• Jacek Biesiada, Vidya Chidambaran, Michael Wagner, Xue Zhang, MartinLisa JLJ, Jaroslaw Meller, and Senthilkumar Sadhasivam.
• Division of Biomedical Informatics, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.
• Pharmacogenomics. 2014 Nov 1; 15 (14): 1749-1762.

AbstractBackground: Respiratory depression is a clinically and economically important but preventable complication of opioids. Genetic factors can help identify patients with high risk for respiratory depression. Methods: In this prospective genotype blinded clinical study, we evaluated the effect of a panel of variants in candidate genes on opioid-related respiratory depression in 347 children following tonsillectomy. Results: Using unsupervised hierarchical clustering and a combination of candidate genotypes and clinical variables, we identified several distinct clusters of patients at high risk (36-38%) and low risk (10-17%) of respiratory depression; the relative risk of respiratory depression for high versus low risk clusters was 2.1-3.8 (p = 0.003). Conclusion: Genetic risk predictions (genetic signatures) along with clinical risk factors effectively identify children at higher and lower risks of opioid-induced respiratory depression. Genetic signatures of respiratory depression offer strategies for improved clinical decision support to guide clinicians to balance the risks of opioid adverse effects with analgesia. Original submitted 9 July 2014; Revision submitted 19 September 2014.

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