Please use this identifier to cite or link to this item:
|Title:||Identifying DNA Methylation Patterns as Novel Urinary Biomarkers for Kidney Function|
|Keywords:||DNA Methylation;Kidney Function|
|Abstract:||Chronic kidney disease (CKD) is a major public health concern, characterized by an irreversible reduction in renal function. Currently, creatinine-based GFR estimation is predominantly used clinically to characterize CKD. However, this method is known to be an insensitive test for early losses of kidney function. Since patient prognosis relies heavily on slowing further decline of kidney function, uncovering novel biomarkers for kidney function, in conjunction with eGFR, will help improve patient outcome. Epigenetic-based biomarkers have been identified in numerous cancers, as DNA methylation changes alter cellular function. Thus, the objective of this study is to determine novel DNA methylation patterns reflecting altered kidney function. Five healthy participants that have undergone a nephrectomy have donated urine samples before and after their surgery, and global DNA methylation changes were analyzed through the 450K HumanMethylation microarray. Site- and region-level analyses were conducted to determine significant differentially methylated probes post-nephrectomy. The differential associations observed post-nephrectomy are statistically significant in both the site-level and regional analyses. Nineteen significant candidate probes have been systematically selected for validation, based on involvement in kidney function and consistent direction of methylation. Pyrosequencing assays have also been successfully designed and tested with control DNA, however replication of the microarray findings in participant DNA was unsuccessful. The inability to validate these candidate probes may be attributed to many influencing factors, and with this in mind, uncovering novel methylation patterns is still a promising biomarker for evaluating kidney function.|
|Appears in Collections:||Open Access Dissertations and Theses|
Files in This Item:
|Ranya Hasso - Final Masters thesis.pdf||Thesis||1.59 MB||Adobe PDF||View/Open|
Items in MacSphere are protected by copyright, with all rights reserved, unless otherwise indicated.