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Endocrine Abstracts (2016) 44 OC1.4 | DOI: 10.1530/endoabs.44.OC1.4

1Oxford Centre for Diabetes, Endocrinology & Metabolism, University of Oxford, Oxford, UK; 2Centre for Endocrinology, Diabetes & Metabolism, University of Birmingham, Birmingham, UK; 3Centre for Liver Research, University of Birmingham, Birmingham, UK; 4University of Antwerp, Antwerp, Belgium; 5University of Groningen, Groningen, The Netherlands.


Introduction: Dysregulation of glucocorticoid (GC) metabolism is implicated in the pathogenesis of non-alcoholic fatty liver disease (NAFLD). The only available treatment for NAFLD is weight loss and the gold standard diagnostic test is liver biopsy, which is invasive and resource intensive. NAFLD ranges from simple steatosis, to inflammation (steatohepatitis/NASH), fibrosis and cirrhosis. It may be regarded as the hepatic manifestation of the metabolic syndrome and is strongly associated with increased cardiovascular mortality. Changes to GC metabolism, thus far described in small numbers of patients, relate to the metabolism of cortisol. 11β-hydroxysteroid dehydrogenase type 1 (11β-HSD1) regenerates cortisol (F) from inactive cortisone (E), whilst A-ring reductases 5α and 5β reductase (5αR/5βR) inactivate cortisol to tetrahydrocortisol metabolites (THF/5αTHF).

Methods: Using gas chromatography / mass spectrometry, we analysed steroid metabolites in spot urine samples (corrected for creatinine) in a large cohort of patients with biopsy proven NASH (n=39) alongside patients with cirrhosis (n=44), and compared them to healthy controls without liver disease (n=58).

Results: Total cortisol metabolites differed significantly across all 3 groups allowing discrete separation (P<0.0001) with the highest levels seen in patients with NASH. Interestingly, 11β-HSD1 activity (THF+5αTHF/THE ratio) was significantly increased in patients with cirrhosis in comparison to NASH or healthy controls (P<0.0001). A-ring reductase activity (THF/5αTHF ratio) was not significantly different between the 3 groups. Furthermore, machine learning-based analysis by generalised matrix learning vector quantisation (GMLVQ) achieved complete separation of control and cirrhosis groups (AUC ROC: 0.99).

Conclusion: Our work has identified steroid metabolic pathways that appear differentially regulated across the spectrum of NAFLD and has the potential to lead to the identification of as yet unidentified treatment targets. Additionally, through the adoption of an unbiased computational (GMLVQ) approach, we have raised the potential to use this technique as a novel, non-invasive assessment to stage the severity of NAFLD.

Volume 44

Society for Endocrinology BES 2016

Brighton, UK
07 Nov 2016 - 09 Nov 2016

Society for Endocrinology 

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