Background: Pancreatic disease is a global problem. Severe acute pancreatitis (AP) carries a 30-50% mortality. Current scoring systems fall short in predictive accuracy, sensitivity, specificity and availability. Pancreatic cancer (PC) is a leading cause of cancer-related mortality, most patients die within one year of diagnosis. Late presentation and lack of effective oncological treatment determine a desperate need to focus on early detection of the pancreatic cancer. Current biomarkers fall short in accessibility, sensitivity and specificity and ability to distinguish malignant from benign conditions. Metabolomics aims to decipher molecular signatures that will distinguish disease from controls, ultimately leading to novel targets for diagnosis and treatment. Initial studies are discovery-based, hypothesis-generating and typically aim to establish a snapshot of the metabolism of an individual by metabolite profile. Aims: Establish a prospective phenotypic and demographic database of patients with acute pancreatitis. Determine urinary and serum metabolomic profiles of AP and PC in comparison to controls and establish if metabolomic profiling can distinguish severity of each disease in order to identify potential novel bio-markers. Methods: Urine and serum samples from 73 AP, 32 PC, 62 Healthy Controls, 8 Chronic pancreatitis and 8 Benign jaundice participants were analysed using GC-MS and UPLCMS. Metabolite identification was subject to univariate and multivariate analysis (p<0.05). Results: The differentiation of metabolite profiles was most distinct with AP. There was no differentiation by AP aetiology. AP severity was distinquished by metabolite profile. Profiles of resectable patients were distinct form non-resectable PC. Fatty acids(FA), glycerophoshocholines, eicosanoids, TCA cycle intermediates and melatonin levels were altered in AP. PC was defined by altered concentrations of FAs, eicosanoids, glycerophoshocholines, sphingomyelins, folates and amino acids and peptides (e.g. glutamine). Altered levels of UFAs, neuromedins, Vitamin D3 determined stage of PC. Conclusion: Urinary and serum metabolomic signatures may provide future biomarker panels for grading AP and PC.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:675589 |
| Date | January 2015 |
| Creators | Ross, Natasha Patrice |
| Publisher | University of Aberdeen |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?pid=228074 |
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