Biochemistry and Pharmacology - Theses
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ItemThe relationship between the plasma lipidome and cardiovascular disease outcomes in diabetes( 2015)People with T2D have a two-fold increased risk of developing cardiovascular disease (CVD) compared to non-diabetic individuals. However, risk stratification in this group is challenging. Moreover, lifestyle factors i.e. smoking, alcohol consumption and sedentary life style are additional risk factors for CVD. Traditional lipid measurements (elevated cholesterol, triglycerides and/or lowered HDL-C) do not show the full complexity of the altered lipid metabolism associated with T2D or CVD. Lipidomics enables the quantification of hundreds of individual lipid species in biological samples in a single analytical process. Previous lipidomic analyses of plasma have revealed information regarding the pathogenesis of these diseases and identified novel biomarkers for disease diagnosis and risk assessment. In this study, a high throughput extraction method using 1-Butanol:Methanol (1:1, v:v) was developed to facilitate efficient extraction of a wide range of lipids from plasma. The method is fast, simple, uses non-halogenated solvents and is suitable for high throughput liquid chromatography electrospray ionization-tandem mass spectrometry (LC ESI-MS/MS). The method showed high recovery (>90%) and reproducibility (CV% < 20%). The simplicity of the method makes it amenable to an automated approach. Comprehensive lipidomic analysis was then performed on sub-cohort (n=3,779) from the ADVANCE (Action in Diabetes and Vascular disease: preterAx and diamicroN-MR Controlled Evaluation) study in a case/cohort design. The sub-cohort contained 698 participants who had a cardiovascular event (CVE) in the five-year follow-up period. Weighted Cox regression was performed to identify lipid species associated with future CVE, CVD death, stroke and myocardial infarction (MI). Multivariable models containing traditional risk factors with or without lipid species were developed using Cox regression. Features were selected and ranked using the Akaike information criteria. C-statistics, net reclassification index (NRI) and integrated discrimination improvement (IDI), were computed within a 5-fold cross-validation framework (200 iterations) to evaluate the ability of the models to reclassify and discriminate five-year risk. Sphingolipids, phospholipids, sterols and glycerolipids were associated with future CVE (31 species), CVD death (37 species) and stroke (5 species). Compared to base models to predict CVE, CVD death, stroke and MI (incorporating 14, 14, 8 and 10 risk factors, respectively), combined models (11, 15, 14 and 17 lipids and risk factors, respectively) resulted in an increase of C-statistics (0.698 (1.8%), 0.768 (2.8%), 0.766 (18.3%) and 0.707 (7.0%), respectively) and NRIs (5.2%, 13.4%, 13.0% and 10.1%, respectively) based on categorical models of <10, 10-15, and >15% 5-year risk. Finally, logistic regression analyses were performed to identify lipid species associated with smoking, alcohol consumption and exercise that may mediate CVE risk in T2D. The ADVANCE sub-cohort contained (565, 1557 and 1822, participants) of smokers, alcohol consumers and exercise active, respectively. Sphingolipids, phospholipids, sterols and glycerolipids were associated with smoking and alcohol consumption and may represent mediators of disease pathogenesis and so potential therapeutic targets. In summary, these studies improve our understanding of the lipid metabolism associated with CVD risk and the interactions with lifestyle factors in the T2D population. Importantly, we have demonstrated the ability of plasma lipids to improve upon traditional risk factors for the prediction of future CVE and identified potential therapeutic targets to modify that risk.