LDL particle size and number compared with LDL cholesterol and risk categorization in end-stage renal disease patients

Estimated small dense low-density lipoprotein cholesterol and nonalcoholic fatty liver disease in nonobese populations

AIMS/INTRODUCTION

To explore the association between estimated small dense low-density lipoprotein cholesterol (sdLDL-C) and the risk of incident nonalcoholic fatty liver disease (NAFLD) in nonobese populations.

MATERIALS AND METHODS

This study included participants who underwent health checkups in 2014 and were followed up until 2019. We carried out Cox proportional hazards regression analyses to evaluate the association of estimated sdLDL-C with NAFLD. Discordance analyses were carried out to estimate the relative NAFLD risk in estimated sdLDL-C versus low-density lipoprotein cholesterol (LDL-C) discordant/concordant groups. Estimated sdLDL-C was calculated by equations based on LDL-C and triglycerides. The diagnosis of NAFLD was based on the presence of abdominal ultrasonography after excluding other causes of chronic liver disease.

RESULTS

Over a mean follow-up period of 26,694 person-years, 844 incident NAFLD cases were recorded. Compared with the first quartile of estimated sdLDL-C, the fourth quartile was associated with a 2.933-fold increased risk of NAFLD (95% confidence interval 2.095-4.107). With the increase in estimated sdLDL-C, the risk of NAFLD gradually increased both in participants within the normal range of LDL-C (hazard ratio 2.854, 95% confidence interval 1.650-5.617) and beyond the normal range of LDL-C (hazard ratio 2.636, 95% confidence interval 1.263-5.502). In addition, the inconsistent high estimated sdLDL-C/low LDL-C group was associated with an increased risk of NAFLD, but not the low estimated sdLDL-C/high LDL-C group.

CONCLUSIONS

Estimated sdLDL-C was positively associated with the risk of incident NAFLD in a nonobese population, independent of LDL-C.

A network analysis of depressive symptoms and metabolomics

BACKGROUND

Depression is associated with metabolic alterations including lipid dysregulation, whereby associations may vary across individual symptoms. Evaluating these associations using a network perspective yields a more complete insight than single outcome-single predictor models.

METHODS

We used data from the Netherlands Study of Depression and Anxiety (N = 2498) and leveraged networks capturing associations between 30 depressive symptoms (Inventory of Depressive Symptomatology) and 46 metabolites. Analyses involved 4 steps: creating a network with Mixed Graphical Models; calculating centrality measures; bootstrapping for stability testing; validating central, stable associations by extra covariate-adjustment; and validation using another data wave collected 6 years later.

RESULTS

The network yielded 28 symptom-metabolite associations. There were 15 highly-central variables (8 symptoms, 7 metabolites), and 3 stable links involving the symptoms Low energy (fatigue), and Hypersomnia. Specifically, fatigue showed consistent associations with higher mean diameter for VLDL particles and lower estimated degree of (fatty acid) unsaturation. These remained present after adjustment for lifestyle and health-related factors and using another data wave.

CONCLUSIONS

The somatic symptoms Fatigue and Hypersomnia and cholesterol and fatty acid measures showed central, stable, and consistent relationships in our network. The present analyses showed how metabolic alterations are more consistently linked to specific symptom profiles.

Low-density lipoprotein cholesterol to apolipoprotein B ratio predicts mortality and cardiovascular events in peritoneal dialysis patients

PURPOSE

The ratio of low-density lipoprotein cholesterol (LDL-C)/apolipoprotein B (apo B) is associated with all-cause mortality and cardiovascular events in chronic kidney disease patients. The aim of this study was to investigate the association between the LDL-C/apo B ratio (LAR) and all-cause mortality and cardiovascular events in peritoneal dialysis (PD) patients.

METHODS

A total of 1199 incident PD patients were enrolled from November 1, 2005 to August 31, 2019. The LAR was used to divide the patients into two groups by X-Tile software and restricted cubic splines using 1.04 as the cutoff. The incidence of all-cause mortality and cardiovascular events at follow-up was compared according to LAR.

RESULTS

Of the 1199 patients, 58.0% were men, the mean age was 49.3 ± 14.5 years, 225 patients had a history of diabetes, and 117 patients had prior cardiovascular disease. During the follow-up period, 326 patients died, and 178 patients experienced cardiovascular events. After full adjustment, a low LAR was significantly associated with HRs for all-cause mortality of 1.37 (95% CI 1.02-1.84, P = 0.034) and for cardiovascular events of 1.61 (95% CI 1.10-2.36, P = 0.014).

