Association between COMMD1 gene polymorphism rs11125908 and rheumatoid arthritis in the Cuban population

Submitted: 4 December 2023
Accepted: 9 March 2024
Published: 24 June 2024
Abstract Views: 109
PDF: 58
SUPPLEMENTARY MATERIAL: 33
Publisher's note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

Authors

Objective. To evaluate the association of the rs11125908 polymorphism in the COMMD1 gene in the Cuban population with rheumatoid arthritis (RA).

Methods. In this case-control study, 161 RA patients and 150 control subjects were genotyped for rs11125908 by the allele-specific polymerase chain reaction method. DNA sequencing was used to verify the assignation of the polymorphism. The odds ratios (OR) and their 95% confidence interval were calculated by logistic regression to determine the associations between genotypes and RA using the SNPStats software.

Results. An association of the single nucleotide polymorphism with the disease was found in the overdominant model (p=0.025; OR=1.91) for the AG genotype. Our analyses revealed an association between rs11125908 and the subgroup of patients with swollen joints < median under the codominant model for AG (p=0.034; OR=2.30) and GG genotype (p=0.034; OR=0.82) and with the overdominant model (p=0.01; OR=2.38). The subgroup of patients with an age of onset lower than the mean and AG genotype showed an association in the overdominant model (p=0.027; OR=2.27). Disease activity score 28 with erythrocyte sedimentation rate and disease duration variables were not associated with the rs11125908 polymorphism.

Conclusions. rs11125908 was associated with RA and with the number of swollen joints and age of onset subgroup analyses. We provide concepts for treatments for RA, based on pharmacological management of COMMD1 expression.

Dimensions

Altmetric

PlumX Metrics

Downloads

Download data is not yet available.

