NMR-determined lipoprotein subclass profile predicts type 2 diabetes

Ambient air pollution exposure, plasma metabolomic markers, and risk of type 2 diabetes: A prospective cohort study

BACKGROUND

Both air pollution (AP) and impaired lipid metabolism contribute to type 2 diabetes (T2D). However, little is known about the detailed associations of AP to lipidomic markers and the specific lipid metabolomic profile that mediates the impact of AP on incident T2D. We aimed to examine the associations between long-term AP exposure, plasma metabolomic markers, and incident T2D, and subsequently determine the lipid metabolomic profile that mediates the relationship between AP and T2D.

METHODS

This prospective study included 82,548 participants from the UK Biobank without a history of T2D at baseline. Baseline plasma samples were analyzed using the nuclear magnetic resonance (NMR) metabolomic platform, which measured 168 metabolomic markers, including lipids, lipoprotein subclasses, and other circulating metabolites. Land Use Regression models were utilized to estimate annual average concentrations of PM2.5 and NO2. The associations among AP, metabolomic markers, and T2D were investigated using multivariable linear regressions and Cox proportional hazards models. Mediation analyses were performed to assess the role of each metabolomic marker in the AP-T2D relationship. Furthermore, principal component (PC) analysis was conducted on 168 metabolomic markers to extract metabolic patterns. These patterns were utilized to determine their associations with AP and T2D, as well as their mediating role in the AP-T2D relationship.

RESULTS

We found that long-term AP exposure was associated with some lipid metabolites, including ApoA1, HDL concentration, HDL size, and lipid components within HDL, especially in very large, large, and medium HDL, as well as some other lipids, fatty acids, amino acids, glucose, and glycoprotein acetyls. In pairwise mediation analysis, these metabolites exhibited significant mediation effects in the AP-T2D relationship. We identified six PCS representing distinct metabolic patterns. Long-term exposure to PM2.5 and NO2 showed significantly negative associations with PC2 (characterized by high levels of ApoA1, larger HDL, other lipids, and low levels of larger VLDL). PC2 mediated 12.3% and 10.3% of the associations of PM2.5 and NO2 with incident T2D, respectively.

CONCLUSIONS

This study revealed the associations of AP with various lipid metabolites. A lipid metabolomic profile characterized by ApoA1 and larger HDL may mediate the association between AP and incident T2D.

Both LDL and HDL particle concentrations associate positively with an increased risk of developing microvascular complications in patients with type 2 diabetes: lost protection by HDL (Zodiac-63)

BACKGROUND

Triglyceride-rich lipoproteins (TRL) and low-density lipoproteins (LDL) are associated positively whereas high-density lipoproteins (HDL) are associated inversely with the development of new-onset type 2 diabetes (T2D). Here we studied potential associations between these lipoprotein particle concentrations and the risk of developing microvascular complications in patients with established T2D.

METHODS

Lipoprotein particle concentrations (TRLP, LDLP, and HDLP) were determined in 278 patients with T2D participating in a primary care-based longitudinal cohort study (Zwolle Outpatient Diabetes project Integrating Available Care [ZODIAC] study) leveraging the Vantera nuclear magnetic resonance (NMR) platform using the LP4 algorithm. Associations between lipoprotein particles and incident microvascular complications (nephropathy, neuropathy, and retinopathy) were assessed using Cox proportional hazards regression models.

RESULTS

In total, 136 patients had microvascular complications at baseline. During a median follow-up of 3.2 years, 49 (34.5%) of 142 patients without microvascular complications at baseline developed new-onset microvascular complications. In multivariable Cox proportional hazards regression analyses, both total LDLP and HDLP concentrations, but not total TRLP concentrations, were positively associated with an increased risk of developing any microvascular complications after adjustment for potential confounding factors, including age, sex, disease duration, HbA1c levels, history of macrovascular complications, and statin use (adjusted hazard ratio [HR] per 1 SD increment: 1.70 [95% CI 1.24-2.34], P < 0.001 and 1.63 [95% CI 1.19-2.23], P = 0.002, respectively). When analyzing each microvascular complication individually, total LDLP concentrations were positively associated with retinopathy (adjusted HR 3.35, 95% CI 1.35-8.30, P = 0.009) and nephropathy (adjusted HR 2.13, 95% CI 1.27-3.35, P = 0.004), and total HDLP concentrations with neuropathy (adjusted HR 1.77, 95% CI 1.15-2.70, P = 0.009). No significant associations were observed for lipoprotein particle subfractions.

CONCLUSIONS

Total lipoprotein particle concentrations of both LDL and HDL associate positively with an increased risk of developing microvascular complications in T2D. We propose that the protective role of HDL on the development of microvascular complications may be lost in established T2D.

NMR derived changes of lipoprotein particle concentrations related to impaired fasting glucose, impaired glucose tolerance, or manifest type 2 diabetes mellitus

Background

Type 2 diabetes mellitus (T2D) and corresponding borderline states, impaired fasting glucose (IFG) and/or glucose tolerance (IGT), are associated with dyslipoproteinemia. It is important to distinguish between factors that cause T2D and that are the direct result of T2D.

Methods

The lipoprotein subclass patterns of blood donors with IFG, IGT, with IFG combined with IGT, and T2D are analyzed by nuclear magnetic resonance (NMR) spectroscopy. The development of lipoprotein patterns with time is investigated by using samples retained for an average period of 6 years. In total 595 blood donors are classified by oral glucose tolerance test (oGTT) and their glycosylated hemoglobin (HbA1c) concentrations. Concentrations of lipoprotein particles of 15 different subclasses are analyzed in the 10,921 NMR spectra recorded under fasting and non-fasting conditions. The subjects are assumed healthy according to the strict regulations for blood donors before performing the oGTT.

Results

Under fasting conditions manifest T2D exhibits a significant concentration increase of the smallest HDL particles (HDL A) combined with a decrease in all other HDL subclasses. In contrast to other studies reviewed in this paper, a general concentration decrease of all LDL particles is observed that is most prominent for the smallest LDL particles (LDL A). Under normal nutritional conditions a large, significant increase of the concentrations of VLDL and chylomicrons is observed for all groups with IFG and/or IGT and most prominently for manifest T2D. As we show it is possible to obtain an estimate of the concentrations of the apolipoproteins Apo-A1, Apo-B100, and Apo-B48 from the NMR data. In the actual study cohort, under fasting conditions the concentrations of the lipoproteins are not increased significantly in T2D, under non-fasting conditions only Apo-B48 increases significantly.

