Date of Award

Spring 4-24-2018

Degree Type

Thesis

Department

Psychology

First Advisor

Jessica Turner

Abstract

In previous research, Gupta et al. (2015) analyzed gray matter density as well as volume reductions related to schizophrenia in the region of the insula and medial prefrontal cortex. Sprooten et al. (2015) then identified a set of quantitative trait loci (QTLs), which is a region of DNA associated with variability in these gray matter concentration patterns. The aim of this study is to examine the QTL they found in a region of chromosome 5. We hypothesized that there will be a set of genes in the QTL on chromosome 5 that is related to abnormal brain patterns in potential disorders such as schizophrenia. We identified genes present in the region of the QTL to analyze their function and relatedness to other genes using various software like Ingenuity Pathways Analysis, and Gene Cards. We evaluated their biological functions as well as any related disorders. For the imaging and genetic analyses, the genotypic data contained 9,228 single-nucleotide polymorphisms (SNPs) from shared aggregated datasets. The datasets contained clinical information for 616 subjects (364 controls, 252 cases). Each subject had a corresponding brain image. We identified a set of genes, including SLC1A3, GDNF, C6, C7, and C9, that are possibly related to neurodegeneration as well as brain injury processes. Lastly, we employed the parallel independent component analysis technique (pICA) to incorporate the genetic data with brain imaging to possibly identify an area related to schizophrenia. Some of the genetic variations found corresponded to the genes C7, RPL37, and PTGER4 with a correlation of 0.1012. C7, RPL37, and PTGER4 are involved in the immune system, multiple sclerosis, and neurodegenerative diseases. These genes were correlated with the imaging pattern from the pICA in the regions of the cerebellum, vermis, and mid-temporal lobe. Further analyses are needed to evaluate the correlation obtained from the pICA.

DOI

https://doi.org/10.57709/12015889

Download

Share

COinS