A University of Maryland genomics expert has teamed up with a UMD psychologist to explore new approaches to help those struggling with opioid addiction.
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 only three projects selected for BBI seed funding in 2024.
The research builds upon Li’s prior work, which combines advanced neuroscience techniques with behavioral experiments involving rats, examining how specific activity in the rodent’s brain drives relapse behaviors. The goal is to better characterize the results from those earlier experiments and create a model that is applicable to human behavior.
“Through this research, we hope to identify how specific neural circuits trigger relapse, which could lead to more targeted and effective treatments,” Li says. “Understanding these pathways will be crucial for disrupting the addiction cycle and ultimately improving outcomes for those who struggle with relapse.”
Li’s lab has identified a critical brain circuit involved in relapse: the orbitofrontal-striatal circuit. This circuit 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 the genomic analyses strengths 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, providing insights into the regulatory landscape of each cell.
This process allows researchers to identify which genes are turned on or off in response to addiction-related signals, hopefully leading to therapeutic intervention strategies that are currently not in use.
Simultaneously, El-Sayed will lead the bioinformatics analysis, using advanced computational methods to integrate genetic and epigenetic data. This synthesis of datasets will allow his team to uncover a more comprehensive understanding of how addiction-related behaviors are encoded in the brain, he says.
“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,” says El-Sayed, who has a joint appointment in the University of Maryland Institute for Advanced Computer Studies and is a core faculty member in the Center for Bioinformatics and Computational Biology.
—Story by Melissa Brachfeld, UMIACS communications group