Conclusion

In contrast to other studies, in our cohort of “healthy” blood donors the T2D associated dyslipoproteinemia does not change the total concentrations of the lipoprotein particles produced in the liver under fasting and non-fasting conditions significantly but only their subclass distributions. Compared to the control group, under non-fasting conditions participants with IGT and IFG or T2D show a substantial increase of plasma concentrations of those lipoproteins that are produced in the intestinal tract. The intestinal insulin resistance becomes strongly observable.

Association of Advanced Lipoprotein Subpopulation Profiles with Insulin Resistance and Inflammation in Patients with Type 2 Diabetes Mellitus

Plasma lipoproteins exist as several subpopulations with distinct particle number and size that are not fully reflected in the conventional lipid panel. In this study, we sought to quantify lipoprotein subpopulations in patients with type 2 diabetes mellitus (T2DM) to determine whether specific lipoprotein subpopulations are associated with insulin resistance and inflammation markers. The study included 57 patients with T2DM (age, 61.14 ± 9.99 years; HbA1c, 8.66 ± 1.60%; mean body mass index, 35.15 ± 6.65 kg/m²). Plasma lipoprotein particles number and size were determined by nuclear magnetic resonance spectroscopy. Associations of different lipoprotein subpopulations with lipoprotein insulin resistance (LPIR) score and glycoprotein acetylation (GlycA) were assessed using multi-regression analysis. In stepwise regression analysis, VLDL and HDL large particle number and size showed the strongest associations with LPIR (R² = 0.960; p = 0.0001), whereas the concentrations of the small VLDL and HDL particles were associated with GlycA (R² = 0.190; p = 0.008 and p = 0.049, respectively). In adjusted multi-regression analysis, small and large VLDL particles and all sizes of lipoproteins independently predicted LPIR, whereas only the number of small LDL particles predicted GlycA. Conventional markers HbA1c and Hs-CRP did not exhibit any significant association with lipoprotein subpopulations. Our data suggest that monitoring insulin resistance-induced changes in lipoprotein subpopulations in T2DM might help to identify novel biomarkers that can be useful for effective clinical intervention.

Causal effects of genetically predicted type 2 diabetes mellitus on blood lipid profiles and concentration of particle-size-determined lipoprotein subclasses: A two-sample Mendelian randomization study

Background

Observational studies have shown inconsistent results of the associations between type 2 diabetes mellitus (T2DM) and blood lipid profiles, while there is also a lack of evidence from randomized controlled trials (RCTs) for the causal effects of T2DM on blood lipid profiles and lipoprotein subclasses.

Objectives

Our study aimed at investigating the causal effects of T2DM on blood lipid profiles and concentration of particle-size-determined lipoprotein subclasses by using the two-sample Mendelian randomization (MR) method.

Methods

We obtained genetic variants for T2DM and blood lipid profiles including high-density lipoprotein-cholesterol (HDL-C), low-density lipoprotein-cholesterol (LDL-C), triglycerides (TG), and total cholesterol (TC) from international genome-wide association studies (GWASs). Two-sample MR method was applied to explore the potential causal effects of genetically predicted T2DM on blood lipid profiles based on different databases, respectively, and results from each MR analysis were further meta-analyzed to obtain the summary results. The causal effects of genetically predicted T2DM on the concentration of different subclasses of lipoproteins that are determined by particle size were also involved in MR analysis.

Results

Genetically predicted 1-unit higher log odds of T2DM had a significant causal effect on a higher level of TG (estimated β coefficient: 0.03, 95% confidence interval [CI]: 0.00 to 0.06) and lower level of HDL-C (estimated β coefficient: −0.09, 95% CI: −0.11 to −0.06). The causality of T2DM on the level of TC or LDL-C was not found (estimated β coefficient: −0.01, 95% CI: −0.02 to 0.01 for TC and estimated β coefficient: 0.01, 95% CI: −0.01 to 0.02 for LDL-C). For different sizes of lipoprotein particles, 1-unit higher log odds of T2DM was causally associated with higher level of small LDL particles, and lower level of medium HDL particles, large HDL particles, and very large HDL particles.

Conclusion

Evidence from our present study showed causal effects of T2DM on the level of TG, HDL-C, and concentration of different particle sizes of lipoprotein subclasses comprehensively, which might be particularly helpful in illustrating dyslipidemia experienced by patients with T2DM, and further indicate new treatment targets for these patients to prevent subsequent excessive cardiovascular events from a genetic point of view.

Circulating Metabolic Biomarkers Are Consistently Associated With Type 2 Diabetes Risk in Asian and European Populations

CONTEXT

While Asians have a higher risk of type 2 diabetes (T2D) than Europeans for a given body mass index (BMI), it remains unclear whether the same markers of metabolic pathways are associated with diabetes.

OBJECTIVE

We evaluated associations between metabolic biomarkers and incidence of T2D in 3 major Asian ethnic groups (Chinese, Malay, and Indian) and a European population.

METHODS

We analyzed data from adult males and females of 2 cohorts from Singapore (n = 6393) consisting of Chinese, Malays, and Indians and 3 cohorts of European-origin participants from Finland (n = 14 558). We used nuclear magnetic resonance to quantify 154 circulating metabolic biomarkers at baseline and performed logistic regression to assess associations with T2D risk adjusted for age, sex, BMI and glycemic markers.

RESULTS

Of the 154 metabolic biomarkers, 59 were associated with higher risk of T2D in both Asians and Europeans (P < 0.0003, Bonferroni-corrected). These included branched chain and aromatic amino acids, the inflammatory marker glycoprotein acetyls, total fatty acids, monounsaturated fatty acids, apolipoprotein B, larger very low-density lipoprotein particle sizes, and triglycerides. In addition, 13 metabolites were associated with a lower T2D risk in both populations, including omega-6 polyunsaturated fatty acids and larger high-density lipoprotein particle sizes. Associations were consistent within the Asian ethnic groups (all Phet ≥ 0.05) and largely consistent for the Asian and European populations (Phet ≥ 0.05 for 128 of 154 metabolic biomarkers).

CONCLUSION

Metabolic biomarkers across several biological pathways were consistently associated with T2D risk in Asians and Europeans.

Triglyceride-rich lipoprotein and LDL particle subfractions and their association with incident type 2 diabetes: the PREVEND study

Background

Triglyceride-rich lipoproteins particles (TRLP) and low density lipoprotein particles (LDLP) vary in size. Their association with β-cell function is not well described. We determined associations of TRLP and LDLP subfractions with β-cell function, estimated as HOMA-β, and evaluated their associations with incident T2D in the general population.

