Abstract
Articular cartilage is an avascular tissue with a structure that allows it to support and cushion the overload of the surfaces in contact. It maintains its metabolic functions due to the contribution of different signaling pathways. However, several factors play a role in its deterioration, allowing to the development of osteoarthritis (OA), and one of the major factors is genetic. Our goal was to identify gene–gene interactions (epistasis) between five signaling pathways involved in the articular cartilage metabolism as possible indicators of OA risk. We applied the Multifactor-Dimensionality Reduction (MDR) method to identify and characterize the epistasis between 115 SNPs located in 73 genes related to HIF-1α, Wnt/β-catenin, cartilage extracellular matrix metabolism, oxidative stress, and uric acid transporters. Ninety three patients diagnosed with primary knee OA and 150 healthy controls were included in the study. Genotyping was performed with the OpenArray system, the statistical analysis was carried out with the STATA software v14, and epistasis was analyzed with the MDR software v3.0.2. The MDR analysis revealed that the best interaction model was between polymorphisms rs17786744 of the STC1 gene and rs2615977 of the COL11A1 gene, with an entropy value of 4.44%, CVC 8/10, OR 5.60, 95% CI 3.27–9.59, p < 0.0001. Under this interaction model, we identified high and low risk genotypes involved in OA development. Our results suggest complex interactions between STC1 and COL11A1 genes that might have an impact on genetic susceptibility to develop OA. Further studies are required to confirm it.
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Fernández-Torres, J., Martínez-Nava, G.A., Zamudio-Cuevas, Y. et al. Multifactor dimensionality reduction reveals a strong gene–gene interaction between STC1 and COL11A1 genes as a possible risk factor of knee osteoarthritis. Mol Biol Rep 47, 2627–2634 (2020). https://doi.org/10.1007/s11033-020-05351-4
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DOI: https://doi.org/10.1007/s11033-020-05351-4