Data/hora: 06/06/2024 01:17:39

Provedor de dados: 	74	
País: 	Brazil	
Título: 	Epistasis of polymorphisms related to the articular cartilage extracellular matrix in knee osteoarthritis: Analysis-based multifactor dimensionality reduction	
Autores: 	Fernández-Torres,Javier; Martínez-Nava,Gabriela Angélica; Zamudio-Cuevas,Yessica; Lozada,Carlos; Garrido-Rodríguez,Daniela; Martínez-Flores,Karina.	
Data: 	2020-01-01	
Ano: 	2020	
Palavras-chave: 	Epistasis; Extracellular matrix; Knee osteoarthritis; Multifactor dimensionality reduction; Polymorphisms.	
Resumo: 	Abstract 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.	
Tipo: 	Info:eu-repo/semantics/article	
Idioma: 	Inglês	
Identificador: 	http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572020000400102	
Editor: 	Sociedade Brasileira de Genética	
Relação: 	10.1590/1678-4685-gmb-2018-0349	
Formato: 	text/html	
Fonte: 	Genetics and Molecular Biology  v.43 n.2 2020	
Fonte: 	info:eu-repo/semantics/openAccess