Citations

Finckh A, Gilbert B, Hodkinson B, Bae SC, Thomas R, Deane KD, et al. Global epidemiology of rheumatoid arthritis. Nat Rev Rheumatol 2022; 18: 591-602. DOI: https://doi.org/10.1038/s41584-022-00827-y
Nilsson J, Andersson ML, Hafström I, Svensson B, Forslind K, Ajeganova S, et al. Influence of age and sex on disease course and treatment in rheumatoid arthritis. Open Access Rheumatol 2021; 13: 123-38. DOI: https://doi.org/10.2147/OARRR.S306378
Petrelli F, Mariani FM, Alunno A, Puxeddu I. Pathogenesis of rheumatoid arthritis: one year in review 2022. Clin Exp Rheumatol 2022; 40: 475-82. DOI: https://doi.org/10.55563/clinexprheumatol/l9lyen
Jin S, Zhao J, Li M, Zeng X. New insights into the pathogenesis and management of rheumatoid arthritis. Chronic Dis Transl Med 2022; 8: 256-63. DOI: https://doi.org/10.1002/cdt3.43
Akhtar M, Ali Y, Islam ZU, Arshad M, Rauf M, Ali M, et al. Characterization of rheumatoid arthritis risk-associated SNPs and identification of novel therapeutic sites using an in-silico approach. Biology (Basel) 2021; 10: 501. DOI: https://doi.org/10.3390/biology10060501
Sollis E, Mosaku A, Abid A, Buniello A, Cerezo M, Gil L, et al. The NHGRI-EBI GWAS catalog: knowledgebase and deposition resource. Nucleic Acids Res 2023; 51: D977-85. DOI: https://doi.org/10.1093/nar/gkac1010
Aluko A, Ranganathan P. Pharmacogenetics of drug therapies in rheumatoid arthritis. Methods Mol Biol 2022; 2547: 527-67. DOI: https://doi.org/10.1007/978-1-0716-2573-6_19
Stahl EA, Raychaudhuri S, Remmers EF, Xie G, Eyre S, Thomson BP, et al. Genome-wide association study meta-analysis identifies seven new rheumatoid arthritis risk loci. Nature Genetics 2010; 42: 508-14. DOI: https://doi.org/10.1038/ng.582
Lee YH, Bae S-C, Choi SJ, Ji JD, Song GG. Genome-wide pathway analysis of genome-wide association studies on systemic lupus erythematosus and rheumatoid arthritis. Mol Biol Rep 2012; 39: 10627-35. DOI: https://doi.org/10.1007/s11033-012-1952-x
Okada Y, Eyre S, Suzuki A, Kochi Y, Yamamoto K. Genetics of rheumatoid arthritis: 2018 status. Ann Rheum Dis 2019; 78: 446-53. DOI: https://doi.org/10.1136/annrheumdis-2018-213678
Marcheco-Teruel B, Parra EJ, Fuentes-Smith E, Salas A, Buttenschon HN, Demontis D, et al. Cuba: exploring the history of admixture and the genetic basis of pigmentation using autosomal and uniparental markers. PLoS Genet 2014; 10: e1004488. DOI: https://doi.org/10.1371/journal.pgen.1004488
Murata K, Fang C, Terao C, Giannopoulou EG, Lee YJ, Lee MJ, et al. Hypoxia-Sensitive COMMD1 integrates signaling and cellular metabolism in human macrophages and suppresses osteoclastogenesis. Immunity 2017; 47: 66-79.e5. DOI: https://doi.org/10.1016/j.immuni.2017.06.018
Riera-Romo M. COMMD1: a multifunctional regulatory protein. J Cell Biochem 2018; 119: 34-51. DOI: https://doi.org/10.1002/jcb.26151
Vockley CM, Barrera A, Reddy TE. Decoding the role of regulatory element polymorphisms in complex disease. Curr Opin Genet Dev 2017; 43: 38-45. DOI: https://doi.org/10.1016/j.gde.2016.10.007
Salih MH, Al-Azzawie AF, Al-Assie AHA. Intronic SNPs and genetic diseases: a review. Int J Res Appl Sci Biotechnol 2021; 8: 267-74. DOI: https://doi.org/10.31033/ijrasb.8.2.36
Cronstein BN, Aune TM. Methotrexate and its mechanisms of action in inflammatory arthritis. Nat Rev Rheumatol 2020; 16: 145-54. DOI: https://doi.org/10.1038/s41584-020-0373-9
Aletaha D, Neogi T, Silman AJ, Funovits J, Felson DT, Bingham CO, 3rd, et al. 2010 rheumatoid arthritis classification criteria: an American College of Rheumatology/European League Against Rheumatism collaborative initiative. Ann Rheum Dis 2010; 69: 1580-8. DOI: https://doi.org/10.1136/ard.2010.138461
Kow J, Lim GH, Tan YK. Applying 28-joint disease activity score (DAS28) and swollen joint count together as single time-point measures better depict rheumatoid arthritis disease status when compared to DAS28 alone: Perspectives from an ultrasound imaging study. Int J Rheum Dis 2023; 26: 581-4. DOI: https://doi.org/10.1111/1756-185X.14526
van Riel PL. The development of the disease activity score (DAS) and the disease activity score using 28 joint counts (DAS28). Clin Exp Rheumatol 2014; 32: S-65-74.
Sole X, Guino E, Valls J, Iniesta R, Moreno V. SNPStats: a web tool for the analysis of association studies. Bioinformatics 2006; 22: 1928-9. DOI: https://doi.org/10.1093/bioinformatics/btl268
Gauderman WJ. Sample size requirements for matched case-control studies of gene-environment interaction. Stat Med 2002; 21: 35-50. DOI: https://doi.org/10.1002/sim.973
Noordzij M, Dekker FW, Zoccali C, Jager KJ. Sample size calculations. Nephron Clin Pract 2011; 118: c319-23. DOI: https://doi.org/10.1159/000322830
Politi C, Roumeliotis S, Tripepi G, Spoto B. sample size calculation in genetic association studies: a practical approach. Life (Basel) 2023; 13: 235. DOI: https://doi.org/10.3390/life13010235
Nishino T, Hashimoto A, Tohma S, Matsui T. Comprehensive evaluation of the influence of sex differences on composite disease activity indices for rheumatoid arthritis: results from a nationwide observational cohort study. BMC Rheumatol 2023; 7: 4. DOI: https://doi.org/10.1186/s41927-023-00328-9
van Vollenhoven RF. Sex differences in rheumatoid arthritis: more than meets the eye. BMC Med 2009; 7: 12. DOI: https://doi.org/10.1186/1741-7015-7-12
Galea S, Tracy M. Participation rates in epidemiologic studies. Ann Epidemiol 2007; 17: 643-53. DOI: https://doi.org/10.1016/j.annepidem.2007.03.013
Dong G, Huang B, Verbeeck J, Cui Y, Song J, Gamalo-Siebers M, et al. Win statistics (win ratio, win odds, and net benefit) can complement one another to show the strength of the treatment effect on time-to-event outcomes. Pharm Stat 2023; 22: 20-33. DOI: https://doi.org/10.1002/pst.2251
Cintado A, Companioni O, Nazabal M, Camacho H, Ferrer A, De Cossio ME, et al. Admixture estimates for the population of Havana City. Ann Hum Biol 2009; 36: 350-60. DOI: https://doi.org/10.1080/03014460902817984
Padyukov L. Genetics of rheumatoid arthritis. Semin Immunopathol 2022; 44: 47-62. DOI: https://doi.org/10.1007/s00281-022-00912-0
Rodriguez-Rodriguez L, Ivorra-Cortes J, Carmona FD, Martin J, Balsa A, van Steenbergen HW, et al. PTGER4 gene variant rs76523431 is a candidate risk factor for radiological joint damage in rheumatoid arthritis patients: a genetic study of six cohorts. Arthritis Res Ther 2015; 17: 306. DOI: https://doi.org/10.1186/s13075-015-0830-z
Suzuki T, Ikari K, Yano K, Inoue E, Toyama Y, Taniguchi A, et al. PADI4 and HLA-DRB1 are genetic risks for radiographic progression in RA patients, independent of ACPA status: results from the IORRA cohort study. PLoS One 2013; 8: e61045. DOI: https://doi.org/10.1371/journal.pone.0061045
Hayashi S, Matsubara T, Fukuda K, Maeda T, Funahashi K, Hashimoto M, et al. A genome-wide association study identifying the SNPs predictive of rapid joint destruction in patients with rheumatoid arthritis. Biomed Rep 2021; 14: 31. DOI: https://doi.org/10.3892/br.2021.1407

How to Cite

Carpio Alvarez, M., Cintado Benitez, A., Diaz Argudin, T., Nodarse Cuni, H., Dominguez Horta, M., & Fernández Massó, J. (2024). Association between <i>COMMD1</i> gene polymorphism rs11125908 and rheumatoid arthritis in the Cuban population. Reumatismo, 76(2). https://doi.org/10.4081/reumatismo.2024.1691