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Shape variation in modern human upper premolars

Author

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  • Petra G Šimková
  • Lisa Wurm
  • Cinzia Fornai
  • Viktoria A Krenn
  • Gerhard W Weber

Abstract

Morphological variation in modern human dentition is still an open field of study. The understanding of dental shape and metrics is relevant for the advancement of human biology and evolution and is thus of interest in the fields of dental anthropology, as well as human anatomy and medicine. Of concern is also the variation of the inner aspects of the crown which can be investigated using the tools and methods of virtual anthropology. In this study, we explored inter- and intra-population morphometric variation of modern humans’ upper third and fourth premolars (P3s and P4s, respectively) considering both the inner and outer aspects of the crown, and discrete traits. We worked by means of geometric morphometrics on 3D image data from a geographically balanced sample of human populations from five continents, to analyse the shape of the dentinal crown, and the crown outline in 78 P3s and 76 P4s from 85 individuals. For the study of dental traits, we referred to the Arizona State University Dental Anthropology System integrated with more recent classification systems. The 3D shape variation of upper premolar crowns varied between short and mesio-distally broad, and tall and mesio-distally narrow. The observed shape variation was independent from the geographical origin of the populations, and resulted in extensive overlap. We noted a high pairwise correlation (r1 = 0.83) between upper P3s and P4s. We did not find any significant geographic differences in the analysed non-metric traits. Our outcomes thus suggest that geographical provenance does not play a determinant role in the shaping of the dental crown, whose genesis is under strict genetic control.

Suggested Citation

  • Petra G Šimková & Lisa Wurm & Cinzia Fornai & Viktoria A Krenn & Gerhard W Weber, 2024. "Shape variation in modern human upper premolars," PLOS ONE, Public Library of Science, vol. 19(4), pages 1-19, April.
    • Handle: RePEc:plo:pone00:0301482
    DOI: 10.1371/journal.pone.0301482
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    References listed on IDEAS

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    1. J. Gower, 1975. "Generalized procrustes analysis," Psychometrika, Springer;The Psychometric Society, vol. 40(1), pages 33-51, March.
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