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dc.contributor.advisorMellanby, Richard
dc.contributor.advisorConway, Bryan
dc.contributor.advisorHughes, Jeremy
dc.contributor.authorArmstrong, Susan
dc.date.accessioned2021-12-16T14:53:30Z
dc.date.available2021-12-16T14:53:30Z
dc.date.issued2021-12-08
dc.identifier.urihttps://hdl.handle.net/1842/38365
dc.identifier.urihttp://dx.doi.org/10.7488/era/1630
dc.description.abstractBACKGROUND: Chronic kidney disease (CKD) is a major cause of morbidity and mortality in humans, dogs and cats. These three species share many commonalities in pathophysiology. A wide range of diagnostic tests have been developed and validated to identify renal insufficiency as a result of nephron compromise and loss. However, there is increasing evidence that the sensitivities and specificities of many widely used diagnostic CKD tests are suboptimal. This highlights the need to develop better biomarkers of renal disease which have a true clinical high-throughput application. Urinary extracellular vesicles (uEVs) have become a major focus of CKD biomarker research in recent years. In health and disease, urinary exosomes (~20-150nm) and microvesicles (30-1000nm), collectively referred to as urinary EVs (uEVs), are released from renal cells into urine. They are believed to be reflective of the status of the entire renal system, carrying markers of parent cells on their surface, and translational proteins within the uEVs. Despite their potential promise as a novel disease biomarker, little is definitively known about their diagnostic utility in human renal disorders and they have not been meaningfully studied in companion animals. This is in part due to a lack of technological resolution and standardisation across the tools that are available for uEV analysis. Harnessing the diagnostic utility of uEVs would allow serial measurements acting somewhat like a ‘non-invasive biopsy’ and would be an important contribution to the field of nephrology. This study aimed to further validate the role of uEVs in humans with chronic renal disease and characterise and investigate urinary uEVs in dogs and cats with renal disease using advanced technology to enumerate and define surface phenotypic markers, in conjunction with analysis of a urinary miRNA, miR-21. Methods: Urinary EVs from healthy individuals of all three species were characterised using real time-PCR, Western-Blots, dot-blots and transmission electron-microscopy. A panel of renal damage markers in canine and feline renal tissue was developed using immunohistochemistry (IHC). This also served to assess cross reactivity of antibodies between species. NanoSight tracking analysis was used for enumeration of uEVs across species in health and disease, as was flow cytometry. Flow cytometry also allowed for interrogation of uEV phenotypes in a clinically applicable high-throughput manner. An imaging flow cytometer was then used to corroborate findings by gaining both a fluorescent signal and a brightfield image for particles >300nm. Exosomal micro-RNA 21 in urine and serum was analysed in healthy dogs and cats and dogs and cats with CKD by PCR. RESULTS: uEVs in canine and feline urine were morphologically and phenotypically characterised. uEVs in the cat and dog express similar surface proteins, which were detected by human antibodies. Enumeration of uEVs (20- 150nm) was performed in minimally processed healthy control urine. Centrifugation improved repeatability of urinary uEVs measurement, and one freeze thaw did not have any significant effect on uEV concentration or size when compared with fresh urine. A cohort of homogenous dogs with histopathologically assessed renal tissue, were used to further validate the repeatability of the NanoSight. A repeat sampling study was then conducted in both healthy dogs and cats. It was determined that the uEV concentration and size was similar over three days in both species and a 95% reference range was calculated. A difference in uEV concentration between healthy individuals and patients with chronic renal disease was then elucidated in the 150-250nm uEV size range when corrected for urinary creatinine. Investigation of a large human CKD cohort importantly revealed that uEV number was unaffected irrespective of the level of proteinuria. Patients with diabetic nephropathy (DN) had significantly more uEVs in the 150-250nm, but uEV number was not a predictor of disease in relation to eGFR when assessed over three years of patient follow up. A new correction factor, ratio of Area Under the Curve (AUC) <150nm/ AUC =>150nm was tested against creatinine and USG which showed poorer agreement between samples and will require further mathematical modelling to assess its validity. Dedicated flow cytometry and cutting edge imaging flow cytometry were used to study potential surface phenotypic biomarkers of uEVs using a panexosomal marker in conjunction with fluorescently labelled antibodies including podocalyxin, Kidney injury molecule-1 (KIM-1) and Aquaporin 2 (AQP2). Robust methods for reliable analysis of minimally processed uEVs by flow cytometer (FCM) were developed in healthy urine from all three species to ensure accurate resolution, quantification and standardisation of analysis. Following optimisation of the analysis protocols, uEVs were then assessed in healthy individuals of all species and those with CKD. Finally miR-21 was assessed in urine and serum of healthy animals and in those with CKD. Data from a small cohort of dogs indicates that miR-21 may be increased in serum of dogs suffering from CKD. CONCLUSION: This body of work demonstrated that canine and feline uEVs share many features of human uEVs. In addition, uEVs can be reliably and repeatedly enumerated by NTA in humans, dogs and cats. No evidence was found that uEVs differ between canine and feline health individuals and patients with CKD. Furthermore, no evidence was found that uEVs profiles were prognostically informative in humans with CKD. Finally, data was presented which shows preliminary evidence that urinary microRNA profiles may be diagnostically informative. This body of work provides a wide range of novel information which will guide the development of future CKD diagnostic assay development. Future work should focus on machine learning for elucidating if uEVs are predictors of renal outcome and interrogating further microRNA targets in larger patient cohorts.en
dc.description.abstract2022-12-08en
dc.language.isoenen
dc.publisherThe University of Edinburghen
dc.subjectRenal diseaseen
dc.subjectCKDen
dc.subjectUrinary extracellular vesiclesen
dc.subjectNanoparticle tracking analysisen
dc.titleCharacterisation and investigation of urinary extracellular vesicles as translational diagnostic biomarkers in companion animals and humans with chronic kidney diseaseen
dc.typeThesis or Dissertationen
dc.type.qualificationlevelDoctoralen
dc.type.qualificationnamePhD Doctor of Philosophyen
dc.rights.embargodate2022-12-08en
dcterms.accessRightsRestricted Accessen
dcterms.accessRightsen


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