Methods

We included 4818 subjects of the Prevention of Renal and Vascular End-Stage Disease (PREVEND) study without T2D at baseline. TRLP and LDLP subfraction concentrations and their average sizes were measured using the LP4 algorithm of the Vantera nuclear magnetic resonance platform. HOMA-IR was used as measure of insulin resistance. HOMA-β was used as a proxy of β-cell function.

Results

In subjects without T2D at baseline, very large TRLP, and LDL size were inversely associated with HOMA-β, whereas large TRLP were positively associated with HOMA-β when taking account of HOMA-IR. During a median follow-up of 7.3 years, 263 participants developed T2D. In multivariable-adjusted Cox regression models, higher concentrations of total, very large, large, and very small TRLP (reflecting remnants lipoproteins) and greater TRL size were associated with an increased T2D risk after adjustment for relevant covariates, including age, sex, BMI, HDL-C, HOMA-β, and HOMA-IR. On the contrary, higher concentrations of large LDLP and greater LDL size were associated with a lower risk of developing T2D.

Conclusions

Specific TRL and LDL particle characteristics are associated with β-cell function taking account of HOMA-IR. Moreover, TRL and LDL particle characteristics are differently associated with incident T2D, even when taking account of HOMA-β and HOMA-IR.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12933-021-01348-w.

HDL Particle Subspecies and Their Association With Incident Type 2 Diabetes: The PREVEND Study

CONTEXT

High-density lipoproteins (HDL) may be protective against type 2 diabetes (T2D) development, but HDL particles vary in size and function, which could lead to differential associations with incident T2D. A newly developed nuclear magnetic resonance (NMR)-derived algorithm provides concentrations for 7 HDL subspecies.

OBJECTIVE

We aimed to investigate the association of HDL particle subspecies with incident T2D in the general population.

METHODS

Among 4828 subjects of the Prevention of Renal and Vascular End-Stage Disease (PREVEND) study without T2D at baseline, HDL subspecies with increasing size from H1P to H7P were measured by NMR (LP4 algorithm of the Vantera NMR platform).

RESULTS

A total of 265 individuals developed T2D (median follow-up of 7.3 years). In Cox regression models, HDL size and H4P (hazard ratio [HR] per 1 SD increase 0.83 [95% CI, 0.69-0.99] and 0.85 [95% CI, 0.75-0.95], respectively) were inversely associated with incident T2D, after adjustment for relevant covariates. In contrast, levels of H2P were positively associated with incident T2D (HR 1.15 [95% CI, 1.01-1.32]). In secondary analyses, associations with large HDL particles and H6P were modified by body mass index (BMI) in such a way that they were particularly associated with a lower risk of incident T2D, in subjects with BMI < 30 kg/m2.

CONCLUSION

Greater HDL size and lower levels of H4P were associated with a lower risk, whereas higher levels of H2P were associated with a higher risk of developing T2D. In addition, large HDL particles and H6P were inversely associated with T2D in nonobese subjects.

Predictive utilities of lipid traits, lipoprotein subfractions and other risk factors for incident diabetes: a machine learning approach in the Diabetes Prevention Program

INTRODUCTION

Although various lipid and non-lipid analytes measured by nuclear magnetic resonance (NMR) spectroscopy have been associated with type 2 diabetes, a structured comparison of the ability of NMR-derived biomarkers and standard lipids to predict individual diabetes risk has not been undertaken in larger studies nor among individuals at high risk of diabetes.

RESEARCH DESIGN AND METHODS

Cumulative discriminative utilities of various groups of biomarkers including NMR lipoproteins, related non-lipid biomarkers, standard lipids, and demographic and glycemic traits were compared for short-term (3.2 years) and long-term (15 years) diabetes development in the Diabetes Prevention Program, a multiethnic, placebo-controlled, randomized controlled trial of individuals with pre-diabetes in the USA (N=2590). Logistic regression, Cox proportional hazards model and six different hyperparameter-tuned machine learning algorithms were compared. The Matthews Correlation Coefficient (MCC) was used as the primary measure of discriminative utility.

RESULTS

Models with baseline NMR analytes and their changes did not improve the discriminative utility of simpler models including standard lipids or demographic and glycemic traits. Across all algorithms, models with baseline 2-hour glucose performed the best (max MCC=0.36). Sophisticated machine learning algorithms performed similarly to logistic regression in this study.

CONCLUSIONS

NMR lipoproteins and related non-lipid biomarkers were associated but did not augment discrimination of diabetes risk beyond traditional diabetes risk factors except for 2-hour glucose. Machine learning algorithms provided no meaningful improvement for discrimination compared with logistic regression, which suggests a lack of influential latent interactions among the analytes assessed in this study.

TRIAL REGISTRATION NUMBER

Diabetes Prevention Program: NCT00004992; Diabetes Prevention Program Outcomes Study: NCT00038727.

Dissociation Between Insulin Resistance and Abnormalities in Lipoprotein Particle Concentrations and Sizes in Normal-Weight Chinese Adults

Insulin resistance in obesity coincides with abnormalities in lipid profile and lipoprotein subclass distribution and size even before abnormalities in glucose homeostasis manifest. We aimed to assess this relationship in the absence of obesity. Insulin sensitivity (3-h intravenous glucose tolerance test and minimal modeling) and lipoprotein particle concentrations and sizes (proton nuclear magnetic resonance spectroscopy) were evaluated in 15 insulin-resistant and 15 insulin-sensitive lean Asians of Chinese descent with normal glucose tolerance, matched on age, sex, and body mass index. Despite a ~50% lower insulin sensitivity index (Si) in insulin-resistant than in insulin-sensitive subjects, which was accompanied by significantly greater acute insulin response to glucose (AIRg) and fasting insulin concentration but not different fasting glucose concentration, there were no significant differences between groups in the blood lipid profile (p ≥ 0.44) or the lipoprotein subclass concentrations (p ≥ 0.30) and particle sizes (p ≥ 0.43). We conclude that, contrary to observations in subjects with obesity, insulin resistance is not accompanied by unfavorable changes in the plasma lipid profile and lipoprotein particle concentrations and sizes in lean Asians with normal glucose tolerance. Therefore, insulin resistance at the level of glucose metabolism is mechanistically or temporally dissociated from lipid and lipoprotein metabolism.

Trial Registration:clinicaltrials.gov, NCT03264001.

Predicting Skeletal Muscle and Whole-Body Insulin Sensitivity Using NMR-Metabolomic Profiling

PURPOSE

Abnormal lipoprotein and amino acid profiles are associated with insulin resistance and may help to identify this condition. The aim of this study was to create models estimating skeletal muscle and whole-body insulin sensitivity using fasting metabolite profiles and common clinical and laboratory measures.

