New insights on persistent opioid use after surgery and genetic associations to opioid use disorder.
Study demonstrates the association between persistent opioid use and OPRM1 phenotypes as clinically important, offering evidence of shared biology between opioid dependence and addiction.
October 10, 2024 8:50 AM
ANN ARBOR, Mich. – Persistent opioid use after surgery is a common morbidity outcome associated with subsequent opioid use disorder, overdose, and death. While phenotypic associations have been described in previous research publications, genetic associations have remained unidentified.
In a recent edition of Genetic Epidemiology, Aubrey C. Annis and mentors Gonçalo R. Abecasis and Chad Brummett have new insights to share on these genetic associations in their publication, “Genetic Associations of Persistent Opioid Use After Surgery Point to OPRM1 but Not Other Opioid-Related Loci as the Main Driver of Opioid Use Disorder”.
Annis, Abecasis, Brummett, and co-authors, conducted the largest genetic study of persistent opioid use after surgery, comprising ~40,000 non-Hispanic, European-ancestry Michigan Genomics Initiative participants (3,198 cases and 36,321 surgically exposed controls). This study primarily focused on the reproducibility and reliability of 72 genetic studies of opioid use disorder phenotypes. Nominal associations (p < 0.05) occurred at 12 of 80 unique (r < 0.8) signals from these studies. Six occurred in OPRM1 (most significant: rs79704991-T, OR = 1.17, p = 8.7 × 10), with two surviving multiple testing corrections. One of the more exciting outcomes of the study can be found when looking at associations of previously identified OPRM1 variants, which suggests common biology between persistent opioid use and opioid use ‘disorder’ (diagnostic term for opioid addiction), further demonstrating connections between opioid dependence and addiction phenotypes. Lack of significant associations at other variants challenges previous studies’ reliability.
“Demonstrating the association between persistent opioid use and OPRM1 is clinically important, as it offers evidence of shared biology between opioid dependence and addiction.” Chad Brummett, MD, the Bert N LaDu Professor of Anesthesiology and senior author of the study.
Aubrey C. Annis, Doctoral Candidate in Biostatistics says, “Genetic testing panels that quantify an individual’s genetic predisposition for specific diseases, such as opioid use disorder, are becoming increasingly popular in the medical community. Based on our analysis of prescription data in the Michigan Genomics Initiative, we believe that SNP chips testing for variations in OPRM1 could provide helpful information for patients, particularly those utilizing opioids for pain management, who have elevated genetic risk for persistent opioid use. Genetic testing for variations in OPRM1 could help prevent patient progression from medically approved opioid use to deleterious outcomes like opioid dependence or opioid use disorder. However, our study revealed that inclusion of other genes commonly analyzed in opioid studies, such as OPRD1 and DRD2/ANKK1, do not have statistical justification for inclusion in these panels and could mislead patients being tested for susceptibility to opioid use. More genetic studies of prescription opioid use are needed to confirm the pathways involved in patient progression from opioid prescriptions to more severe opioid outcomes.”
Primary funding for this study came from the National Institute on Drug Abuse, with additional funding from the National Institute of General Medical Sciences, the National Institute on Aging/USC Roybal Center for Behavioral Interventions in Aging, the US National Institutes of Health K08 Award, and the National Institute of Arthritis and Musculoskeletal and Skin Diseases. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
The study was further supported by Precision Health at the University of Michigan, and data were in part from the Michigan Genomics Initiative.
Study co-authors hail from University of Michigan School of Public Health, Dept of Biostatistics and Center for Statistical Genetics, University of Michigan Medical School’s Department of Anesthesiology, the Opioid Research Institute at University of Michigan, and Vanderbilt University Medical Center’s Department of Anesthesiology.
