Aldosterone Hypothesis for Cognitive Impairment in Diabetes Mellitus

Increased plasma aldosterone concentration is significantly associated with dementia, which is accentuated by diabetes mellitus (DM). Angiotensin II (AngII) deteriorates cognitive function through neuronal degradation. Lipoproteins, a major source of cholesterol for aldosterone biosynthesis, undergo glycoxidative modifications in the presence of hyperglycemia. We hypothesize that there would be a pathophysiological link between diabetically-modified lipoproteins, angiotensin II, and increased plasma aldosterone concentration for induction of cognitive impairment. Glycoxidized lipoproteins produce significantly more aldosterone from AngII-sensitized adrenocortical cells compared to their native counterparts. The elucidation of signaling mechanisms revealed that modified lipoproteins follow the similar signaling mechanism like AngII for adrenocortical aldosterone release via ERK1/2 and Janus kinase-2 (Jak-2)-mediated pathways. The enhanced aldosterone release from AngII-sensitized adrenocortical cells induced by glycoxidatively modified lipoproteins may play a crucial role in cognitive dysfunction in diabetic individuals along with AngII via a prevailing mode of signaling cascade involving ERK1/2- and Jak-2-dependent pathways

Long-term follow-up of circulating oxidative stress markers in patients undergoing lipoprotein apheresis by Direct Adsorption of Lipids (DALI)

OBJECTIVE: Beyond its well-established efficacy in lowering atherogenic lipids and lipoproteins, DALI (Direct Adsorption of Lipids) apheresis has been shown to have acute anti-inflammatory and endothelium-protective effects. In the present study, we investigated long-term effects of DALI procedures on circulating oxidative stress markers. METHODS: Thirteen patients involved in the study underwent regular DALI apheresis for nearly two years. At sessions 1, 40 and 80 conventional lipid status and changes of systemic oxidative stress markers (oxidized LDL, anti-oxidized LDL antibodies, advanced oxidation protein products (AOPP), and myeloperoxidase (MPO)) were examined. RESULTS: DALI procedure efficiently reduced atherogenic lipids/lipoproteins. On day three after apheresis lipid parameters returned to pre-apheresis values. They showed no tendency to increase or to decrease over time. No significant differences were found between 1st, 40th and 80th sessions. In a similar way, levels of oxidative stress biomarkers acutely decreased after apheresis sessions and rebounded on day three after apheresis. No significant differences were observed between sessions 1, 40, and 80. CONCLUSION: DALI apheresis repeatedly decreases atherogenic lipid/lipoprotein profile and oxidative stress biomarker levels during each session. Among all investigated parameters no longitudinal effects over two years could be observed

Association between systemic oxidative stress and insulin resistance/sensitivity indices - the PREDIAS study

OBJECTIVE Systemic oxidative stress has been causally related to insulin resistance and the subsequent development of type 2 diabetes mellitus (T2D). We investigated associations between circulating oxidative stress markers and different surrogate indexes of insulin sensitivity/resistance. PATIENTS Cross-sectional data were obtained from 1183 subjects with normal glucose tolerance (NGT), 280 subjects with impaired glucose tolerance (IGT) and 69 newly detected T2D individuals entering the PREDIAS (prevention of diabetes) study. MEASUREMENTS Following oral glucose tolerance test, five different insulin sensitivity/resistance indices were estimated: homoeostasis model of insulin resistance (HOMA-IR), quantitative insulin sensitivity check index (QUICKI), early phase insulin release (EPIR), insulin sensitivity index (ISI) and disposition index (DI). Additionally, circulating phagocyte generation of reactive oxygen species (ROS) and plasma total antioxidant capacity (TAC) was measured. RESULTS After adjustment for five covariates, HOMA-IR was significantly increased in IGT and T2D subjects when compared to NGT subjects (P = 0·000). QUICKI (P = 0·000), ISI (P = 0·000), EPIR (0·005/0·012) and DI (P = 0·000) were significantly attenuated in IGT and T2D. The prevalence of IGT and T2D individuals increased with increasing ROS generation and TAC tertiles. Increased systemic ROS generation was paralleled by increased HOMA-IR (P < 0·001, tertile 1/T1/vs tertile 3/T3/), decreased QUICKI (P < 0·001, T1 vs T3) and decreased ISI (P < 0·05, T1 vs T3). A similar tendency for indices was observed when comparing TAC tertiles: increase in HOMA-IR, decrease in QUICKI and ISI (P < 0·001, T1 vs T3 each). EPIR and DI did not differ significantly across ROS generation and TAC tertiles. CONCLUSIONS Systemic oxidative stress is associated with elevated insulin resistance index HOMA-IR, and decreased insulin sensitivity surrogates QUICKI and ISI