MATERIAL AND METHODS

The cross-sectional study population included 259 subjects with normal or impaired fasting glucose or type 2 diabetes in whom skeletal muscle and whole-body insulin sensitivity (M-value) were measured during euglycemic hyperinsulinemic clamp. Muscle glucose uptake (GU) was measured directly using [18F]FDG-PET. Serum metabolites were measured using nuclear magnetic resonance (NMR) spectroscopy. We used linear regression to build the models for the muscle GU (Muscle-insulin sensitivity index [ISI]) and M-value (whole-body [WB]-ISI). The models were created and tested using randomly selected training (n = 173) and test groups (n = 86). The models were compared to common fasting indices of insulin sensitivity, homeostatic model assessment-insulin resistance (HOMA-IR) and the revised quantitative insulin sensitivity check index (QUICKI).

RESULTS

WB-ISI had higher correlation with actual M-value than HOMA-IR or revised QUICKI (ρ = 0.83 vs -0.67 and 0.66; P < 0.05 for both comparisons), whereas the correlation of Muscle-ISI with the actual skeletal muscle GU was not significantly stronger than HOMA-IR's or revised QUICKI's (ρ = 0.67 vs -0.58 and 0.59; both nonsignificant) in the test dataset.

CONCLUSION

Muscle-ISI and WB-ISI based on NMR-metabolomics and common laboratory measurements from fasting serum samples and basic anthropometrics are promising rapid and inexpensive tools for determining insulin sensitivity in at-risk individuals.

High-Density Lipoprotein Particles and Their Relationship to Posttransplantation Diabetes Mellitus in Renal Transplant Recipients

High concentrations of high-density lipoprotein (HDL) cholesterol are likely associated with a lower risk of posttransplantation diabetes mellitus (PTDM). However, HDL particles vary in size and density with yet unestablished associations with PTDM risk. The aim of our study was to determine the association between different HDL particles and development of PTDM in renal transplant recipients (RTRs). We included 351 stable outpatient adult RTRs without diabetes at baseline evaluation. HDL particle characteristics and size were measured by nuclear magnetic resonance (NMR) spectroscopy. During 5.2 (IQR, 4.1‒5.8) years of follow-up, 39 (11%) RTRs developed PTDM. In multivariable Cox regression analysis, levels of HDL cholesterol (hazard ratio [HR] 0.61, 95% confidence interval [CI] 0.40-0.94 per 1SD increase; p = 0.024) and of large HDL particles (HR 0.68, 95% CI 0.50-0.93 per log 1SD increase; p = 0.017), as well as larger HDL size (HR 0.58, 95% CI 0.36-0.93 per 1SD increase; p = 0.025) were inversely associated with PTDM development, independently of relevant covariates including, age, sex, body mass index, medication use, transplantation-specific parameters, blood pressure, triglycerides, and glucose. In conclusion, higher concentrations of HDL cholesterol and of large HDL particles and greater HDL size were associated with a lower risk of PTDM development in RTRs, independently of established risk factors for PTDM development.

Triglycerides and triglyceride-rich lipoproteins in the development and progression of atherosclerosis

PURPOSE OF REVIEW

In this review, we intend to show the heterogenicity of the triglyceride group, including the triglyceride-rich lipoproteins and its subparticles, apolipoproteins, and its role in atherogenesis through epidemiological and genetic studies, observing the association of these various components and subclasses with subclinical atherosclerosis and cardiovascular events. Also, we reevaluated the moment of blood collection for the triglyceride measurement and its repercussion in atherosclerosis. Finally, we present the current scenario and new insights about the pharmacologic treatment of hypertriglyceridemia.

RECENT FINDINGS

Recent studies have been observed, a correlation between cardiovascular disease and triglyceride components (as apolipoproteins A-V, C-I, C-III) as well as proteins involved in the metabolism pathway, such as the angiopoietin-like proteins. Also, the triglyceride-rich lipoproteins, also known as remnants, were recently associated with atherogenesis. Another important topic addressed is about nonfasting triglyceride level, which has been postulated as a better predictor of cardiovascular events than fasting collection.

SUMMARY

Regarding hypertriglyceridemia treatment, the drug therapy was updated, as the omega-3 polyunsaturated fatty acids were tested in primary prevention as eicosapentaenoic acid and docosahexaenoic acid combination resulted in no benefit, whereas the administration of icosapent ethyl in secondary prevention and high-risk patients showed a robust decrease of the cardiovascular outcomes.

Association of Lipoproteins, Insulin Resistance, and Rosuvastatin With Incident Type 2 Diabetes Mellitus : Secondary Analysis of a Randomized Clinical Trial

IMPORTANCE

Statins decrease levels of low-density lipoprotein (LDL) and triglycerides as well as cardiovascular events but increase the risk for a diagnosis of type 2 diabetes mellitus (T2DM). The risk factors associated with incident T2DM are incompletely characterized.

OBJECTIVE

To investigate the association of lipoprotein subclasses and size and a novel lipoprotein insulin resistance (LPIR) score (a composite of 6 lipoprotein measures) with incident T2DM among individuals randomized to a high-intensity statin or placebo.

DESIGN, SETTING, AND PARTICIPANTS

This secondary analysis of the JUPITER trial (a placebo-controlled randomized clinical trial) was conducted at 1315 sites in 26 countries and enrolled 17 802 men 50 years or older and women 60 years or older with LDL cholesterol levels less than 130 mg/dL, high-sensitivity C-reactive protein levels of at least 2 mg/L, and triglyceride levels less than 500 mg/dL. Those with T2DM were excluded. A prespecified secondary aim was to assess the effect of rosuvastatin calcium on T2DM. Incident T2DM was monitored for a median of 2.0 years. Data were collected from February 4, 2003, to August 20, 2008, and analyzed (intention-to-treat) from December 1, 2013, to January 21, 2016.

INTERVENTIONS

Rosuvastatin calcium, 20 mg/d, or placebo.

MAIN OUTCOMES AND MEASURES

Size and concentration of lipids, apolipoproteins, and lipoproteins at baseline (11 918 patients with evaluable plasma samples) and 12 months after randomization (9180 patients). The LPIR score, a correlate of insulin resistance, was calculated as a weighted combination of size and concentrations of LDL, very low-density lipoprotein (VLDL), and high-density lipoprotein (HDL) particles.

