Predictive model IDs patients at risk of opioid dependence

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The opioid epidemic continues to impact millions of Americans, but researchers have developed a new method to genetically identify patients more at risk of developing an opioid addiction. Findings are published in Annals of Clinical & Laboratory Science.

Some two million Americans struggle with opioid abuse. As the number continues to rise, researchers are exploring genetic factors that could influence an individual’s risk for opioid addiction. This study examined the frequency of 16 single nucleotide polymorphisms in the brain's reward center in patients with and without opioid addictions to identify trends in which patients have a greater risk for addiction.

The study evaluated 37 patients with opioid or heroin addiction, comparing data with 30 control participants. The predictive method was then tested on another 138 samples for predictably. Results showed the model was able to predict with 97 percent accuracy those at low risk of developing an opioid dependence.

“This negative likelihood ratio can be used as an evidence based measure to exclude patients with a high risk of opioid addiction or substance use disorder,” concluded first author Keri Donaldson, MD, MSCE, and colleagues. “By identifying patients with a lower risk for opioid addiction, our model may inform therapeutic decisions.”