Abstract

Morphological integration refers to the interdependence of two or more phenotypic structures. The morphological integration concept is based on the fact that parts of complex organisms do not vary randomly and instead display degrees of non-independence that are thought to occur from shared genetic or developmental origins, and/or functional demands. Integrated traits may develop, evolve, and be inherited together. One instance of morphological integration can be found between the vertebral column and the skull. Due to the position of the skull resting atop of the vertebral column, posture may influence skull development and overall craniofacial morphology. Morphological integration within or between structures is typically statistically assessed by exploring correlation and covariation patterns among biological structures of interest. In this study, an analysis of morphological integration was carried out by studying covariation of morphometric measures from the vertebral column and craniofacial complex. Age- and sex-matched, de-identified computed tomography images of individuals with kyphosis spinal malformation (n = 15) and controls (n = 19) were acquired from Florida Hospital. It is hypothesized that the sample of individuals with kyphosis will exhibit statistically significant covariance differences relative to the control group for T6 vertebral and midfacial linear distance measurements. Anatomical landmarks were identified on the T6 thoracic vertebrae (n = 6) and the midfacial skeleton (n = 6), and XYZ coordinates were recorded for analysis. A subset of 10 individuals (5 kyphosis, 5 controls) individuals were measured on two occasions to assess reliability and measurement error. An Euclidean Distance Matrix Analysis (EDMA) of morphological integration was carried out on the entire sample by calculating correlation values for paired linear distance measurements (one vertebral and one midfacial) separately for the kyphosis and control samples (n = 225 for each sample). Next, EDMA calculated correlation differences and statistically assessed significance using a non-parametric bootstrap (1,000 resamples) and confidence interval testing (α ≤ 0.10). Only 35 of the 225 (15.56%) correlation differences were statistically significant. Patterns of variation among these significant correlation differences were explored by examining sample directionality of differences, sign patterns, and strengths. The relevance of these results to clinical and anthropological pursuits are discussed. Several recommendations for future investigations are made.

Thesis Completion

2018

Semester

Spring

Thesis Chair/Advisor

Starbuck, John

Degree

Bachelor of Science (B.S.)

College

College of Sciences

Department

Anthropology

Location

Orlando (Main) Campus

Language

English

Access Status

Open Access

Release Date

5-1-2018

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