RESULTS

Among the 11 918 patients (4334 women [36.4%]; median [interquartile range] age, 66 [60-71] years), rosuvastatin lowered the levels of LDL particles (-39.6%; 95% CI, -49.4% to -24.6%), VLDL particles (-19.6%; 95% CI, -40.6% to 10.3%), and VLDL triglycerides (-15.2%; 95% CI, -35.9% to 11.3%) and shifted the lipoprotein subclass distribution toward smaller LDL size (-1.5%; 95% CI, -3.7% to 0.5%), larger VLDL size (2.8%; 95% CI, -5.8% to 12.7%), and lower LPIR score (-3.2%; 95% CI, -20.6% to 16.9%). In analyses adjusted for age, sex, race or ethnic origin, exercise, educational level, family history, and smoking, the hazard ratio (HR) for T2DM per SD of LPIR score in the placebo arm was 1.99 (95% CI, 1.64-2.42); in the rosuvastatin arm, 2.06 (95% CI, 1.74-2.43). After additional adjustment for systolic blood pressure, body mass index, high-sensitivity C-reactive protein, hemoglobin A1c, HDL cholesterol, LDL cholesterol, and triglycerides, the LPIR score remained associated with T2DM in the placebo arm (HR, 1.35; 95% CI, 1.03-1.76) and rosuvastatin arm (HR, 1.60; 95% CI, 1.27-2.03). Similar trends were seen at 12 months. The LPIR score improved the model likelihood ratio (χ2 = 18.23; P < .001) and categorical net reclassification index (0.039; 95% CI, 0.003-0.072).

CONCLUSIONS AND RELEVANCE

In apparently healthy people, LPIR score was positively associated with incident T2DM, including during rosuvastatin therapy.

TRIAL REGISTRATION

clinicaltrials.gov Identifier: NCT00239681.

Different inverse association of large high-density lipoprotein subclasses with exacerbation of insulin resistance and incidence of type 2 diabetes: The Nagahama study

AIMS

In addition to its antiatherogenic action, high-density lipoprotein (HDL) may also have an antidiabetes function. Although the biological actions of small HDL (HDL3) and large HDL (HDL2) subclasses may be different, evidence in support of that hypothesis is lacking. The aim of this study was to clarify the difference in prognostic significance of HDL subclasses for exacerbation of insulin resistance and incidence of type 2 diabetes in the general population.

METHODS

Study participants included 8365 community residents 52±13years of age not taking lipid lowering drugs. Serum HDL cholesterol subclasses and low-density lipoprotein subclasses, were measured by a homogeneous assay. Insulin resistance was assessed by homeostasis model assessment of insulin resistance (HOMA-IR).

RESULTS

Cross-sectional analysis adjusted for possible covariates found that HDL2 cholesterol (HDL2-C) levels were inversely associated with HOMA-IR (β=-0.169, p<0.001), whereas HDL3-C had the opposite association (β=0.054, p<0.001). Similar results were found in an analysis for type 2 diabetes (HDL2-C, odds ratio=0.96, p=0.001; HDL3-C, odds ratio=1.04, p=0.181). In a longitudinal analysis with 5.0years of follow-up, HDL2-C was inversely associated with exacerbation of insulin resistance (β=-0.163, p<0.001); HDL3-C had the opposite association (β=0.026, p=0.037). During follow-up, 205 individuals were newly diagnosed with diabetes, and HDL2-C level was associated with an inverse risk of type 2 diabetes incidence (odds ratio=0.98, p=0.006).

CONCLUSIONS

HDL may have an antidiabetic function; the prognostic value of HDL2-C for diabetes and insulin resistance might be better than that of HDL3-C.

Egg consumption and risk of incident type 2 diabetes: a dose–response meta-analysis of prospective cohort studies

Experimental data suggest that egg intake could have a beneficial impact on several risk factors for type 2 diabetes. In contrast, some recent epidemiological studies have concluded that egg consumption may increase diabetes risk. We performed a dose–response meta-analysis of prospective cohorts on the relation of egg consumption with incident type 2 diabetes. We searched for cohort studies that assessed egg consumption and diabetes risk up to June 2015. We identified 416 articles and extracted data independently and in duplicate from ten eligible studies. We used random-effects generalised least squares models for pooled dose–response estimation based on thirteen estimates. Our study included 251 213 individuals and 12 156 incident type 2 diabetes cases. Egg intake was associated with incident type 2 diabetes (risk ratio (RR)/egg per d 1·13; 95 % CI 1·04, 1·22). We identified study location as a major source of heterogeneity. For studies conducted in the USA, we observed a stronger association (RR 1·47; 95 % CI 1·32, 1·64), whereas results were null for studies conducted elsewhere. Studies considered to be of high quality yielded null findings (RR 0·94; 95 % CI 0·74, 1·19). The association of egg intake with increased risk of incident type 2 diabetes may be restricted to US cohort studies. There are limited data to support a biological mechanism that could underlie this association; thus, the possibility that these results may be due to residual confounding by dietary behaviours restricted to certain populations cannot be excluded.

Egg consumption and risk of incident type 2 diabetes in men: the Kuopio Ischaemic Heart Disease Risk Factor Study

BACKGROUND

The prevalence of type 2 diabetes (T2D) is increasing around the world. Eggs are a major source of cholesterol, which has been associated with elevated blood glucose and an increased risk of T2D. However, there are limited and conflicting data from prospective population studies on the association between egg consumption and risk of T2D.

OBJECTIVE

We investigated the association between egg consumption and risk of incident T2D in middle-aged and older men from eastern Finland.

DESIGN

The study included 2332 men aged 42-60 y in 1984-1989 at the baseline examinations of the prospective, population-based Kuopio Ischaemic Heart Disease Risk Factor Study. Dietary intakes were assessed with 4-d food records at baseline. Incident T2D was assessed by self-administered questionnaires; by fasting and 2-h oral-glucose-tolerance-test blood glucose measurement at re-examination rounds 4, 11, and 20 y after baseline; and by record linkage to a hospital discharge registry and reimbursement register of diabetes medication expenses. Cox proportional hazards regression analyses were used to estimate associations with the risk of incident T2D. Associations with the metabolic risk markers at baseline and at the 4-y examinations were analyzed by ANCOVA.

RESULTS

During an average follow-up of 19.3 y, 432 men developed T2D. After adjustment for potential confounders, those in the highest compared with the lowest egg intake quartile had a 38% (95% CI: 18%, 53%; P-trend across quartiles <0.001) lower risk of incident T2D. Analyses with metabolic risk markers also suggested an inverse association with fasting plasma glucose and serum C-reactive protein but not with serum insulin. The associations between cholesterol intake and risk of T2D, plasma glucose, serum insulin, and C-reactive protein were mainly nonsignificant, especially after accounting for egg consumption.

CONCLUSION

Higher egg intake was associated with a lower risk of T2D in this cohort of middle-aged and older men.

