Background & Aims

Chronic pain is a debilitating health issue, afflicting an estimated 20% of the global population[1]. While Genome-wide association studies (GWASs) have uncovered numerous common variants linked to chronic pain susceptibility[2, 3], the use of rare coding variants is still in its early stages. Our research is dedicated to the identification of the coding genetic variants contributing to chronic pain. We leveraged the large-scale UK Biobank (UKBB) whole-exome sequencing (WES) database[4], which includes sequences from over 500,000 participants along with their comprehensive health records. By applying advanced analytical tools, we were able to explore the association and implications of both common variants and rare variants to chronic pain.

Methods

We first screened the UKBB WES database for Caucasians who self-reported chronic pain. We then selected subjects according to eight distinct types of pain: headache, facial pain, neck or shoulder pain, stomach or abdominal pain, back pain, hip pain, knee pain, and general pain. Based on the number of pain types experienced simultaneously, we defined three additional pain traits: lone pain, overlapping pain, and multisite pain. Participants who reported no pain were classified as controls. We carried out variant-level and gene-level association tests. To enhance rare variants’ signals, we categorized these variants into three functional groups: high-confidence loss-of-function variants, deleterious missense variants, and possible damaging missense variants. We then conducted gene-level analyses for rare variants. To explore the genetic contribution of coding variants to pain, we also performed a pathway analysis, tissue enrichment analysis, and heritability estimation analysis.

Results

The quality control measures that we applied left us with 393,485 human subjects and 26,388,327 genetic variants for the downstream analysis. Our variant-level analysis identified 347 significant variant-pain pairs, corresponding to 247 variants and 129 genes, with the largest set of signals found in the headache patients. From the gene-level analysis, we detected eight pain-related genes (ANKRD12, ARID5A, CCDC88A, DPP7, KIF20B, SLC13A1, UBR2, ZNF558), seven of which were linked to one pain trait except ANKRD12. All the identified genes and variants were further analyzed. We found that they were enriched in pathways related to nervous system development, with the regulation of neuron project development as the most significant pathway. Notably, we uncovered that rare variants generally explained more heritability than common variants. The highest rare variant heritability was observed in neck or shoulder pain while the largest common variant heritability was in overlapping pain.

Conclusions

In this study, we explored the genetic foundations of chronic pain in the UK Biobank. The variant association tests identified 247 pain-related variants. Most the variants were unique to a specific pain condition, proportional to the sample size of each pain trait, suggesting distinct pathogenic pathways among chronic pain. Headache patients showed the largest set of variants, indicating a relatively high heritability of headache, which was verified by heritability estimation. Analysis on rare variant revealed eight pain genes, seven of which were novel findings and the eighth gene, SLC13A1, was reported in our previous study[5]. Pathway analysis on all pain genes demonstrated the critical role of nervous system in pain. We found that the rare variants generally explained a larger proportion of the genetic variance in chronic pain than common variants, highlighting the significance of rare variant study. Our findings offer valuable insights into the genetic basis of chronic pain.

References

[1] Zimmer Z, Fraser K, Grol-Prokopczyk H, et al. A global study of pain prevalence across 52 countries: examining the role of country-level contextual factors. PAIN 2022; 163: 1740.
[2] Diatchenko L, Slade GD, Nackley AG, et al. Genetic basis for individual variations in pain perception and the development of a chronic pain condition. Human Molecular Genetics 2005; 14: 135–143.
[3] Chasman DI, Schürks M, Anttila V, et al. Genome-wide association study reveals three susceptibility loci for common migraine in the general population. Nat Genet 2011; 43: 695–698.
[4] Backman JD, Li AH, Marcketta A, et al. Exome sequencing and analysis of 454,787 UK Biobank participants. Nature 2021; 599: 628–634.
[5] Ao X, Parisien M, Zidan M, et al. Rare variant analyses in large-scale cohorts identified SLC13A1 associated with chronic pain. PAIN 2022; 10.1097/j.pain.0000000000002882.

Presenting Author

Xiang Ao

Poster Authors

Xiang Ao

PhD student

McGill University

Lead Author

Marc Bouffard

McGill University

Lead Author

Francesca Montagna

McGill University

Lead Author

Luda Diatchenko

McGill University

Lead Author

Topics

  • Genetics