SPPM Annual Meeting - Award Winning Abstracts
Biopsychosocial Clusters Based on Genetic Risk Scores for Chronic Post-Surgical Pain in Children Undergoing Spine Fusion
Vidya Chidambaran, MD;1 Valentina Pilipenko, PhD;2 Anil G. Jegga, DVM;3 Lisa J. Martin, PhD2
(submitted by Vidya Chidambaran, MD)
1Department of Anesthesiology, Cincinnati Children’s Hospital Medical Center
2Division of Human Genetics, Cincinnati Children’s Hospital Medical Center
3Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center
Chronic post-surgical pain (CPSP) is a significant problem associated with disability and psychological consequences in children, with an incidence of 14.5 – 38%.1 Poor control of postoperative pain (PoP) and childhood anxiety sensitivity (CASI), are associated with chronic postsurgical pain (CPSP) after spine fusion in children.2 Pain sensitivity and anxiety have high heritable risk and likely, common underlying genetic processes underly predisposition to CPSP endophenotypes with varying risk combinations for CASI and PoP.3
However, genetic variants have small effect sizes in prediction of CPSP.4 Thus, we hypothesized that polygenic risk will improve predictive accuracy of CPSP common genetic risk profiles will determine endophenotypes of CPSP. This would allow a priori risk stratification to enable personalized preventive/therapeutic measures.
Systematic literature review for known genes associated with phenotypes (PoP, CPSP, CASI), was followed by computational modeling to identify novel prioritized gene sets using the Toppgene data portal (based on similarity scores for various functional notations).5 After IRB approval and appropriate consent, we prospectively recruited 171 children undergoing spinal fusion under standard anesthesia/pain protocols, assessed preoperative CASI/pain, pain scores and opioids use immediately after and 6-12 months post-surgery. Blood samples were analyzed using Omni5M arrays. After strict quality criteria, association analyses of phenotypes with ranked deciles of prioritized gene variants (against 10,000 matched control gene sets) was conducted. This was followed by gene set enrichment analyses to determine pathways enriched by significant gene variants. Polygenic risk scores were developed to predict phenotypes, and hierarchical cluster analysis used to determine genotype-phenotype clusters.
Systematic review provided 31, 38 and 61 literature curated genes with variants associated in CPSP, PoP and anxiety respectively. Toppgene was used to identify novel genes which were scored and ranked to provide prioritized gene sets. The cohort (14.5±1.8 years, 75% female) had CASI scores of 28.5±8.5 and pain scores of 2.2+2.5 at 6-12 months. After adjusting for covariates (including demographics, surgical duration, preoperative pain) compared to control sets, there was enrichment of SNP associations in 10th-50th decile gene sets (p<0.05) for CASI, 50-80% deciles for PoP, and training set for CPSP (p<0.001; Benjamini-Hochberg correction). Common and unique biological processes enriched by significant SNP sets were identified for each phenotype. Polygenic risk scores predictive of phenotypes (p<0.05) were derived. CPSP was predicted with 92% accuracy (AUC of ROC). Five endophenotypes were identified by hierarchical clustering of risk for PoP, CASI and CPSP. Genotype risk clusters predicted the endophenotypes with 70% accuracy.
In summary, ours is the first pediatric study to identify genetic data integrated biopsychosocial factor clusters for CPSP. Further phenotype refinement and validation of risk scores is needed in larger and diverse surgical cohorts. These findings further our ability to guide clinical decision and tailor preventive strategies to decrease the incidence of CPSP.
References:
- Rabbitts et. al. J Pain. 2017 Jun;18(6):605-614
- Chidambaran et. al. Eur J Pain. 2017 Aug;21(7):1252-1265
- Hettema et. al. American Journal of Psychiatry 2001 158:10, 1568-1578
- Lichtenwalter et. al. Neuroscience 338 (2016) 36–62
- Chen et. al. BMC Bioinformatics. 2007 Oct 16;8:392