Lipoprotein particles and incident type 2 diabetes in the multi-ethnic study of atherosclerosis

OBJECTIVE

In the Multi-Ethnic Study of Atherosclerosis (MESA), we evaluated associations of baseline levels of a lipoprotein-based insulin resistance (IR) index (LP-IR), IR-related lipoprotein particles, mean particle sizes, and lipids, with incident type 2 diabetes, independent of confounders, glucose, insulin, and HOMA-IR.

RESEARCH DESIGN AND METHODS

Among 5,314 adults aged 45-84 years without baseline diabetes or cardiovascular disease, 656 cases of diabetes were identified during a mean follow-up of 7.7 years. Lipoprotein particle concentrations, size, and LP-IR were determined by nuclear magnetic resonance spectroscopy of stored baseline plasma. Potential effect modification, by race/ethnicity, sex, baseline use of lipid-lowering medications or hormone therapy, or glucose strata (<90, 90-99, and ≥ 100 mg/dL), was also evaluated.

RESULTS

Higher levels of LP-IR, large VLDL particles (VLDL-P), small LDL particles, triglycerides (TG), and TG-to-HDL cholesterol (HDL-C) ratio and lower levels of large HDL particles, smaller HDL and LDL size, and larger VLDL size were significantly associated with incident diabetes adjusted for confounders and glucose or insulin. These also were similar by race/ethnicity, sex, and treatment group. Associations were similar for LP-IR, large VLDL-P, mean VLDL size, TG, and TG-to-HDL-C ratio; they persisted for LP-IR, large VLDL-P, or mean VLDL size adjusted for HOMA-IR or TG-to-HDL-C ratio and glucose but not for the TG-to-HDL-C ratio adjusted for LP-IR or for HOMA-IR or insulin if adjusted for LP-IR and glucose.

CONCLUSIONS

Among ethnically diverse men and women, LP-IR, large VLDL-P, large VLDL size, TG, and TG-to-HDL-C ratio were associated with incident diabetes independent of established risk factors, glucose, insulin, or HOMA-IR, as well as the use of lipid-lowering medications or hormone therapy.

HDL-C and HDL-C/ApoA-I predict long-term progression of glycemia in established type 2 diabetes

OBJECTIVE

Low HDL cholesterol (HDL-C) and small HDL particle size may directly promote hyperglycemia. We evaluated associations of HDL-C, apolipoprotein A-I (apoA-I), and HDL-C/apoA-I with insulin secretion, insulin resistance, HbA1c, and long-term glycemic deterioration, reflected by initiation of pharmacologic glucose control.

RESEARCH DESIGN AND METHODS

The 5-year Fenofibrate Intervention and Event Lowering in Diabetes (FIELD) study followed 9,795 type 2 diabetic subjects. We calculated baseline associations of fasting HDL-C, apoA-I, and HDL-C/apoA-I with HbA1c and, in those not taking exogenous insulin (n = 8,271), with estimated β-cell function (homeostasis model assessment of β-cell function [HOMA-B]) and insulin resistance (HOMA-IR). Among the 2,608 subjects prescribed lifestyle only, Cox proportional hazards analysis evaluated associations of HDL-C, apoA-I, and HDL-C/apoA-I with subsequent initiation of oral hypoglycemic agents (OHAs) or insulin.

RESULTS

Adjusted for age and sex, baseline HDL-C, apoA-I, and HDL-C/apoA-I were inversely associated with HOMA-IR (r = -0.233, -0.134, and -0.230; all P < 0.001; n = 8,271) but not related to HbA1c (all P > 0.05; n = 9,795). ApoA-I was also inversely associated with HOMA-B (r = -0.063; P = 0.002; n = 8,271) adjusted for age, sex, and HOMA-IR. Prospectively, lower baseline HDL-C and HDL-C/apoA-I levels predicted greater uptake (per 1-SD lower: hazard ratio [HR] 1.13 [CI 1.07-1.19], P < 0.001; and HR 1.16 [CI 1.10-1.23], P < 0.001, respectively) and earlier uptake (median 12.9 and 24.0 months, respectively, for quartile 1 vs. quartile 4; both P < 0.01) of OHAs and insulin, with no difference in HbA1c thresholds for initiation (P = 0.87 and P = 0.81). Controlling for HOMA-IR and triglycerides lessened both associations, but HDL-C/apoA-I remained significant.

CONCLUSIONS

HDL-C, apoA-I, and HDL-C/apoA-I were associated with concurrent insulin resistance but not HbA1c. However, lower HDL-C and HDL-C/apoA-I predicted greater and earlier need for pharmacologic glucose control.

Incidence of total knee and hip replacement for osteoarthritis in relation to the metabolic syndrome and its components: a prospective cohort study

OBJECTIVE

To examine whether components of metabolic syndrome (MetS), either singly or additively, were associated with the incidence of severe knee and hip OA, and whether these associations were independent of obesity assessed by body mass index (BMI).

METHODS

Twenty thousand, four hundred and thirty participants who had blood lipids, anthropometric and blood pressure measurements during 2003-2007 were selected from the Melbourne Collaborative Cohort Study. MetS was defined as central obesity assessed by waist circumference and any two of raised triglyceride level, reduced HDL cholesterol level, hypertension or impaired fasting glycaemia. The incidence of total knee and hip replacement was determined by linking cohort records to the Australian Orthopaedic Association National Joint Replacement Registry.

RESULTS

Six hundred and sixty participants had knee OA and 562 had hip OA. After adjustment for age, gender, country of birth, education, physical activity and BMI, central obesity [hazard ratio (HR) 1.59, 95% confidence interval (CI) 1.25-2.01] and hypertension (1.24, 1.05-1.48) were associated with increased risk of knee OA. The accumulation of MetS components was associated with knee OA risk, independent of BMI: one component, 2.12 (1.15-3.91); two components, 2.92 (1.60-5.33) and three or more components, 3.09 (1.68-5.69). No statistically significant associations were observed for hip OA.

CONCLUSION

Cumulative number of MetS components and central obesity and hypertension were associated with increased risk of severe knee OA, independent of BMI. No associations were observed with severe hip OA. These findings suggest that the pathogenesis of knee and hip OA differ and that targeting the management of MetS may reduce the risk of knee OA.

New tools for weight-loss therapy enable a more robust medical model for obesity treatment: rationale for a complications-centric approach

OBJECTIVE

Recent advances in lifestyle intervention programs, pharmacotherapy, and bariatric surgery have enabled the development of medical models for the treatment of obesity. Regarding pharmacotherapy, in 2012 the U.S. Food and Drug Administration approved two new effective and safe weight-loss medications, phentermine/topiramate extended release and lorcaserin, which has greatly augmented options for medically assisted weight loss.

