University of Maryland experts in genomics and psychology have teamed up to explore new approaches to help those struggling to leave opioid use disorder behind.

Najib El-Sayed, a professor of cell biology and molecular genetics, is working with Xuan “Anna” Li, an assistant professor of psychology, to uncover genetic and epigenetic changes—how genes are turned on or off—linked to relapse behavior involving oxycodone abuse.

Their work is supported by a $77,500 grant from the UMD Brain and Behavior Institute (BBI), one of three projects selected recently for BBI seed funding.

The research builds upon Li’s work that combines advanced neuroscience techniques with behavioral experiments involving rats, examining how specific activity in the rodent’s brain drives relapse. The goal is to use the results from those earlier experiments to help create a model applicable to human behavior.

The researchers intend to identify how specific neural circuits trigger relapse, which could lead to more targeted and effective treatments, Li said. According to the 2023 National Survey on Drug Use and Health, nearly 8.6 million Americans 12 years and older reported misusing prescription opioids in the past year. More than 81,000 people died of opioid disorders in 2023.

“Understanding these pathways will be crucial for disrupting the addiction cycle and ultimately improving outcomes for those who struggle with relapse,” she said.

Li’s lab has identified the critical orbitofrontal-striatal brain circuit, which connects brain regions responsible for decision-making and reward evaluation with those that regulate motivation and behavior. While these areas are central to addiction, the exact processes that initiate relapse remain poorly understood.

To help provide answers, Li will rely heavily on genomic analyses offered by El Sayed and his team.

Using the cells collected by Li’s team, El-Sayed’s group will apply single-cell RNA sequencing and single-cell ATAC sequencing, a technique used to analyze the accessibility of chromatin within individual cells, allowing researchers to identify which genes are turned on or off in response to addiction-related signals.

Simultaneously, El-Sayed will lead the bioinformatics analysis, using advanced computational methods to integrate genetic and epigenetic data. With this synthesis of datasets, his team can uncover a more comprehensive understanding of how addiction-related behaviors are encoded in the brain, he said.

“Using these new approaches—where we’re examining DNA changes that are specific to behavioral outcomes—will hopefully have a positive impact on the grand challenges we face regarding the opioid crisis,” said El-Sayed, who has a joint appointment in the University of Maryland Institute for Advanced Computer Studies (UMIACS) and is a core faculty member in the Center for Bioinformatics and Computational Biology.

Source – The University of Maryland