Persistent pain after surgery (CPSP) in children is a significant problem impeding rehabilitation and recovery; it adversely affects daily quality of life during developmental stages and leads to chronic pain/disability as adults. It is important to be able to predict which children are at higher risk for developing CPSP, to direct preventive and therapeutic strategies, and mitigate devastating consequences. Based on our preliminary findings in adolescents undergoing spine surgery, we hypothesize that certain genetic and epigenetic variables influence an individual’s risk for CPSP. The proposed study aims to validate our preliminary findings, obtain further insights into strata with varying degree of individual risk and develop a predictive algorithm incorporating distinct patterns of genetic, epigenetic and non-genetic covariates contributing to risk of CPSP. The genes we will investigate have functional relevance in the pain-opioid pathway including those involved in peripheral nociception and central opioid effects.
The innovativeness of this study is that genetic variants and epigenetics have never been investigated in children as predictors of CPSP. Also, application of bioinformatics approaches (decision tree and unsupervised hierarchical clustering) in conjunction with traditional statistical methods to identify risk clusters is novel. This research complements ongoing genomics research supported by a NIH funded K23 (PI: Chidambaran, perioperative pain clinical researcher), and she is aided by experts in genetics (Martin), epigenetics (Ji) and bioinformatics (Meller). Our chosen genetic targets are variants that occur frequently, so that genotype based prediction and interventions could benefit 1-2 in 5 children undergoing surgery. The proposed research has clinical translational potential as the findings could propel commercialization of DNA-methylation based and combinatorial genomics assays in simple blood/saliva tests to identify children at risk of CPSP; it has extended benefits to children with chronic non-surgical pain, and is highly likely to provide new targets for interventions.