METHODS

The rationale for advantages of a complications-centric medical model over current body mass index (BMI)-centric indications for therapy is examined.

RESULTS

Currently, the baseline BMI level is the principle determinant of indications for obesity treatment using medication and surgery. However, the BMI-centric approach fails to target therapy to those obese patients who will benefit most from weight loss. In contrast, a complications-centric medical model is proposed that will earmark the modality and intensity of the therapeutic intervention based on the presence and severity of complications that can be ameliorated by weight loss.

CONCLUSION

The complications-centric approach to "medicalizing" obesity care employs weight loss primarily as a tool to treat obesity-related complications and promotes the optimization of health outcomes, the benefit/risk ratio, and the cost-effectiveness of therapy.

Whole egg consumption improves lipoprotein profiles and insulin sensitivity to a greater extent than yolk-free egg substitute in individuals with metabolic syndrome

OBJECTIVE

We investigated if daily egg feeding, along with carbohydrate restriction, would alter lipoprotein metabolism and influence atherogenic lipoprotein profiles and insulin resistance in men and women with metabolic syndrome (MetS).

METHODS

In a randomized, single-blind, parallel design, participants consumed either 3 whole eggs/day (EGG, n=20) or the equivalent amount of yolk-free egg substitute (SUB, n=17), as part of a moderately carbohydrate-restricted diet (25%-30% energy) for 12 weeks. Plasma lipids, apolipoproteins (apos), oxidized LDL (oxLDL), cholesteryl ester transfer protein (CETP) and lecithin-cholesterol acyltransferase (LCAT) activities were assessed at baseline and week 12. Lipoprotein particle concentrations and sizes were measured by nuclear magnetic resonance spectroscopy.

RESULTS

Atherogenic dyslipidemia improved for all individuals as evidenced by reductions in plasma triglycerides, apoC-III, apoE, oxLDL, VLDL particle diameter, large VDL, total IDL, small LDL, and medium LDL particles (P<0.05). Furthermore, there were increases in HDL-cholesterol, large LDL and large HDL particles (P<0.05) for all individuals. However, there were greater increases in HDL-cholesterol and large HDL particles, and reductions in total VLDL and medium VLDL particles for those consuming EGG compared to SUB (P<0.05). Plasma insulin and insulin resistance (HOMA-IR) were reduced, while LCAT activity, and both HDL and LDL diameters increased over time in the EGG group only (P<0.05).

CONCLUSIONS

Incorporating daily whole egg intake into a moderately carbohydrate-restricted diet provides further improvements in the atherogenic lipoprotein profile and in insulin resistance in individuals with MetS.

Lipoprotein subclass profiles in individuals with varying degrees of glucose tolerance: a population-based study of 9399 Finnish men

OBJECTIVES

We investigated serum concentrations of lipoprotein subclass particles and their lipid components determined by proton nuclear magnetic resonance spectroscopy in a population-based study.

DESIGN AND METHODS

A total of 9399 Finnish men were included in the study: 3034 men with normal fasting glucose and normal glucose tolerance; 4345 with isolated impaired fasting glucose (IFG); 312 with isolated impaired glucose tolerance (IGT); 1058 with both IFG and IGT; and 650 with newly diagnosed type 2 diabetes (New DM). Lipoprotein subclasses included chylomicrons (CM) and largest VLDL particles, other VLDL particles (five subclasses), intermediate-density lipoprotein (IDL), LDL (three subclasses) and HDL (four subclasses). The phospholipid, triglyceride (TG), cholesterol, free cholesterol and cholesterol ester levels of the lipoprotein particles were measured.

RESULTS

Abnormal glucose tolerance (especially IGT and New DM) was significantly associated with increased concentrations of VLDL subclass particles and their components (with the exception of very small VLDL particles). After further adjustment for total TGs and HDL cholesterol, increased lipid concentrations in the CM/largest VLDL particles and in most of the other VLDL particles remained significant in individuals with isolated IGT, IFG+IGT and New DM. There was a consistent trend towards a decrease in large and an increase in small HDL particle concentrations in individuals with hyperglycaemia even after adjustment for serum total TGs and HDL cholesterol.

CONCLUSIONS

Abnormal glucose tolerance modifies the concentrations of lipoprotein subclass particles and their lipid components in the circulation and is also related to compositional changes in these particles.

Opportunities for using lipoprotein subclass profile by nuclear magnetic resonance spectroscopy in assessing insulin resistance and diabetes prediction

The incidence of type 2 diabetes mellitus (T2DM) has reached epidemic levels, and current trends indicate that its prevalence will continue to rise. The development of T2DM can be delayed by several years, and may even be prevented, by identifying individuals at risk for T2DM and treating them with lifestyle modification and/or pharmacological therapies. There are a number of methods available for assessing the insulin resistance (IR) that characterizes, and is the precursor to, T2DM. However, current clinical methods for assessing IR, based on measures of plasma glucose and/or insulin are either laborious and time-consuming or show a low specificity. IR manifests its earliest measurable abnormalities through changes in lipoproteins, and thus we propose that by examining lipoprotein subclass profile, it may be possible to alert physicians and patients to a heightened risk of developing diabetes. This will allow us to institute appropriate lifestyle changes and treatment potentially to delay the onset or possibly prevent the progression to diabetes.

Developing high performance lipoprotein density profiling for use in clinical studies relating to cardiovascular disease

Early detection of the beginning stage of cardiovascular disease (CVD) is an approach to prevention because the process is reversible at this stage. Consequently, several methods for screening for CVD have been introduced in recent years incorporating different analytical methods for characterizing the population of blood-borne lipoprotein subclasses. The gold standard method for lipoprotein subclassification is based on lipoprotein density measured by sedimentation equilibrium using the ultracentrifuge. However, this method has not been adopted for clinical studies because of difficulties in achieving the precision required for distinguishing individuals with and without CVD particularly when statistical classification methods are used. The objective of this study was to identify and improve the major factors that influence the precision of measurement of lipoprotein density profile by sedimentation equilibrium analysis and labeling with a fluorescent probe. The study has two phases, each contributing to precision. The first phase focuses on the ultracentrifugation-related variables, and the second phase addresses those factors involved in converting the fluorescent lipoprotein density profile to a digital format compatible with statistical analysis. The overall improvement in precision was on the order of a factor of 5, sufficient to be effectively applied to ongoing classification studies relating to CVD risk assessment.

A differential network approach to exploring differences between biological states: an application to prediabetes

Background

Variations in the pattern of molecular associations are observed during disease development. The comprehensive analysis of molecular association patterns and their changes in relation to different physiological conditions can yield insight into the biological basis of disease-specific phenotype variation.

