Polygenic Score for the Prediction of Postoperative Nausea and Vomiting: A Retrospective Derivation and Validation Cohort Study.

Abstract

BACKGROUND Postoperative nausea and vomiting (PONV) is a key driver of unplanned admission and patient satisfaction following surgery. Because traditional risk factors do not completely explain variability in risk, we hypothesize that genetics may contribute to the overall risk for this complication. The objective of this research is to perform a genome-wide association study of PONV, derive a polygenic risk score for PONV, assess associations between the risk score and PONV in a validation cohort, and compare any genetic contributions to known clinical risks for PONV. METHODS Surgeries with integrated genetic and perioperative data performed under general anesthesia at Michigan Medicine and Vanderbilt University Medical Center were studied. PONV was defined as nausea or emesis occurring and documented in the PACU. In the Discovery Phase, genome-wide association studies were performed on each genetic cohort and the results were meta-analyzed. Next, in the Polygenic Phase, we assessed whether a polygenic score, derived from genome-wide association study in a derivation cohort from Vanderbilt University Medical Center, improved prediction within a validation cohort from Michigan Medicine, as quantified by discrimination (C-statistic) and net reclassification index. RESULTS Of 64,523 total patients, 5,703 developed PONV (8.8%). We identified 46 genetic variants exceeding P<1x10-5 threshold, occurring with minor allele frequency > 1%, and demonstrating concordant effects in both cohorts. Standardized polygenic score was associated with PONV in a basic model, controlling for age and sex, (aOR 1.027 per standard deviation increase in overall genetic risk, 95% CI 1.001-1.053, P=0.044), a model based on known clinical risks (aOR 1.029, 95% CI 1.003-1.055, P=0.030), and a full clinical regression, controlling for 21 demographic, surgical, and anesthetic factors, (aOR 1.029, 95% CI 1.002-1.056, P=0.033). The addition of polygenic score improved overall discrimination in models based on known clinical risk factors (c-statistic: 0.616 compared to 0.613, P=0.028) and improved net reclassification of 4.6% of cases. CONCLUSION Standardized polygenic risk was associated with PONV in all three of our models, but the genetic influence was smaller than exerted by clinical risk factors. Specifically, a patient with a polygenic risk score > 1 standard deviation above the mean, has 2-3% greater odds of developing PONV when compared to the baseline population, which is at least an order of magnitude smaller than the increase associated with having prior PONV/motion sickness (55%), having a history of migraines (17%), or being female (83%), and is not clinically significant. Furthermore, the use of a polygenic risk score does not meaningfully improve discrimination compared to clinical risk factors and is not clinically useful.