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Study: Test Identifies Susceptibility to Opioid Use Disorder


— January 9, 2025

Genetic test for opioid use disorder shows inaccuracies, raising concerns about reliability.


Opioid use disorder (OUD) remains a significant public health issue in the United States, affecting over six million individuals aged 12 and older in 2022. As efforts to address this crisis continue, researchers have explored various methods to identify those at greater risk, including genetic testing. Recently, a test based on 15 genetic markers received pre-marketing approval from the FDA, aiming to predict susceptibility to OUD. However, new findings published in JAMA Network Open cast doubt on the reliability of this test.

Led by Dr. Christal Davis of the Crescenz VA Medical Center and Dr. Henry Kranzler of the University of Pennsylvania, the study analyzed health records of over 450,000 veterans, including 33,000 individuals diagnosed with OUD. The research found that the genetic test often provided inaccurate results, with nearly half of its predictions being incorrect. For every 100 cases, the test misclassified 47 individuals, a performance no better than chance. These inaccuracies raise concerns about the potential consequences for both patients and healthcare providers.

False negatives, where a person at high risk is labeled as low risk, could give patients a false sense of security about opioid use. This may lead to increased prescriptions and subsequent addiction. On the other hand, false positives, where low-risk individuals are incorrectly flagged as high risk, might result in denial of necessary pain management and contribute to stigma. These risks highlight the importance of ensuring the accuracy of such tools before integrating them into clinical practice. The potential for harm extends beyond individual patients, as incorrect assessments can disrupt trust in healthcare systems and strain relationships between patients and providers.

Study: Test Identifies Susceptibility to Opioid Use Disorder
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The study also emphasized the complexity of conditions like OUD, which arise from a combination of genetic, environmental, and experiential factors that lead to susceptibility. For instance, variations in ancestry and life experiences significantly influence the risk of developing OUD, making it challenging to create a one-size-fits-all genetic test. Cultural, social, and economic factors also play a role in shaping addiction risks, further complicating the development of predictive tools. Drs. Davis and Kranzler, along with other psychiatric geneticists, recently addressed these concerns in a letter to Lancet Psychiatry. They urged regulators to account for these complexities when evaluating genetic testing for OUD and other mental health disorders.

Support for this research came from the Million Veteran Program, an initiative of the U.S. Department of Veterans Affairs that examines how genes, lifestyle, and military experiences impact health. Additional funding was provided by the VA, the VISN 4 Mental Illness Research, Education, and Clinical Center, and grants from the National Institutes on Alcohol Abuse and Drug Abuse. This broad support underscores the importance of rigorous, well-funded studies in advancing understanding and treatment of conditions like OUD.

These findings call for caution in adopting genetic tests for identifying susceptibility to conditions like OUD. While the idea of predicting addiction risk through genetics is appealing, the science is still in its early stages. Until testing methods are refined and backed by more robust data, reliance on these tools could do more harm than good. Comprehensive approaches that consider genetics alongside environmental and social factors are essential for addressing the multifaceted nature of OUD and providing effective care to those affected. In the meantime, public health initiatives, education, and evidence-based interventions remain critical in managing the ongoing opioid crisis.

Sources:

Study questions accuracy of genetic test for opioid use disorder

Utility of Candidate Genes From an Algorithm Designed to Predict Genetic Risk for Opioid Use Disorder

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