Research Support Core C: Computational Biology in Substance Use

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Project Summary - Computational Biology in Substance Use Core C A large number of studies have been performed to identify the impact of drug use on the mechanisms that govern the integrity of the innate and adaptive arms of the immune system, gastrointestinal (GI) function, and neurocognitive disease in the context of HIV persistence. Such studies have led to conflicting results largely because of the complexity of these systems and the low resolution of assays aimed at measuring the different arms, cells, and functions. The lack of assays that can provide an accurate assessment of substance use is also at the source of these conflicting results that have attempted to associate mechanisms downstream of substance use. on HIV disease severity. To address these issues, and in support of the NIDA funded projects at CWRU and nationwide, the CWRU Center for Excellence on the Impact of Substance Use on HIV will rely on the Computational Biology in Substance Use Research Support Core C. This core is a comprehensive shared resource that provides advanced transcriptomics, genomics, functional microbiome, metabolomics, proteomics, bioinformatics, and computational biology resources to Center investigators. This shared resource leverages multiple technologies under the direction of Drs. Mark Chance, Adam Burgener, Saba Valadkhan, and Konstantin Leskov that provide that provide advanced computational and experimental platforms to serve the Substance Use program and the Center’s investigators. Core C will provide a centralized data management and analysis resource to all Center investigators making the navigation of the ‘omics’ landscape seamless and driving appropriate choices of a wide array of ‘omics’ technologies for specific experimental designs. It will be focused on ‘omics’ data acquisition and storage (Aim 1), training and data analysis (Aim 2), and data integration, biomarker validation, and modeling of these datasets (Aim 3). The deliverables of Core C will be an iterative database of all experimental datasets, including protocols and sample identifiers (Aim 1), state of the art analysis of all datasets stemming from all ‘omics’ platforms as well as assays that can provide quantitative assessment of drug levels (Aim 2). Aim 3 will focus on integrating and performing meta-analysis of all datasets across all cohorts and physiological systems to define generalizable and distinct mechanisms that underlie the impact of cocaine, methamphetamine, opioids, and cannabis on HIV latency, neurocognitive dysfunction, constipation, intestinal permeability, damage to the blood brain barrier, and loss of immune homeostasis and function. This integrated approach will identify predictors of HIV disease progression specific to single and poly-users of each drug for each organ system, which could lead to the development of therapeutic approaches tailored to correct the GI, neurological, and immunological pathologies in persons with drug use and HIV.