Background & Aims
Although there are multiple factors that have been shown to influence pain after surgery, genetic factors have been identified as potential risk factors in the development of chronic postoperative pain (CPSP). CPSP affects up to 30% of postsurgical patients. Yet attempts to predict patients that are genetically predisposed to severe postoperative pain or who will progress to develop CPSP, have been largely ineffective. The goal of this work is to identify genetic variants that are associated with the development of acute postoperative pain and/or CPSP, as well as validate previously reported alleles. Identifying variants associated with post-surgical pain will provide insight into the pathophysiology of pain and could serve as a basis for future investigation into personalized pharmacologic therapies for the prevention and treatment of postoperative pain.
Methods
Patients were recruited prior to surgery and completed a brief battery validated, self-report measures, including pain severity using the 0-10 Likert scale pain questions from the Brief Pain Inventory, which has been validated in various pain disorders. DNA was extracted from a blood sample collected at consent.
The primary outcome was change in patient-reported surgical site pain (scaled from 0 to 10) from baseline to 3 months postoperatively (? = postsurgical – baseline). We performed genome-wide association analyses using SAIGE software. We controlled for the first 10 principal components as well as chip and study versions. Our primary outcome was the difference in pre- and postsurgical pain scores. Prior to inputting our phenotype into SAIGE, we performed a linear regression on difference scores in the R statistical software, using patient age, gender, and preoperative (baseline) pain score as covariates.
Results
Genetic and survey data from a total of 3,594 patients were included in our analysis. Our cohort was 61.9% female, 61.4% age 65 and older, and 91.6% self-reporting as white race. 29.5% of patients had baseline pain scores of 7 or greater on a 10-point scale. At 3 months post-surgery, 61.6% had a decrease in pain score from baseline, 29.0% had no change in pain score, and 9.4% had an increase in pain score. Genome-wide association with patient-reported surgical site pain did not demonstrate any loci that reached genome-wide significance. Furthermore, analysis of previously identified single nucleotide polymorphisms (SNPs) showed no significant associations with these SNPs in our cohort.
Conclusions
We have conducted a genome-wide association study of chronic postsurgical pain in the largest cohort (>3500 patients) used thus far, using prospectively collected patient survey data. Though prior GWAS done in smaller cohorts have identified significant associations with postsurgical pain, we found no loci that reached genome-wide significance in our cohort. Additionally, genes and variants previously reported to be significantly associated with postsurgical pain were not found to reach predetermined level of significance in our cohort. Our study shows the difficulty in finding significant genetic association with a phenotype as fluid and with subtle variability as self-reported pain. Previously reported significant associations should also be critically assessed when not replicated in larger, well-phenotyped cohorts.
References
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Presenting Author
Stephan Frangakis
Poster Authors
Stephan Frangakis
MD, PhD
University of Michigan
Lead Author
Matthew Zawistowski
Ph.D
School of Public Health, University of Michigan
Lead Author
Vidhya Gunaseelan
MBA
. Department of Anesthesiology, University of Michigan Medical School
Lead Author
Mark Bicket
M.D.
Department of Anesthesiology, University of Michigan Medical School
Lead Author
Chad Brummett
University of Michigan
Lead Author
Topics
- Genetics