Publication Details

AFRICAN RESEARCH NEXUS

SHINING A SPOTLIGHT ON AFRICAN RESEARCH

medicine

Quantifying linear enamel hypoplasia in Virunga Mountain gorillas and other great apes

American Journal of Physical Anthropology, Volume 166, No. 2, Year 2018

Objective: Linear enamel hypoplasia (LEH) is a condition marked by localized reductions in enamel thickness, resulting from growth disruptions during dental development. We use quantitative criteria to characterize the depth of LEH defects and “normal” perikymata in great apes. We test the hypothesis that mountain gorillas have shallow defects compared to other taxa, which may have led to their underestimation in previous studies. Materials and Methods: Previous attempts to characterize LEH morphology quantitatively have been limited in sample size and scope. We generated digital elevation models using optical profilometry (Sensofar PLu Neox) and extracted 2D coordinates using ImageJ to quantify depths in canines from three great ape genera (N = 75 perikymata; 255 defects). Results: All defect depths fall outside the distribution of perikymata depths. Mountain gorilla defects are significantly shallower than those of other great ape taxa examined, including western lowland gorillas. Females have significantly deeper defects than males in all taxa. The deepest defect belongs to a wild-captured zoo gorilla. Virunga mountain gorilla specimens collected by Dian Fossey exhibit deeper defects than those collected recently. Discussion: Shallow defect morphology in mountain gorillas may have led to an underestimation of LEH prevalence in past studies. Defect depth is used as a proxy for insult severity, but depth might be influenced by inter- and intra-specific variation in enamel growth. Future studies should test whether severe insults are associated with deeper defects, as might be the case with Haloko, a wild-captured gorilla. Ongoing histologic studies incorporating associated behavioral records will test possible factors that underlie differences in defect morphology.
Statistics
Citations: 28
Authors: 9
Affiliations: 7
Identifiers
Research Areas
Health System And Policy
Study Design
Cross Sectional Study
Study Approach
Quantitative
Participants Gender
Female