Date of Award

6-30-2017

Document Type

Restricted Access Thesis

Degree Name

Master of Science in Biology

Department

Department of Biological Sciences

Thesis Advisor

Heather E. Doherty

Committee Member

Christopher C. Chabot

Committee Member

Brigid C. O’Donnell

Committee Member

Susan K. Swope

Abstract

Organ fibrosis is a major contributor to morbidity and mortality in the United States, and there are no FDA­approved treatments for it. It is characterized by thickening and scarring of tissues and is a shared endpoint of many common conditions that affect the heart, liver, lungs, kidneys, intestines, and skin. Fibrosis develops during the wound healing process due to the excess deposition of extracellular matrix (ECM) proteins by fibroblast cells. Organ fibrosis impairs tissue function and can lead to organ failure. There is no evidence that fibrosis in humans can be reversed once it has occurred, so its prevention may be the only reliable method of reducing fibrosis-related morbidity and mortality. Additionally, fibrosis risk is variable within the population and methods of identifying those in need of treatment will be required. The connective tissue growth factor (CTGF) gene is overexpressed during fibrosis in many organs, and single nucleotide polymorphisms (SNPs) in the gene’s promoter have been identified as risk factors for fibrotic disease. Reducing expression of CTGF has been proposed as a method of decreasing fibrosis risk or severity. CTGF belongs to the CCN family of genes that influence fibrosis-related cellular functions, and several are associated with fibrotic diseases. However, the fibrosis­related effects of coding SNPs in CTGF or other CCN genes have not been reported. We used targeted resequencing, population genetics, and in silico analyses to discover and investigate the potential role of nonsynonymous SNPs in CTGF and other CCN family genes. In our sample population from Plymouth State University, we identified 17 CTGF SNPs. Six of the SNPs were novel, suggesting the published list of variants is not comprehensive. One SNP, G1355T, was common in our population and associated with a decreased family history score for cardiovascular disease. In our in silico analyses, we categorized the nonsynonymous SNPs from our sample population and all published CCN SNPs into risk categories. Five of the SNPs identified in our sample population were categorized as high-risk including the G1355T SNP. Of the 872 published SNPs in CCN family genes, 174 were classified as high-risk, and 26 were predicted to be at greatest risk of significantly impacting CCN protein structure or function. The highest-risk SNPs, base changes that occur in functional protein regions, and SNPs already associated with disease are excellent targets for in vitro or large-scale studies. The identification of SNPs that alter one’s risk of developing fibrosis could be used in the future to identify those most likely to benefit from anti-fibrotic treatments.

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Rights Statement

In Copyright