| Title: | Genome-wide association study on chronic postsurgical pain after abdominal surgeries in the UK Biobank |
| Journal: | Anaesthesia |
| Published: | 29 Dec 2024 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/39734325/ |
| DOI: | https://doi.org/10.1111/anae.16528 |
Publication 14805
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Abstract
INTRODUCTION: Chronic pain is one of the most common and severe complications after surgery, affecting quality of life and overall wellbeing of patients. Several risk factors have been identified but the mechanisms of chronic postsurgical pain development remain unclear. This study aimed to identify single-nucleotide polymorphisms associated with developing chronic postsurgical pain after abdominal surgery, one of the most common types of surgery.</p>
METHODS: A genome-wide association study was performed on 27,603 patients from the UK Biobank who underwent abdominal surgery. The robustness of identified loci was validated by split-half validation analysis. Functionally related top loci were selected for expression validation in clinical samples of adhesions from patients with and without pain.</p>
RESULTS: One locus (rs185545327) reached genome-wide significance for association with chronic postsurgical pain development, and 10 loci surpassed the suggestively significant threshold (p < 1 × 10-6). In the robustness analysis, eight loci had at least nominal significance. The loci passing the suggestively significant threshold were mapped to 15 genes, of which two loci contained pain-related genes (SRPK2, PDE4D). Although marginally approaching statistical significance in the expression validation of clinical samples, the detection rate and expression level of PDE4D were modestly higher in patients with pain compared with those in the control group.</p>
DISCUSSION: This study provides preliminary evidence for genetic risk factors implicated in chronic postsurgical pain following abdominal surgery, particularly the PDE4D gene, which has been associated with pain in previous studies. The findings add to evidence suggesting potential for the future development of a clinically applicable tool for personalised risk prediction, aiding clinicians in stratifying patients and enhancing clinical decision-making through individualised risk assessments.</p>
8 Authors
- Song Li
- Masja K. Toneman
- Judith P. M. Mangnus
- Stefano Strocchi
- Regina L. M. van Boekel
- Kris C. P. Vissers
- Richard P. G. ten Broek
- Marieke J. H. Coenen
1 Application
| Application ID | Title |
|---|---|
| 64102 | Understanding the mechanisms of pain (heterogeneity) |
Enabling scientific discoveries that improve human health