Background & Aims

Hip pain is a common musculoskeletal complaint that leads many people to seek medical attention. Approximately 14.3% of the population aged 60 and above have reported substantial hip pain persisting for most days over a six-week period. This study aims to explore the genetic basis of the hip pain phenotype.

Methods

We performed a comprehensive genome-wide association study (GWAS) on hip pain, utilizing data from 221,127 participants from the UK Biobank cohort, to identify genetic variants linked to hip pain. Following the primary GWAS, we carried out two sex-stratified secondary GWASs. Additionally, our research further conducted several post-GWAS analyses, including advanced visualization, gene and gene-set analysis, tissue examination using the FUMA web application, and genetic correlation assessments through Linkage Disequilibrium Score Regression (LDSC).

Results

In the primary GWAS, we found 7 different loci associated with hip pain at GWAS significance level, with the most significant SNP being rs77641763, which is situated within the EXD3 (p value = 2.20 x 10^-13). We utilized publicly available summary statistics from the FinnGen cohort and a previous GWAS meta-analysis on hip osteoarthritis as replication cohorts. Four loci (rs509345, rs73581564, rs9597759, rs2018384) were replicated with a p value less than 0.05. The tissue expression analysis indicated significant associations between brain tissues and hip pain. In the sex-stratified GWASs, three unique significant loci (top SNPs: rs12533425, rs1978969, rs552965738, respectively) were identified in females, and one unique significant locus (top SNP: rs4726995) was identified in males. Furthermore, we found strong genetic correlations between hip pain and several other phenotypes.

Conclusions

This study has identified, for the first time, 7 genetic loci associated with hip pain. It also highlights sex-specific differences in hip pain phenotype and explores genetic correlations between hip pain and other phenotypes. These findings provide a vital foundation for future research into the mechanisms underlying hip pain and hip osteoarthritis, potentially guiding more effective treatment and prevention strategies.

References

1. Bulik-Sullivan, B. K., Loh, P. R., Finucane, H. K., Ripke, S., Yang, J., Patterson, N., Daly, M. J., Price, A. L., & Neale, B. M. (2015). LD Score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat Genet, 47(3), 291-295. https://doi.org/10.1038/ng.3211
2. Henkel, C., Styrkársdóttir, U., Thorleifsson, G., Stefánsdóttir, L., Björnsdóttir, G., Banasik, K., Brunak, S., Erikstrup, C., Dinh, K. M., Hansen, T. F., Nielsen, K. R., Bruun, M. T., Dowsett, J., Brodersen, T., Thorgeirsson, T. E., Gromov, K., Boesen, M. P., Ullum, H., Ostrowski, S. R., . . . Troelsen, A. (2023). Genome-wide association meta-analysis of knee and hip osteoarthritis uncovers genetic differences between patients treated with joint replacement and patients without joint replacement. Ann Rheum Dis, 82(3), 384-392. https://doi.org/10.1136/ard-2022-223199
3. Tachmazidou, I., Hatzikotoulas, K., Southam, L., Esparza-Gordillo, J., Haberland, V., Zheng, J., Johnson, T., Koprulu, M., Zengini, E., Steinberg, J., Wilkinson, J. M., Bhatnagar, S., Hoffman, J. D., Buchan, N., Süveges, D., Yerges-Armstrong, L., Smith, G. D., Gaunt, T. R., Scott, R. A., . . . Zeggini, E. (2019). Identification of new therapeutic targets for osteoarthritis through genome-wide analyses of UK Biobank data. Nat Genet, 51(2), 230-236. https://doi.org/10.1038/s41588-018-0327-1
4. Yang, J., Lee, S. H., Goddard, M. E., & Visscher, P. M. (2011). GCTA: a tool for genome-wide complex trait analysis. Am J Hum Genet, 88(1), 76-82. https://doi.org/10.1016/j.ajhg.2010.11.011

Presenting Author

Qi Pan

Poster Authors

Qi Pan

PhD

University of Nottingham Ningbo China

Lead Author

E-mail

Tengda Cai

Nottingham Ningbo China Beacons of Excellence Research and Innovation Institute

Lead Author

E-mail

Abirami Veluchamy

PhD

University of Dundee

Lead Author

E-mail

Harry Hebert

University of Dundee

Lead Author

E-mail

Peixi Zhu

Lead Author

E-mail

Mainul Haque

Lead Author

E-mail

Tania Dottorini

Lead Author

E-mail

Lesley Colvin

University of Dundee

Lead Author

E-mail

Blair H. Smith

University of Dundee

Lead Author

E-mail

Weihua Meng

Nottingham Ningbo China Beacons of Excellence Research and Innovation Institute

Lead Author

Topics

  • Specific Pain Conditions/Pain in Specific Populations: Arthritis and Other Joint Pains