
  2. Also working with the Predicting Toxicity of Complex PAH Mixtures project, the DMAC team has supported the development of gene co-expression networks to reveal similarities and differences between chemical classes using network structure based on modules (Shankar et al., 2021).  AHR2 Activators centered in one module related to chemical stress responses. Analysis of network changes identified neurogenesis pathways associated with FRCs, and regulation of vascular development associated with both chemical classes. We identified highly connected genes responding specifically to each class that are potential biomarkers of exposure.
  3. Working with the PAH Fate and Exposure project, the DMAC team has been analyzing data from wristband samplers worn by human volunteers to identify relationships between chemical measurements from the wristband and measurements of lung function during the period that the wristband is worn.  We use a novel combination of descriptive statistics and supervised statistical learning to evaluate the relationship between polycyclic aromatic hydrocarbon (PAH) concentrations in silicone wristbands and hydroxy-PAH (OH-PAH) concentrations in urine (Dixon et al., 2021). Our results demonstrate that wristbands and urine provide similar PAH exposure assessment information, which is critical for environmental health researchers looking for the flexibility to switch between biological sample and wristband collection.
  4. Work with the PAH Health Outcomes project, the DMAC team is analyzing dose-response transcriptome data to develop concentration-dependent pathway profiles of gene regulation. We are also analyzing gene expression profiles for chemical mixtures to determine if chemical interactions can be quantified when compared to individual chemical profiles.
  5. In a multi-project collaboration, the DMAC team is working with the Predicting Toxicity of Complex PAH Mixtures project, the PAH Fate and Exposure project and the Mechanisms of PAH Susceptability Project to use transcriptome data coupled with metabolism data to decipher the mixed bioactivity profile seen for retene. The DMAC team is creating molecular dynamic simulation models of the AH receptor to determine which retene metabolite structures are likely to bind and cause downstream toxicity. We are also creating network models with transcriptome data to identify regulators that are modulating toxicity in the zebrafish model.