CONCLUSION

This study suggests that a low LAR is an independent risk factor for all-cause mortality and cardiovascular events in PD patients, indicating that the LAR may provide significant information when assessing all-cause mortality and cardiovascular risks.

Advanced lipoprotein parameters could better explain atheromatosis in non-diabetic chronic kidney disease patients

Background

Chronic kidney disease (CKD) patients have a high burden of atheromatous cardiovascular disease (ASCVD) not fully explained by traditional lipid parameters. Lipoprotein composition and subclass particle number information could improve ASCVD risk assessment. The objective of this study is to investigate the association of advanced lipoprotein parameters with the risk of atheromatosis in a subpopulation of the NEFRONA study.

Methods

This was a cross-sectional study in 395 non-diabetic individuals (209 CKD and 186 non-diabetic and non-CKD) without statin therapy. Vascular ultrasound examination assessing 10 territories was combined with advanced lipoprotein testing performed by nuclear magnetic resonance spectroscopy. Logistic regression was used to estimate adjusted odds ratios (ORs) per 1 standard deviation increment.

Results

Atheromatosis was more prevalent in CKD patients (33.9% versus 64.6%). After adjusting for age, gender, smoking habit and CKD stage, the amount of triglycerides (TGs) within low-density lipoprotein (LDL) lipoproteins was independently and positively associated with atheromatosis [OR 1.33; 95% confidence interval (CI) 1.03–1.74; P = 0.03]. Similarly, total and medium LDL particles (LDL-Ps) showed a positive association (OR 1.29; 95% CI 1.00–1.68; P = 0.05 and OR 1.34; 95% CI 1.04–1.75; P = 0.03, respectively). TG-loaded medium LDL-Ps were higher in CKD patients compared with controls and showed an adjusted OR of 1.40 (95% CI 1.09–1.82; P = 0.01) in non-diabetic patients (CKD and non-CKD individuals). In contrast, non-diabetic CKD patients showed a similar coefficient but the significance was lost (OR 1.2; 95% CI 0.8–1.7; P = 0.359).

Conclusions

Non-diabetic CKD patients showed a higher amount of TG-loaded medium LDL-Ps compared with controls. These particles were independently associated with atheromatosis in non-diabetic patients.

Proinflammatory and Hyperinsulinemic Dietary Patterns Are Associated With Specific Profiles of Biomarkers Predictive of Chronic Inflammation, Glucose-Insulin Dysregulation, and Dyslipidemia in Postmenopausal Women

Background: Dietary patterns promoting hyperinsulinemia and chronic inflammation, including the empirical dietary index for hyperinsulinemia (EDIH) and empirical dietary inflammatory pattern (EDIP), have been shown to strongly influence risk of weight gain, type 2 diabetes, cardiovascular disease, and cancer. EDIH was developed using plasma C-peptide, whereas EDIP was based on plasma C-reactive protein (CRP), interleukin-6, and tumor necrosis factor alpha receptor 2 (TNF-αR2). We investigated whether these dietary patterns were associated with a broader range of relevant biomarkers not previously tested. Methods: In this cross-sectional study, we included 35,360 women aged 50-79 years from the Women's Health Initiative with baseline (1993-1998) fasting blood samples. We calculated EDIH and EDIP scores from baseline food frequency questionnaire data and tested their associations with 40 circulating biomarkers of insulin response/insulin-like growth factor (IGF) system, chronic systemic inflammation, endothelial dysfunction, lipids, and lipid particle size. Multivariable-adjusted linear regression was used to estimate the percent difference in biomarker concentrations per 1 standard deviation increment in dietary index. FDR-adjusted p < 0.05 was considered statistically significant. Results: Empirical dietary index for hyperinsulinemia (EDIH) and empirical dietary inflammatory pattern (EDIP) were significantly associated with altered concentrations of 25 of the 40 biomarkers examined. For EDIH, the percent change in biomarker concentration in the insulin-related biomarkers ranged from +1.3% (glucose) to +8% (homeostatic model assessment for insulin resistance) and -9.7% for IGF-binding protein-1. EDIH impacted inflammation and endothelial dysfunction biomarkers from +1.1% (TNF-αR2) to +7.8% (CRP) and reduced adiponectin by 2.4%; and for lipid biomarkers: +0.3% (total cholesterol) to +3% (triglycerides/total cholesterol ratio) while reducing high-density lipoprotein cholesterol by 2.4%. EDIP showed a similar trend of associations with most biomarkers, although the magnitude of association was slightly weaker for the insulin-related biomarkers and stronger for lipids and lipid particle size. Conclusions: Dietary patterns with high potential to contribute to insulin hypersecretion and to chronic systemic inflammation, based on higher EDIH and EDIP scores, were associated with an unfavorable profile of circulating biomarkers of glucose-insulin dysregulation, chronic systemic inflammation, endothelial dysfunction and dyslipidemia. The broad range of biomarkers further validates EDIH and EDIP as mechanisms-based dietary patterns for use in clinical and population-based studies of metabolic and inflammatory diseases.