Type 2 Diabetes in Octogenarians Is Associated with Decreased Low Molecular Weight Adiponectin

Background: Adiponectin circulates in the blood in three different multimer isoforms, of which the high molecular weight form (HMW) is presumed to mediate insulin sensitivity. We examined whether adiponectin oligomer distribution is associated with aging and type 2 diabetes (T2D) in octogenarians without characteristic features of metabolic syndrome. Methods: The study included 154 octogenarians (58 men, 96 women), 24 normoglycemic middle-aged controls (11 men, 13 women; mean age 44 years), and 33 middle-aged individuals (14 men, 19 women; mean age 55 years) with T2D. Based on oral glucose tolerance test 62 octogenarians had normal, 63 impaired glucose tolerance, and 29 octogenarians had newly detected T2D. Serum adiponectin multimer isoforms were measured after overnight fast by enzyme-linked immunosorbent assays. Results:Compared to the normoglycemic middle-aged control group, male normoglycemic octogenarians revealed significantly higher total adiponectin and all adiponectin isoforms. The same was true for females with the exception of low molecular weight (LMW) adiponectin, which was not statistically higher in octogenarians. Male and female octogenarians with T2D had significantly higher levels of total, HMW, and middle molecular weight (MMW) adiponectin, but not LMW adiponectin, than middle-aged individuals with T2D. Female, but not male, octogenarians revealed significantly lower total adiponectin than normoglycemic octogenarians. Compared with normoglycemic octogenarians, male and female octogenarians with T2D were characterized by significantly lower LMW adiponectin. In male and female octogenarians, total adiponectin and all multimer isoforms were directly correlated with HDL cholesterol. LMW adiponectin in octogenarians of both sexes was inversely correlated with glucose level at 2-hour oral glucose tolerance test. Conclusions: Serum levels of total adiponectin as well as its HMW and MMW isoforms were significantly higher in octogenarians with normoglycemia or T2D than in corresponding middle-aged control groups. In male and female octogenarians without metabolic syndrome, T2D was associated with lower LMW adiponectin, while the HMW and MMW isoforms were not statistically different.Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG-geförderten) Allianz- bzw. Nationallizenz frei zugänglich

Detection of Independent Associations of Plasma Lipidomic Parameters with Insulin Sensitivity Indices Using Data Mining Methodology

OBJECTIVE Glucolipotoxicity is a major pathophysiological mechanism in the development of insulin resistance and type 2 diabetes mellitus (T2D). We aimed to detect subtle changes in the circulating lipid profile by shotgun lipidomics analyses and to associate them with four different insulin sensitivity indices. METHODS The cross-sectional study comprised 90 men with a broad range of insulin sensitivity including normal glucose tolerance (NGT, n = 33), impaired glucose tolerance (IGT, n = 32) and newly detected T2D (n = 25). Prior to oral glucose challenge plasma was obtained and quantitatively analyzed for 198 lipid molecular species from 13 different lipid classes including triacylglycerls (TAGs), phosphatidylcholine plasmalogen/ether (PC O-s), sphingomyelins (SMs), and lysophosphatidylcholines (LPCs). To identify a lipidomic signature of individual insulin sensitivity we applied three data mining approaches, namely least absolute shrinkage and selection operator (LASSO), Support Vector Regression (SVR) and Random Forests (RF) for the following insulin sensitivity indices: homeostasis model of insulin resistance (HOMA-IR), glucose insulin sensitivity index (GSI), insulin sensitivity index (ISI), and disposition index (DI). The LASSO procedure offers a high prediction accuracy and and an easier interpretability than SVR and RF. RESULTS After LASSO selection, the plasma lipidome explained 3% (DI) to maximal 53% (HOMA-IR) variability of the sensitivity indexes. Among the lipid species with the highest positive LASSO regression coefficient were TAG 54:2 (HOMA-IR), PC O- 32:0 (GSI), and SM 40:3:1 (ISI). The highest negative regression coefficient was obtained for LPC 22:5 (HOMA-IR), TAG 51:1 (GSI), and TAG 58:6 (ISI). CONCLUSION Although a substantial part of lipid molecular species showed a significant correlation with insulin sensitivity indices we were able to identify a limited number of lipid metabolites of particular importance based on the LASSO approach. These few selected lipids with the closest connection to sensitivity indices may help to further improve disease risk prediction and disease and therapy monitoring

Detection of Independent Associations of Plasma Lipidomic Parameters with Insulin Sensitivity Indices Using Data Mining Methodology.

