Masters Theses

Keywords and Phrases

Brain; Genetics; Injury; Statistical; TBI; Traumatic

Abstract

"Traumatic brain injury (TBI) is a growing health concern, with millions of TBI diagnoses in the United States each year. The vast majority of TBI diagnoses are mild traumatic brain injuries (mTBI), which can be challenging to manage due to variation in symptoms and outcomes. Most individuals with mTBI successfully recover quickly, but a small subset has a delayed recovery. Although the factors that contribute to this variation in recovery are not clearly understood, it is possible that genetic differences may play a role. Very few studies have investigated the association between single nucleotide polymorphisms (SNPs) with mTBI outcomes and this is an emerging area of research. In this study, we utilize data collected in the Transforming Research and Clinical Knowledge in Traumatic Brain Injury Pilot (TRACK-TBI Pilot) study to test the association between 10 different SNPs and 7 TBI outcomes measured at six- and twelve-months post injury. Linear mixed models are utilized to investigate the association between genotypes and mTBI outcome measurements over time. Previous studies have primarily focused on a single time point at six months for one or two SNPs. This study seeks to expand the existing literature by using the TRACK-TBI Pilot data to evaluate multiple SNPs and multiple outcome assessments to discover their connections over time. The findings in this study demonstrate the potential benefits of using linear mixed models to identify relationships between genotypes and TBI outcomes over time"--Abstract, p. iv

Advisor(s)

Olbricht, Gayla R.

Committee Member(s)

Obafemi-Ajayi, Tayo
Samaranayake, V. A.

Department(s)

Mathematics and Statistics

Degree Name

M.S. in Applied Mathematics

Publisher

Missouri University of Science and Technology

Publication Date

Spring 2023

Pagination

x, 74 pages

Note about bibliography

Includes bibliographical references (pages 69-73)

Rights

© 2023 Caroline Elizabeth Claire Schott, All Rights Reserved

Document Type

Thesis - Open Access

File Type

text

Language

English

Thesis Number

T 12260

Electronic OCLC #

1426307566

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