Small dense low-density lipoprotein-cholesterol (sdLDL-C): Analysis, effects on cardiovascular endpoints and dietary strategies

Lipid profile screening is crucial for the prevention, evaluation and treatment of cardiovascular (CV) disease (CVD). Small dense low-density lipoprotein-cholesterol (sdLDL-C) is an emerging biomarker associated with CVD and several comorbidities. The aim of this literature review is to discuss the potential importance of sdLDL-C as a surrogate biomarker for managing CVD by explaining its pathophysiology and promising treatments. The current synthesis demonstrates the impact of sdLDL-C on CV ailments, which are related to arterial pathologies and dysregulated lipid profiles. Several drug classes used for the treatment of dyslipidemia decrease the sdLDL-C concentrations. For instance, statins, fibrates, ezetimibe, nicotinic acid, resin and orlistat are pharmacological sdLDL-C-lowering agents. Regarding nutritional strategies, simple carbohydrate types, such as fructose, are common in Western diets and should be reduced or avoided due to their potential in increasing synthesis of sdLDL-C subclasses. Dairy products, avocado, pistachios, soy-based diet (except for hydrogenated soybean oil) and corn oil seem to be suitable food choices for a therapeutic diet aiming to control sdLDL-C concentrations. However, thus far dietary supplementation with omega-3 fatty acids is unsubstantiated for decreasing sdLDL-C concentration. In conclusion, coupled with the traditional lipid profile, measurement or even the estimation of sdLDL-C as a routine screening should be encouraged, whereas more insights into the control of sdLDL-C are imperative. Appropriate clinical reference ranges for sdLDL-C are also needed.

Nutrition, lipidic parameters, and cancer risk and progress

The aim of this literature review is to analyze the association between lipidic parameters and cancer risk and progression, as there is no clear evidence that the risk or advancement of cancer increases with cholesterol levels. Some works suggest a positive, others a negative, and still others a neutral correlation between cancer advancement or risk and cholesterol-related parameters. This lack of a simple relationship indicates the need for a more complex, multi-variable, non-linear framework correlating lipid and cancer parameters, as well as the likely existence of optimum values of lipid parameters that may pave the way to cancer therapeutic strategies that include clinical nutrition.

Lipids, Apolipoproteins, and Risk of Atherosclerotic Cardiovascular Disease in Persons With CKD

RATIONALE & OBJECTIVE

A large residual risk for atherosclerotic cardiovascular disease (ASCVD) remains in the setting of chronic kidney disease (CKD) despite treatment with statins. We sought to evaluate the associations of lipid and apolipoprotein levels with risk for ASCVD in individuals with CKD.

STUDY DESIGN

Prospective cohort study.

SETTINGS & PARTICIPANTS

Adults aged 21 to 74 years with non-dialysis-dependent CKD at baseline enrolled in the Chronic Renal Insufficiency Cohort (CRIC) Study in 7 clinical study centers in the United States.

PREDICTOR

Baseline total cholesterol, non-high-density lipoprotein cholesterol (non-HDL-C), very low-density lipoprotein cholesterol (VLDL-C), triglycerides, low-density lipoprotein cholesterol (LDL-C), apolipoprotein B (Apo-B), HDL-C, and apolipoprotein AI (Apo-AI) values stratified into tertiles.

OUTCOME

A composite ASCVD event of myocardial infarction or ischemic stroke.