OBJECTIVE:Glucolipotoxicity is a major pathophysiological mechanism in the development of insulin resistance and type 2 diabetes mellitus (T2D). We aimed to detect subtle changes in the circulating lipid profile by shotgun lipidomics analyses and to associate them with four different insulin sensitivity indices. METHODS:The cross-sectional study comprised 90 men with a broad range of insulin sensitivity including normal glucose tolerance (NGT, n = 33), impaired glucose tolerance (IGT, n = 32) and newly detected T2D (n = 25). Prior to oral glucose challenge plasma was obtained and quantitatively analyzed for 198 lipid molecular species from 13 different lipid classes including triacylglycerls (TAGs), phosphatidylcholine plasmalogen/ether (PC O-s), sphingomyelins (SMs), and lysophosphatidylcholines (LPCs). To identify a lipidomic signature of individual insulin sensitivity we applied three data mining approaches, namely least absolute shrinkage and selection operator (LASSO), Support Vector Regression (SVR) and Random Forests (RF) for the following insulin sensitivity indices: homeostasis model of insulin resistance (HOMA-IR), glucose insulin sensitivity index (GSI), insulin sensitivity index (ISI), and disposition index (DI). The LASSO procedure offers a high prediction accuracy and and an easier interpretability than SVR and RF. RESULTS:After LASSO selection, the plasma lipidome explained 3% (DI) to maximal 53% (HOMA-IR) variability of the sensitivity indexes. Among the lipid species with the highest positive LASSO regression coefficient were TAG 54:2 (HOMA-IR), PC O- 32:0 (GSI), and SM 40:3:1 (ISI). The highest negative regression coefficient was obtained for LPC 22:5 (HOMA-IR), TAG 51:1 (GSI), and TAG 58:6 (ISI). CONCLUSION:Although a substantial part of lipid molecular species showed a significant correlation with insulin sensitivity indices we were able to identify a limited number of lipid metabolites of particular importance based on the LASSO approach. These few selected lipids with the closest connection to sensitivity indices may help to further improve disease risk prediction and disease and therapy monitoring

Detection of Independent Associations of Plasma Lipidomic Parameters with Insulin Sensitivity Indices Using Data Mining Methodology

<div><p>Objective</p><p>Glucolipotoxicity is a major pathophysiological mechanism in the development of insulin resistance and type 2 diabetes mellitus (T2D). We aimed to detect subtle changes in the circulating lipid profile by shotgun lipidomics analyses and to associate them with four different insulin sensitivity indices.</p><p>Methods</p><p>The cross-sectional study comprised 90 men with a broad range of insulin sensitivity including normal glucose tolerance (NGT, n = 33), impaired glucose tolerance (IGT, n = 32) and newly detected T2D (n = 25). Prior to oral glucose challenge plasma was obtained and quantitatively analyzed for 198 lipid molecular species from 13 different lipid classes including triacylglycerls (TAGs), phosphatidylcholine plasmalogen/ether (PC O-s), sphingomyelins (SMs), and lysophosphatidylcholines (LPCs). To identify a lipidomic signature of individual insulin sensitivity we applied three data mining approaches, namely least absolute shrinkage and selection operator (LASSO), Support Vector Regression (SVR) and Random Forests (RF) for the following insulin sensitivity indices: homeostasis model of insulin resistance (HOMA-IR), glucose insulin sensitivity index (GSI), insulin sensitivity index (ISI), and disposition index (DI). The LASSO procedure offers a high prediction accuracy and and an easier interpretability than SVR and RF.</p><p>Results</p><p>After LASSO selection, the plasma lipidome explained 3% (DI) to maximal 53% (HOMA-IR) variability of the sensitivity indexes. Among the lipid species with the highest positive LASSO regression coefficient were TAG 54:2 (HOMA-IR), PC O- 32:0 (GSI), and SM 40:3:1 (ISI). The highest negative regression coefficient was obtained for LPC 22:5 (HOMA-IR), TAG 51:1 (GSI), and TAG 58:6 (ISI).</p><p>Conclusion</p><p>Although a substantial part of lipid molecular species showed a significant correlation with insulin sensitivity indices we were able to identify a limited number of lipid metabolites of particular importance based on the LASSO approach. These few selected lipids with the closest connection to sensitivity indices may help to further improve disease risk prediction and disease and therapy monitoring.</p></div

Relative errors of insulin sensitivity indices HOMA-IR, ISI, GSI, and DI explained by lipid species and age, BMI, WHR and systolic blood pressure.

<p>Three different selection methods were applied: LASSO, Random Forests (RF), and support vector regression (SVR). Data are presented as boxplots plus median.</p