Study of ischemia-reperfusion induced metabolite changes in porcine kidney model and their potential role in acute kidney injury
Acute kidney injury (AKI) is a common and serious complication in patients undergoing surgery, chronic treatment or kidney transplantation. In AKI patients, the normal functioning of kidneys are suddenly compromised leading to morbidity and mortality. It is reported that annually more than 40,000 in...
| Main Author: | |
|---|---|
| Format: | Thesis (University of Nottingham only) |
| Language: | English English |
| Published: |
2017
|
| Subjects: | |
| Online Access: | https://eprints.nottingham.ac.uk/40642/ |
| Summary: | Acute kidney injury (AKI) is a common and serious complication in patients undergoing surgery, chronic treatment or kidney transplantation. In AKI patients, the normal functioning of kidneys are suddenly compromised leading to morbidity and mortality. It is reported that annually more than 40,000 inpatient deaths and expenditure of one billion pounds by National Health Service (NHS) in England are associated with AKI. There is a critical need to understand the pathophysiology of ischemia-reperfusion induced acute kidney injury and develop biomarkers useful for clinical management of AKI.
In the present study, mass spectrometry based metabolomics approach was employed to investigate the metabolite changes in the kidney tissues of porcine AKI model. To ischemia or reperfusion induced porcine kidneys, two step solvent extraction followed by chromatography separation of metabolites was done prior to mass spectrometric analysis. The mass spectrometric data was generated and processed using IDEOM or Progenesis CoMet software algorithms. Further multivariate and univariate statistical analysis was done using SIMCA or Metaboanalyst software to identify key metabolites associated with Ischemia or reperfusion. Comparative analysis between control, ischemia and reperfusion kidneys revealed altered levels of several metabolites and majority of them belongs to amino acid, lipid and carbohydrate metabolisms. Degradation of several glucogenic and ketogenic amino acids was observed implicating their potential role in ischemia-reperfusion induced acute kidney injury. The combination of high throughput mass spectrometry, bioinformatics and statistical tools resulted in high confidence identification of metabolites and pathways associated with AKI and provide an opportunity for clinical intervention that may help prevent acute kidney injury. |
|---|