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Sub-clustering in skeletal class III malocclusion phenotypes via principal component analysis in a southern European population

de Frutos-Valle, L ; Martin, C ; Alarcón, J A ; Palma-Fernández, J C ; Ortega, R ; Iglesias-Linares, A

Scientific reports, 2020-10, Vol.10 (1), p.17882-17882, Article 17882 [Periódico revisado por pares]

England: Nature Publishing Group

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  • Título:
    Sub-clustering in skeletal class III malocclusion phenotypes via principal component analysis in a southern European population
  • Autor: de Frutos-Valle, L ; Martin, C ; Alarcón, J A ; Palma-Fernández, J C ; Ortega, R ; Iglesias-Linares, A
  • Assuntos: Adolescent ; Adult ; Cephalometry ; Cluster Analysis ; Europe ; Female ; Humans ; Male ; Malocclusion, Angle Class III - diagnostic imaging ; Mandible - diagnostic imaging ; Maxilla - diagnostic imaging ; Minority & ethnic groups ; Phenotype ; Phenotypes ; Phenotypic variations ; Principal Component Analysis ; Principal components analysis ; Radiography ; Young Adult
  • É parte de: Scientific reports, 2020-10, Vol.10 (1), p.17882-17882, Article 17882
  • Notas: ObjectType-Article-1
    SourceType-Scholarly Journals-1
    ObjectType-Feature-2
    content type line 23
  • Descrição: The main aim of this study was to generate an adequate sub-phenotypic clustering model of class III skeletal malocclusion in an adult population of southern European origin. The study design was conducted in two phases, a preliminary cross-sectional study and a subsequent discriminatory evaluation by main component and cluster analysis to identify differentiated skeletal sub-groups with differentiated phenotypic characteristics. Radiometric data from 699 adult patients of southern European origin were analyzed in 212 selected subjects affected by class III skeletal malocclusion. The varimax rotation was used with Kaiser normalization, to prevent variables with more explanatory capacity from affecting the rotation. A total of 21,624 radiographic measurements were obtained as part of the cluster model generation, using a total set of 55 skeletal variables for the subsequent analysis of the major component and cluster analyses. Ten main axes were generated representing 92.7% of the total variation. Three main components represented 58.5%, with particular sagittal and vertical variables acting as major descriptors. Post hoc phenotypic clustering retrieved six clusters: C1:9.9%, C2:18.9%, C3:33%, C4:3.77%, C5:16%, and C6:16%. In conclusion, phenotypic variation was found in the southern European skeletal class III population, demonstrating the existence of phenotypic variations between identified clusters in different ethnic groups.
  • Editor: England: Nature Publishing Group
  • Idioma: Inglês
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