Methodology

Here, we introduce a formal statistical method for the differential analysis of molecular associations via network representation. We illustrate our approach with extensive data on lipoprotein subclasses measured by NMR spectroscopy in 4,406 individuals with normal fasting glucose, and 531 subjects with impaired fasting glucose (prediabetes). We estimate the pair-wise association between measures using shrinkage estimates of partial correlations and build the differential network based on this measure of association. We explore the topological properties of the inferred network to gain insight into important metabolic differences between individuals with normal fasting glucose and prediabetes.

Conclusions/Significance

Differential networks provide new insights characterizing differences in biological states. Based on conventional statistical methods, few differences in concentration levels of lipoprotein subclasses were found between individuals with normal fasting glucose and individuals with prediabetes. By performing the differential analysis of networks, several characteristic changes in lipoprotein metabolism known to be related to diabetic dyslipidemias were identified. The results demonstrate the applicability of the new approach to identify key molecular changes inaccessible to standard approaches.

Clinical applications of advanced lipoprotein testing in diabetes mellitus

Traditional lipid profiles often fail to fully explain the elevated cardiovascular risk of individuals with diabetes mellitus. Advanced lipoprotein testing offers a novel means to evaluate dyslipidemia and refine risk estimation. Numerous observational studies have demonstrated a characteristic pattern of elevated levels of small, dense LDL particles, out of proportion to traditional lipid levels, in patients with both diabetes mellitus and the metabolic syndrome. Commonly used glucose and lipid-lowering agents have varied effects in patients with diabetes on both LDL and HDL subfractions. The exact role of advanced lipoprotein testing in patients with diabetes mellitus and the metabolic syndrome remains unclear but may offer improved assessment of cardiovascular risk compared with traditional lipid measurements.

Associations among smoking status, lifestyle and lipoprotein subclasses

BACKGROUND

The relationship between cigarette smoking and cardiovascular disease is well established, yet the underlying mechanisms remain unclear. Although smokers have a more atherogenic lipid profile, this may be mediated by other lifestyle-related factors. Analysis of lipoprotein subclasses by the use of nuclear magnetic resonance spectroscopy (NMR) may improve characterisation of lipoprotein abnormalities.

OBJECTIVE

We used NMR spectroscopy to investigate the relationships between smoking status, lifestyle-related risk factors, and lipoproteins in a contemporary cohort.

METHODS

A total of 612 participants (360 women) aged 40-69 years at baseline (1990-1994) enrolled in the Melbourne Collaborative Cohort Study had plasma lipoproteins measured with NMR. Data were analysed separately by sex.

RESULTS

After adjusting for lifestyle-related risk factors, including alcohol and dietary intake, physical activity, and weight, mean total low-density lipoprotein (LDL) particle concentration was greater for female smokers than nonsmokers. Both medium- and small-LDL particle concentrations contributed to this difference. Total high-density lipoprotein (HDL) and large-HDL particle concentrations were lower for female smokers than nonsmokers. The proportion with low HDL particle number was greater for female smokers than nonsmokers. For men, there were few smoking-related differences in lipoprotein measures.

CONCLUSION

Female smokers have a more atherogenic lipoprotein profile than nonsmokers. This difference is independent of other lifestyle-related risk factors. Lipoprotein profiles did not differ greatly between male smokers and nonsmokers.

Fenofibrate concomitantly decreases serum proprotein convertase subtilisin/kexin type 9 and very-low-density lipoprotein particle concentrations in statin-treated type 2 diabetic patients

AIM

Diabetic dyslipidaemia, characterized by hypertriglyceridaemia as a result of elevated serum very-low-density lipoprotein (VLDL) concentrations, contributes to the increased risk of cardiovascular disease (CVD) in type 2 diabetes (T2DM). Proprotein convertase subtilisin/kexin type 9 (PCSK9) may play a role in regulating VLDL metabolism. We investigated the effect of fenofibrate on serum PCSK9 and VLDL particle concentrations in T2DM patients already receiving statin therapy.

METHODS

In a double-blind randomized crossover study, 15 statin-treated T2DM patients (63 +/- 8 years, body mass index (BMI) 29 +/- 3 kg/m(2)) were treated with fenofibrate (145 mg/day) or matching placebo for 12 weeks. Serum PCSK9 concentrations were measured by immunoassay. VLDL particle concentration and size were determined by nuclear magnetic resonance spectroscopy.

RESULTS

Fenofibrate decreased serum triglycerides (-23%), VLDL-triglycerides (-51%), total cholesterol (-11%), LDL-cholesterol (-16%), apolipoprotein B-100 (-16%), apolipoprotein C-III (-20%) and PCSK9 (-13%) concentrations compared with placebo (p < 0.05). Fenofibrate also decreased serum concentrations of large (-45%), medium (-66%) and small VLDL (-67%) particles (p < 0.05), without altering VLDL particle size. Serum PCSK9 reduction correlated with decreases in total (r = 0.526, p = 0.044) and small (r = 0.629, p = 0.021) VLDL particle concentrations.

CONCLUSIONS

Fenofibrate concomitantly decreased serum PCSK9 and VLDL particle concentrations in statin-treated T2DM patients. These findings support a mechanistic link between PCSK9 and VLDL metabolism, possibly through an effect of PSK9 on VLDL receptor degradation.

HDL 2 particles are associated with hyperglycaemia, lower PON1 activity and oxidative stress in type 2 diabetes mellitus patients

OBJECTIVES

In this study we examined the relationship of oxidative stress and hyperglycaemia to antioxidative capacity of high-density cholesterol (HDL-C) particles in type 2 diabetes mellitus (DM).

DESIGN AND METHODS

Oxidative stress status parameters (superoxide anion (O2(-)), superoxide dismutase (SOD) activity and paraoxonase (PON1) status were assessed in 114 patients with type 2 DM and 91 healthy subjects. HDL particle diameters were determined by non-denaturing polyacrylamide gradient (3-31%) gel electrophoresis.

RESULTS

Patients had significantly higher concentrations of oxidative stress parameter O2(-)(p<0.001) and antioxidative defence, SOD activity (p<0.001). Paraoxonase activity was significantly lower in diabetics (p<0.001). The PON1(192) phenotype distribution among study groups was not significantly different. HDL 3 phenotype was significantly prevalent among patients (p<0.001). Paraoxonase activity was significantly lower in patients with predominantly HDL 2 particles than in controls.

CONCLUSIONS

The results of our current study indicate that the diabetic HDL 2 phenotype is associated with hyperglycaemia, lower PON1 activity and elevated oxidative stress.