# Identification of immune protective pathways dysregulated by opioid use in HIV infection, using a systems biology-based approach, toward the goal of pharmacological restoration of immune function

> **NIH NIH R01** · CASE WESTERN RESERVE UNIVERSITY · 2020 · $813,788

## Abstract

Abstract
In the era of combination antiretroviral therapy (cART) for HIV infection, a major focus of clinical and scientific
investigation lies with the high risk of cardiovascular disease, neurocognitive disorders, nephropathy, and
malignancy among many other non-AIDS complications. In addition, continuing problems with patient non-
compliance and a subsequent resurgence of HIV replication have lead the NIH to prioritize translational HIV
research focused on the identification and eradication of viral reservoirs. While strategies are being developed
to identify and reverse the latent pool, a parallel effort must proceed to enhance immune defenses against viral
persistence as well as re-establish immune homeostasis. The focus of this dual discovery and mechanistic
proposal is to identify pathways, molecular targets, and small molecule compounds that regulate immune
protection in the HIV patient, whose function is compromised by chronic opioid use and addiction. We
hypothesize that an unbiased systems biological evaluation of the T cell, dendritic cell, and B cell
transcriptome will reveal specific molecular targets, pathways, or signatures that affect HIV
persistence and reservoir size as well as non-AIDS complications. A key corollary of this hypothesis is
that chronic opioid addiction, via narcotic pain medication, will perturb these networks and associate
with increased HIV persistence, reservoir size, and systemic inflammation. This work will take advantage
of two distinct cohorts of virally suppressed HIV+ patients (with and without a prescription-based addiction to
the narcotic pain medication Percocet), available in Dr. Avery’s clinic at MetroHealth Medical Center in
Cleveland, Ohio, and our already characterized cohort of elite controllers. The work will focus around the
following Specific Aims:
Aim 1: Identify molecular networks in CD8+ and CD4+ T cell memory subsets, as well as in innate cells,
that are differentially regulated in opioid addiction and reciprocally regulated in elite controllers (EC)
that naturally control HIV infection.
Aim 2: Identify and dissect molecular signatures that are induced by opioid use in memory CD8+ and
CD4+ T cells that correlate with inflammation, exhaustion, immune failure, and HIV that are absent in
gene expression profiles from elite controllers.
Aim 3: Develop and evaluate discrete opioid use specific biomarkers of immune deficiency and
comorbidity to inform bioinformatic approaches to identify repurposed drugs to reverse the altered
networks.
The application of our highly refined transcriptional signature to a Biomarker panel will allow us to rapidly
screen a high number of compounds for their ability to rescue opioid-use related immune dysregulation in a
very small number of primary cells from cART suppressed HIV+ subjects. Thus, our overall goal is to
generate a refined list of therapeutic targets for pharmacologic restoration of immune function in HIV-
infected subjects that require opioid therap...

## Key facts

- **NIH application ID:** 9933863
- **Project number:** 5R01DA043253-05
- **Recipient organization:** CASE WESTERN RESERVE UNIVERSITY
- **Principal Investigator:** Alan David Levine
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $813,788
- **Award type:** 5
- **Project period:** 2016-09-01 → 2024-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9933863

## Citation

> US National Institutes of Health, RePORTER application 9933863, Identification of immune protective pathways dysregulated by opioid use in HIV infection, using a systems biology-based approach, toward the goal of pharmacological restoration of immune function (5R01DA043253-05). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9933863. Licensed CC0.

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