Mia Rough is a postdoctoral researcher at Wake Forest University School of Medicine. She studies the neurobiological and behavioral mechanisms underlying substance use disorders. In this Postdoc Portrait interview, she shares her early motivation for this field and the next research question she wants to investigate.
Modeling Polysubstance Use Reinforcement
Q | What drew you to studying substance abuse disorders?
What drew me to this field was my early exposure to people living with substance use disorders. My dad is an addiction psychiatrist, and as an undergraduate student, I worked as a receptionist in his office. In that role, I interacted regularly with patients and saw firsthand how devastating substance use can be for individuals and families. I also saw how limited our treatment options often are, especially for stimulant use disorders. That made me want to contribute in a way that could help move the field forward. Research felt like the right path because it offered a way to address these problems at their roots by improving how we understand substance use disorders and how we develop treatments. My interest in polysubstance use came from that same motivation. Real-world substance use is rarely simple, and our science should reflect that.
Q | What scientific problem are you trying to solve?
There is an ongoing substance use crisis in the United States, particularly the sharp rise in stimulant-involved overdose deaths. More than one million Americans have died from a fatal drug overdose since 2000, and since 2013 there has been a dramatic increase in stimulant-related overdose deaths, many of which involve polysubstance use. My research focuses on polysubstance use because most people with stimulant use disorders do not use one drug in isolation, yet many preclinical models still study substance use disorders as if they do. I study how commonly co-used substances such as alcohol, nicotine, and opioids alter cocaine reinforcement and treatment responsiveness in nonhuman primate models. The goal is to develop more clinically relevant preclinical models that can help identify new interventions for stimulant use disorders for which there are currently no FDA-approved medications.
Deconstructing Addiction Misconceptions
Q | What’s one thing you learned from working in addiction research that you didn’t expect?
One thing I learned that I did not fully expect is how much the design of our preclinical models may contribute to the lack of effective treatments for stimulant use disorders. Preclinical models are the backbone of drug discovery and development, yet they often fail to incorporate factors that can dramatically influence the initiation, maintenance, and treatment of drug use. In real-world settings, people do not use stimulants in isolation, and their drug-taking behavior is shaped by social context, alternative reinforcers, and co-use of other substances. Our recent work has reinforced the importance of those variables. We have found that co-use of nicotine with cocaine, alcohol with cocaine, and the combination of all three can decrease the efficacy of a behavioral intervention designed to reduce cocaine choice. That finding changed how I think about treatment development. It suggests that some interventions may fail not because the target is wrong, but because the models used to test them do not adequately reflect the complexity of human substance use.
Q | If your research succeeds, what could it change for science or society?
It could help accelerate the development of new treatments for stimulant use disorders for which there are currently no FDA-approved medications. The most important outcome would be saving lives and improving quality of life for people with substance use disorders and their families. Beyond that, the societal impact could also be substantial. Substance use imposes an enormous economic burden in the United States, often estimated in the hundreds of billions of dollars each year due to lost productivity, health care costs, and criminal justice involvement. I hope my work helps improve the preclinical pipeline for medication discovery so that promising interventions are tested in models that better predict what will work in patients.
Q | What question are you most excited to answer next?
One question I am especially excited to answer next is how sleep disruption contributes to substance use and relapse vulnerability. Much of our work so far has focused on social context, biological sex, polysubstance use, and brain-based biomarkers of substance use disorders. An exciting next step is to integrate sleep architecture into these models. Sleep disturbances are common across neuropsychiatric disorders, and growing evidence suggests there may be a bidirectional relationship between poor sleep and substance use. That makes sleep a particularly promising target, both as a biomarker and as a potential point of intervention. I am especially interested in determining whether drug use alters sleep in ways that further increase vulnerability, and whether medications that improve sleep can reduce drug taking or improve treatment response. If so, sleep-targeted interventions could open a new avenue for treating substance use disorders.
Responses have been edited for length and clarity.
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