Epistasis of polymorphisms related to the articular cartilage extracellular matrix in knee osteoarthritis: Analysis-based multifactor dimensionality reduction.
Javier Fernández-TorresGabriela Angélica Martínez-NavaYessica Zamudio-CuevasCarlos LozadaDaniela Garrido-RodríguezKarina Martínez FloresPublished in: Genetics and molecular biology (2020)
Osteoarthritis (OA) is a complex disease with a multifactorial etiology. The genetic component is one of the main associated factors, resulting from interactions between genes and environmental factors. The aim of this study was to identify gene-gene interactions (epistasis) of the articular cartilage extracellular matrix (ECM) in knee OA. Ninety-two knee OA patients and 147 healthy individuals were included. Participants were genotyped in order to evaluate nine variants of eight genes associated with ECM metabolism using the OpenArray technology. Epistasis was analyzed using the multifactor dimensionality reduction (MDR) method. The MDR analysis showed significant gene-gene interactions between MMP3 (rs679620) and COL3A1 (rs1800255), and between COL3A1 (rs1800255) and VEGFA (rs699947) polymorphisms, with information gain values of 3.21% and 2.34%, respectively. Furthermore, in our study we found interactions in high-risk genotypes of the HIF1AN, MMP3 and COL3A1 genes; the most representative were [AA+CC+GA], [AA+CT+GA] and [AA+CT+GG], respectively; and low-risk genotypes [AA+CC+GG], [GG+TT+GA] and [AA+TT+GA], respectively. Knowing the interactions of these polymorphisms involved in articular cartilage ECM metabolism could provide a new tool to identify individuals at high risk of developing knee OA.
Keyphrases
- knee osteoarthritis
- extracellular matrix
- genome wide
- pet ct
- copy number
- genome wide identification
- end stage renal disease
- dna methylation
- computed tomography
- genome wide analysis
- multidrug resistant
- chronic kidney disease
- image quality
- newly diagnosed
- healthcare
- magnetic resonance imaging
- rheumatoid arthritis
- contrast enhanced
- transcription factor
- gene expression
- dual energy
- cross sectional