School of BioSciences - Research Publications
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ItemMeasures of insulin sensitivity, leptin, and adiponectin concentrations in cats in diabetic remission compared to healthy control cats(FRONTIERS MEDIA SA, 2022-07-29)OBJECTIVES: Firstly, to compare differences in insulin, adiponectin, leptin, and measures of insulin sensitivity between diabetic cats in remission and healthy control cats, and determine whether these are predictors of diabetic relapse. Secondly, to determine if these hormones are associated with serum metabolites known to differ between groups. Thirdly, if any of the hormonal or identified metabolites are associated with measures of insulin sensitivity. ANIMALS: Twenty cats in diabetic remission for a median of 101 days, and 21 healthy matched control cats. METHODS: A casual blood glucose measured on admission to the clinic. Following a 24 h fast, a fasted blood glucose was measured, and blood sample taken for hormone (i.e., insulin, leptin, and adiponectin) and untargeted metabolomic (GC-MS and LC-MS) analysis. A simplified IVGGT (1 g glucose/kg) was performed 3 h later. Cats were monitored for diabetes relapse for at least 9 months (270 days). RESULTS: Cats in diabetic remission had significantly higher serum glucose and insulin concentrations, and decreased insulin sensitivity as indicated by an increase in HOMA and decrease in QUICKI and Bennett indices. Leptin was significantly increased, but there was no difference in adiponectin (or body condition score). Several significant correlations were found between insulin sensitivity indices, leptin, and serum metabolites identified as significantly different between remission and control cats. No metabolites were significantly correlated with adiponectin. No predictors of relapse were identified in this study. CONCLUSION AND CLINICAL IMPORTANCE: Insulin resistance, an underlying factor in diabetic cats, persists in diabetic remission. Cats in remission should be managed to avoid further exacerbating insulin resistance.
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ItemMetabolic Profiling of Diabetic Cats in Remission(FRONTIERS MEDIA SA, 2020-05-15)Background: The majority of diabetic cats in remission have abnormal glucose tolerance, and approximately one third relapse within 1 year. Greater understanding of the metabolic characteristics of diabetic cats in remission, and predictors of relapse is required to effectively monitor and manage these cats. Objectives: To identify and compare differences in plasma metabolites between diabetic cats in remission and healthy control cats using a metabolomics approach. Secondly, to assess whether identified metabolites are predictors of diabetic relapse. Animals: Twenty cats in diabetic remission for a median of 101 days, and 22 healthy matched control cats. Methods: Cats were admitted to a clinic, and casual blood glucose was recorded. After a 24 h fast, blood glucose concentration was measured, then a blood sample was taken for metabolomic (GCMS and LCMS) analyses. Three hours later, a simplified intravenous glucose tolerance test (1 g glucose/kg) was performed. Cats were monitored for diabetes relapse for at least 9 months (270 days) after baseline testing. Results: Most cats in remission continued to display impaired glucose tolerance. Concentrations of 16 identified metabolites differed (P ≤ 0.05) between remission and control cats: 10 amino acids and stearic acid (all lower in remission cats), and glucose, glycine, xylitol, urea and carnitine (all higher in remission cats). Moderately close correlations were found between these 16 metabolites and variables assessing glycaemic responses (most |r| = 0.31 to 0.69). Five cats in remission relapsed during the study period. No metabolite was identified as a predictor of relapse. Conclusion and clinical importance: This study shows that cats in diabetic remission have abnormal metabolism.
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ItemMetabolic profiling of a transgenic Caenorhabditis elegans Alzheimer model(SPRINGER, 2015-04)Despite decades of research, no early-onset biomarkers are currently available for Alzheimer's disease, a cureless neurodegenerative disease afflicting millions worldwide. In this study, transgenic Caenorhabditis elegans were used to investigate changes in the metabolome after induced expression of amyloid-β. GC- and LC-MS-based platforms determined a total of 157 differential features. Some of these were identified using in-house (GC-MS) or public libraries (LC-MS), revealing changes in allantoin, cystathionine and tyrosine levels. Since C. elegans is far better suited to metabolomics studies than most other model systems, the accordance of these findings with vertebrate literature is promising and argues for further use of C. elegans as a model of human pathology in the study of AD.