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Efficacy, Safety & Modification of Albuminuria in Type 2 Diabetes Subjects with Renal Disease with LINAgliptin (MARLINA-T2D), a multicentre, multinational, randomized, double-blind, placebo-controlled, parallel-group, phase 3b clinical trial, aims to further define the potential renal effects of dipeptidyl peptidase-4 inhibition beyond glycaemic control. A total of 350 eligible individuals with inadequately controlled type 2 diabetes and evidence of renal disease are planned to be randomized in a 1:1 ratio to receive either linagliptin 5mg or placebo in addition to their stable glucose-lowering background therapy for 24weeks. Two predefined main endpoints will be tested in a hierarchical manner: (1) change from baseline in glycated haemoglobin and (2) time-weighted average of percentage change from baseline in urinary albumin-to-creatinine ratio. Both endpoints are sufficiently powered to test for superiority versus placebo after 24weeks with =0.05. MARLINA-T2D is the first of its class to prospectively explore both the glucose- and albuminuria-lowering potential of a dipeptidyl peptidase-4 inhibitor in patients with type 2 diabetes and evidence of renal disease.
Background
High blood glucose and diabetes are amongst the conditions causing the greatest losses in years of healthy life worldwide. Therefore, numerous studies aim to identify reliable risk markers for development of impaired glucose metabolism and type 2 diabetes. However, the molecular basis of impaired glucose metabolism is so far insufficiently understood. The development of so called 'omics' approaches in the recent years promises to identify molecular markers and to further understand the molecular basis of impaired glucose metabolism and type 2 diabetes. Although univariate statistical approaches are often applied, we demonstrate here that the application of multivariate statistical approaches is highly recommended to fully capture the complexity of data gained using high-throughput methods.
Methods
We took blood plasma samples from 172 subjects who participated in the prospective Metabolic Syndrome Berlin Potsdam follow-up study (MESY-BEPO Follow-up). We analysed these samples using Gas Chromatography coupled with Mass Spectrometry (GC-MS), and measured 286 metabolites. Furthermore, fasting glucose levels were measured using standard methods at baseline, and after an average of six years. We did correlation analysis and built linear regression models as well as Random Forest regression models to identify metabolites that predict the development of fasting glucose in our cohort.
Results
We found a metabolic pattern consisting of nine metabolites that predicted fasting glucose development with an accuracy of 0.47 in tenfold cross-validation using Random Forest regression. We also showed that adding established risk markers did not improve the model accuracy. However, external validation is eventually desirable. Although not all metabolites belonging to the final pattern are identified yet, the pattern directs attention to amino acid metabolism, energy metabolism and redox homeostasis.
Conclusions
We demonstrate that metabolites identified using a high-throughput method (GC-MS) perform well in predicting the development of fasting plasma glucose over several years. Notably, not single, but a complex pattern of metabolites propels the prediction and therefore reflects the complexity of the underlying molecular mechanisms. This result could only be captured by application of multivariate statistical approaches. Therefore, we highly recommend the usage of statistical methods that seize the complexity of the information given by high-throughput methods.
Background: The role of fatty acid (FA) intake and metabolism in type 2 diabetes (T2D) incidence is controversial. Some FAs are not synthesised endogenously and, therefore, these circulating FAs reflect dietary intake, for example, the trans fatty acids (TFAs), saturated odd chain fatty acids (OCFAs), and linoleic acid, an n-6 polyunsaturated fatty acids (PUFA). It remains unclear if intake of TFA influence T2D risk and whether industrial TFAs (iTFAs) and ruminant TFAs (rTFAs) exert the same effect. Unlike even chain saturated FAs, the OCFAs have been inversely associated with T2D risk, but this association is poorly understood. Furthermore, the associations of n-6 PUFAs intake with T2D risk are still debated, while delta-5 desaturase (D5D), a key enzyme in the metabolism of PUFAs, has been consistently related to T2D risk. To better understand these relationships, the FA composition in circulating lipid fractions can be used as biomarkers of dietary intake and metabolism. The exploration of TFAs subtypes in plasma phospholipids and OCFAs and n-6 PUFAs within a wide range of lipid classes may give insights into the pathophysiology of T2D.
