Research Support Core C: Computational Biology in Substance Use

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.

Grant Number: 5P30DA054557-05
NIH Institute/Center: NIH
Principal Investigator: MARK CHANCE