ANALYTIC APPROACH

Multivariable Cox proportional hazards regression to estimate the risk for ASCVD for each tertile of lipoprotein predictor.

RESULTS

Among 3,811 CRIC participants (mean age, 57.7 years; 41.8% white), there were 451 ASCVD events during a median follow-up of 7.9 years. There was increased ASCVD risk among participants with VLDL-C levels in the highest tertile (HR, 1.28; 95% CI, 1.01-1.64), Apo-B levels in the middle tertile (HR, 1.30; 95% CI, 1.03-1.64), HDL-C levels in the middle and lowest tertiles (HRs of 1.40 [95% CI, 1.08-1.83] and 1.77 [95% CI, 1.35-2.33], respectively), and Apo-AI levels in the middle and lowest tertiles (HRs of 1.77 [95% CI, 1.02-1.74] and 1.77 [95% CI, 1.36-2.32], respectively). LDL-C level was not significantly associated with the ASCVD outcome in this population (HR, 1.00 [95% CI, 0.77-1.30] for the highest tertile).

LIMITATIONS

Associations based on observational data do not permit inferences about causal associations.

CONCLUSIONS

Higher VLDL-C and Apo-B levels, as well as lower HDL-C and Apo-AI levels, are associated with increased risk for ASCVD. These findings support future investigations into pharmacologic targeting of lipoproteins beyond LDL-C, such as triglyceride-rich lipoproteins, to reduce residual risk for ASCVD among individuals with CKD.

An in-depth analysis shows a hidden atherogenic lipoprotein profile in non-diabetic chronic kidney disease patients

Background: Chronic kidney disease (CKD) is an independent risk factor for atherosclerotic disease. We hypothesized that CKD promotes a proatherogenic lipid profile modifying lipoprotein composition and particle number. Methods: Cross-sectional study in 395 non-diabetic individuals (209 CKD patients and 186 controls) without statin therapy. Conventional lipid determinations were combined with advanced lipoprotein profiling by nuclear magnetic resonance, and their discrimination ability was assessed by machine learning. Results: CKD patients showed an increase of very-low-density (VLDL) particles and a reduction of LDL particle size. Cholesterol and triglyceride content of VLDLs and intermediate-density (IDL) particles increased. However, low-density (LDL) and high-density (HDL) lipoproteins gained triglycerides and lost cholesterol. Total-Cholesterol, HDL-Cholesterol, LDL-Cholesterol, non-HDL-Cholesterol and Proprotein convertase subtilisin-kexin type (PCSK9) were negatively associated with CKD stages, whereas triglycerides, lipoprotein(a), remnant cholesterol, and the PCSK9/LDL-Cholesterol ratio were positively associated. PCSK9 was positively associated with total-Cholesterol, LDL-Cholesterol, LDL-triglycerides, LDL particle number, IDL-Cholesterol, and remnant cholesterol. Machine learning analysis by random forest revealed that new parameters have a higher discrimination ability to classify patients into the CKD group, compared to traditional parameters alone: area under the ROC curve (95% CI), .789 (.711, .853) vs .687 (.611, .755). Conclusions: non-diabetic CKD patients have a hidden proatherogenic lipoprotein profile.

Regulation of low-density lipoprotein subfractions by carbohydrates

PURPOSE OF REVIEW

This article aims at reviewing the recent findings that have been made concerning the crosstalk of carbohydrate metabolism with the generation of small, dense low-density lipoprotein (LDL) particles, which are known to be associated with an adverse cardiovascular risk profile.

RECENT FINDINGS

Studies conducted during the past few years have quite unanimously shown that the quantity of carbohydrates ingested is associated with a decrease of LDL particle size and an increase in its density. Conversely, diets that aim at a reduction of carbohydrate intake are able to improve LDL quality. Furthermore, a reduction of the glycaemic index without changing the amount of carbohydrates ingested has similar effects. Diseases with altered carbohydrate metabolism, for example, type 2 diabetes, are associated with small, dense LDL particles. Finally, even the kind of monosaccharide the carbohydrate intake consists of is important concerning LDL particle size: fructose has been shown to alter the LDL particle subclass profile more adversely than glucose in many recent studies.

SUMMARY

LDL particle quality, rather than its quantity, is affected by carbohydrate metabolism, which is of clinical importance, in particular, in the light of increased carbohydrate consumption in today's world.