Rare variant associations of chronic pain conditions in the UK Biobank Whole Exome Sequencing

Introduction

In this population-based genetic study of chronic pain, we performed association analysis, including rare variants analysis, across a broad spectrum of conditions. While it is well-established that genetic factors play a significant role in the susceptibility to chronic pain, genome-wide association studies (GWAS) conducted to date have only uncovered a small portion of the genetic variants that likely contribute to its heritability. Our study identified shared genetic contributors to pain conditions at variant and gene levels, on a genome-wide basis.

Methods

We performed genome wide association analysis of chronic pain using the whole exome sequencing data in the UK Biobank across chronic pain conditions using optimized control cohorts. 355 chronic pain endpoints were derived from ICD diagnoses and a pain-specific questionnaire. For that purpose, we recalibrated principal components to account for population stratification and designed control cohorts to minimize bias and variability in the identified associations. Additionally, we analysed the shared genetic heritability of these different pain conditions using latent causal variable analysis on genotypic array data. Finally, we compared genes from our genome-wide significant associations with prior reported pain relevant genes.

Results

We found novel associations for mutations in all investigated pain conditions, with a particular emphasis on rare variants in the full UK Biobank cohort, which opens new opportunities for therapeutic approaches in the age of genetic medicines. Consequently, novel mechanisms of enigmatic diseases like complex regional pain syndrome and Fibromyalgia can be proposed. Many of these associations revealed the relevance of auto-immune processes and vascular pathophysiology. For example, in complex regional pain syndrome we found several novel genome wide significant associations. Examples include a causal rare missense variant in sialic acetyl esterase (SIAE R479C, p-value 3.34E-08, odds ratio 7.1, MAF 1e-04) and a protective rare missense variant in Mammary Analogous Zinc Finger 2 (MAML2, p-value 6.57E-06, odds ratio 0.62, MAF 0.015, I480M, rs61749251), which acts as a transcriptional cofactor for Notch proteins.

We conducted epistasis analyses on top-ranking variants to assess mutation penetrance and identified a causal mutation in JCAD (V366E; β = 3.4, χ² = 20.4, OR = 29.9, p = 6.39×10⁻⁶), a gene previously implicated in coronary artery disease. Given JCAD’s role in endothelial cell junctions and vascular integrity, this mutation may also influence neurovascular contributions to pain signalling, particularly in chronic inflammatory states.

Importantly, we discovered a rare protective variant in PLA2G7 (S388P; β = –2.1, OR = 0.12, χ² = 12.9, p = 3.16×10⁻⁴), encoding lipoprotein-associated phospholipase A2, which is involved in phospholipid catabolism during inflammation and oxidative stress. This variant appears to limit oxylipin accumulation in the vascular wall—a mechanism that may reduce neuroinflammation and peripheral sensitization, offering a protective effect against pain pathophysiology.

The use of several control groups of different sizes allowed us to analyse the variability of results depending on this control cohort composition to characterize the sensitivity of genetic associations. This revealed several novel genome wide significant associations that were formerly of lower significance in osteoarthritis. Within our dataset of associations, we found frequently occurring variants that were associated with multiple chronic pain phenotypes suggesting common mechanisms across different pain conditions. Finally, we highlight the identification of novel mutations in known pain genes especially in sodium, potassium and calcium channels.

Conclusions

This study provides valuable insights into the genetic architecture of pain conditions by leveraging rare variant analysis and using optimized controls in a large-scale population cohort. Our findings implicate novel genetic associations and their role in pain susceptibility, paving the way for targeted research in the understanding of chronic pain conditions.