Kidney biopsy is the current gold standard diagnostic test for intrinsic renal disease but requires hospital admission and carries a 3% risk of major complications. Current non-invasive prognostic indicators such as urine protein quantification have limited predictive value. Better diagnostic and prognostic tests for chronic kidney disease (CKD) patients are therefore a major focus for industry and academia. An alternative approach is the quantification of urinary microRNAs(miRNAs): short, non-coding RNAs that regulate gene expression posttranscriptionally. This project investigated the utility of urinary miRNA expression analysis as a method for non-invasive diagnostic/prognostic testing for CKD. A technique was developed for quantifying miRNAs in urine samples from control subjects and diabetic nephropathy (DN) patients with a coefficient of variation below 10%. The stability of endogenous miRNAs was demonstrated in urine samples from unaffected individuals and DN patients. Two populations of urinary miRNAs were identified: those associated with exosomes and those associated with AGO2, a component protein of the RNA-induced silencing complex. Expression of over 750 urinary miRNAs in pooled urine samples from DN patients was compared with that in corresponding control samples using TaqMan Array Human microRNA Card analysis. Statistically significant differences in expression of a subset of putative disease-associated miRNAs were then replicated in individual urine samples, and these data were supported by ROC curve analyses. Expression analysis of these target miRNAs in defined nephron segments was observed using laser capture microdissection of renal biopsy tissues followed by miRNA detection by RT-qPCR. Subsequent renal cell line analysis pinpointed miRNA cellular origins, and miRNA release into conditioned tissue culture medium in response to disease stimuli was also observed. These experimental data reveal a pattern of urinary miRNA expression changes in DN and present putative mechanisms by which these differences in abundance might come about.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:633560 |
| Date | January 2014 |
| Creators | Beltrami, Cristina |
| Publisher | Cardiff University |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://orca.cf.ac.uk/68643/ |
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