Aim: This thesis aimed mainly to analyse the association of TFAs, OCFAs and n-6 PUFAs with self-reported dietary intake and prospective T2D risk, using seven types of TFAs in plasma phospholipids and deep lipidomics profiling data from fifteen lipid classes.
Methods: A prospective case-cohort study was designed within the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam study, including all the participants who developed T2D (median follow-up 6.5 years) and a random subsample of the full cohort (subcohort: n=1248; T2D cases: n=820). The main analyses included two lipid profiles. The first was an assessment of seven TFA in plasma phospholipids, with a modified method for analysis of FA with very low abundances. The second lipid profile was derived from a high-throughout lipid profiling technology, which identified 940 distinct molecular species and allowed to quantify OCFAs and PUFAs composition across 15 lipid classes. Delta-5 desaturase (D5D) activity was estimated as 20:4/20:3-ratio. Using multivariable Cox regression models, we examined the associations of TFA subtypes with incident T2D and class-specific associations of OCFA and n-6 PUFAs with T2D risk.
Results: 16:1n-7t, 18:1n-7t, and c9t11-CLA were positively correlated with the intake of fat-rich dairy foods. iTFA 18:1 isomers were positively correlated with margarine. After adjustment for confounders and other TFAs, higher plasma phospholipid concentrations of two rTFAs were associated with a lower incidence of T2D: 18:1n-7t and t10c12-CLA. In contrast, the rTFA c9t11-CLA was associated with a higher incidence of T2D. rTFA 16:1n-7t and iTFAs (18:1n-6t, 18:1n-9t, 18:2n-6,9t) were not statistically significantly associated with T2D risk.
We observed heterogeneous integration of OCFA in different lipid classes, and the contribution of 15:0 versus 17:0 to the total OCFA abundance differed across lipid classes. Consumption of fat-rich dairy and fiber-rich foods were positively and red meat inversely correlated to OCFA abundance in plasma phospholipid classes. In women only, higher abundances of 15:0 in phosphatidylcholines (PC) and diacylglycerols (DG), and 17:0 in PC, lysophosphatidylcholines (LPC), and cholesterol esters (CE) were inversely associated with T2D risk. In men and women, a higher abundance of 15:0 in monoacylglycerols (MG) was also inversely associated with T2D. Conversely, a higher 15:0 concentration in LPC and triacylglycerols (TG) was associated with higher T2D risk in men. Women with a higher concentration of 17:0 as free fatty acids (FFA) also had higher T2D incidence.
The integration of n-6 PUFAs in lipid classes was also heterogeneous. 18:2 was highly abundant in phospholipids (particularly PC), CE, and TG; 20:3 represented a small fraction of FA in most lipid classes, and 20:4 accounted for a large proportion of circulating phosphatidylinositol (PI) and phosphatidylethanolamines (PE). Higher concentrations of 18:2 were inversely associated with T2D risk, especially within DG, TG, and LPC. However, 18:2 as part of MG was positively associated with T2D risk. Higher concentrations of 20:3 in phospholipids (PC, PE, PI), FFA, CE, and MG were linked to higher T2D incidence. 20:4 was unrelated to risk in most lipid classes, except positive associations were observed for 20:4 enriched in FFA and PE. The estimated D5D activities in PC, PE, PI, LPC, and CE were inversely associated with T2D and explained variance of estimated D5D activity by genomic variation in the FADS locus was only substantial in those lipid classes.
Conclusion: The TFAs' conformation is essential in their relationship to diabetes risk, as indicated by plasma rTFA subtypes concentrations having opposite directions of associations with diabetes risk. Plasma OCFA concentration is linked to T2D risk in a lipid class and sex-specific manner. Plasma n-6 PUFA concentrations are associated differently with T2D incidence depending on the specific FA and the lipid class. Overall, these results highlight the complexity of circulating FAs and their heterogeneous association with T2D risk depending on the specific FA structure, lipid class, and sex. My results extend the evidence of the relationship between diet, lipid metabolism, and subsequent T2D risk. In addition, my work generated several potential new biomarkers of dietary intake and prospective T2D risk.