Non-High-Density Lipoprotein Cholesterol and Guidelines for Cholesterol Lowering in Recent History

Non-HDL Cholesterol May Be Preferred over Apolipoprotein B-100 for Risk Assessment when Evaluated by Receiver Operator Characteristic Curve Analysis

BACKGROUND

Most studies found that apolipoprotein B (apo B)-100 is a superior marker for coronary risk to non-high-density lipoprotein (HDL) cholesterol (C). Usually, studies use multivariant analysis with single-point odds/risk ratios. In multivariant analysis, when variables are highly correlated they are difficult to interpret. Effects cannot be well discriminated.

METHODS

Brief review and examination of diagnostic sensitivity and specificity by receiver operator characteristic (ROC) curves at decision levels so that discrimination can be well compared. Since apo B has additional expense, clinical value should be compared in an appropriate format. Apo B and cholesterols were measured in 382 angiographically defined patients.

RESULTS

Non-HDLC and apo B were stronger markers than low-density lipoprotein (LDL)C, when examined by logistic regression, but as a result of strong collinearity, non-HDLC appeared weaker than LDLC in the presence of apo B, based on P values. This was true when analyzed with and without nonlipid risk factors. On ROC analysis, apo B and non-HDLC showed stronger C statistics than LDLC and total C. When analyzed alone apo B showed about 6.1% greater sensitivity than non-HDLC. After adjustment for nonlipid risk factors, the C statistics for apo B and non-HDLC were 0.74 and 0.73, and there was little difference in diagnostic specificity.

CONCLUSIONS

Risk is calculated from an algorithm that includes nonlipid risk factors similar to those examined here along with cholesterols. When assessed by the 10-year screening algorithm, these data support the view that non-HDLC would be less expensive than apo B with similar clinical efficacy.

Modification of lipoprotein metabolism and function driving atherogenesis in diabetes

Type 2 diabetes mellitus (T2DM) is a chronic metabolic disease, characterized by raised blood glucose levels and impaired lipid metabolism resulting from insulin resistance and relative insulin deficiency. In diabetes, the peculiar plasma lipoprotein phenotype, consisting in higher levels of apolipoprotein B-containing lipoproteins, hypertriglyceridemia, low levels of HDL cholesterol, elevated number of small, dense LDL, and increased non-HDL cholesterol, results from an increased synthesis and impaired clearance of triglyceride rich lipoproteins. This condition accelerates the development of the atherosclerotic cardiovascular disease (ASCVD), the most common cause of death in T2DM patients. Here, we review the alteration of structure, functions, and distribution of circulating lipoproteins and the pathophysiological mechanisms that induce these modifications in T2DM. The review analyzes the influence of diabetes-associated metabolic imbalances throughout the entire process of the atherosclerotic plaque formation, from lipoprotein synthesis to potential plaque destabilization. Addressing the different pathophysiological mechanisms, we suggest improved approaches for assessing the risk of adverse cardiovascular events and clinical strategies to reduce cardiovascular risk in T2DM and cardiometabolic diseases.

Association of non-HDL-C and depression: a cross-sectional analysis of the NHANES data

Objectives

Non-high-density lipoprotein cholesterol (non-HDL-C) has attracted attention because it is associated with a variety of diseases and is easy to measure. However, the relationship between non-HDL-C and depression is still unclear. Our aim was to assess the relationship between non-HDL-C and depression using the cross-sectional NHANES survey from 2005 to 2018.

Methods

We examined the association between non-HDL-C and depression using weighted multivariable logistic regression models and subgroup analysis. Sensitivity analysis demonstrated the robustness of the results.

Results

There were 42,143 participants in this study and 8.6% had depression (weighted 7.53%). Non-HDL-C was higher in participants with depression compared to those without depression (weighted mean 3.64 vs. 3.73, p < 0.01). There was a positive association between non-HDL-C and depression with a 95% OR of 1.22 adjusted for multifactorial (95% CI,1.03-1.45). In subgroup analyses, non-HDL-C was positively associated with depression in men (OR, 1.31; 95% CI, 1.01-1.70), normal BMI (OR: 0.93; 95% CI: 0.66-1.32) and in participants without hypertension (OR, 1.29; 95% CI, 1.01-1.66).

Conclusion

Non-HDL-C positively correlated with depression, and further research may be better for clinical service.

Variability in Plasma Lipids Between Intensive Statin Therapy and Conventional-Dose Statins Combined with Ezetimibe Therapy in Patients with Coronary Atherosclerosis Disease

Dyslipidemia has been widely recognized as a significant risk factor for coronary atherosclerosis disease (CAD). In fact, lipid variability has emerged as a more reliable predictor of cardiovascular events. In this study, we aimed to examine the variability in plasma lipids under two different lipid-lowering regimens (intensive statin therapy versus the combination of conventional-dose statins with ezetimibe). In total, we have retrospectively examined 1275 patients with CAD from January 2009 to April 2019 and divided them into two groups: intensive statin group and conventional-dose statins combined with ezetimibe group. All patients were followed up for at least 1 year. Lipid variability was verified by standard deviation (SD), coefficient of variation (CV), and variability independent of mean (VIM) triple methods. Multiple linear regression and subgroup analyses were performed. In the overall participants, the mean age was 62.3 ± 10.4 years old, and 72.8% were male. Multivariate linear regression analysis indicated that the intensive statin group had lower variability in terms of total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), and non-high-density lipoprotein cholesterol (non-HDL-C) in all SD, CV, and VIM triple methods than statins combined with ezetimibe group (P for all <0.05). Similar results were established in the subgroup analyses based on atorvastatin or rosuvastatin, diabetes mellitus or not, and hypertension or not (P for all < 0.05). Thus, we can conclude that intensive statin therapy could contribute in lowering lipid variability than conventional-dose statins combined with ezetimibe therapy among patients with CAD.

Assessment of Dyslipidemia, Lipid Ratios, and Atherogenic Indices as Cardiovascular Risk Factors in Prediabetic and Diabetic Subjects

Background Uttarakhand is a small state in northern India that comprises mixed population with people dwelling in both hilly and plain areas. Globally, diabetes mellitus (DM) has already been considered to be a pandemic. Furthermore, cardiovascular diseases (CVD) significantly increase mortality and morbidity in patients suffering from DM. Additionally, dyslipidemia has been identified as an important marker in the development of atherosclerosis and ultimately CVD in patients of prediabetes and diabetes. Thus, the identification of subjects with dyslipidemia in prediabetes might be fruitful in lowering their progression to diabetes and ultimately in decreasing incidences of CVD. Hence, this study was undertaken to assess dyslipidemia via the calculation of atherogenic indices (AI) and lipid ratios in prediabetic and diabetic groups attending tertiary care hospital in Uttarakhand.

Materials and Methods This study reviewed retrospective biochemical data of 500 study subjects from e-hospital software of the All India Institute of Medical Sciences, Rishikesh. All study subjects were divided into three groups: 122 controls, 137 prediabetics, and 241 diabetics based on the American Diabetes Association criteria. Study subjects were evaluated for glycated hemoglobin (HbA1c), lipid profile, and AI (total cholesterol [TC]/high-density lipoprotein cholesterol [HDLc], low-density lipoprotein cholesterol [LDLc]/HDLc, TC-HDLc/HDLc, triglycerides [TG]/HDLc).

Results Results showed that TC, TG, LDLc, and AI were significantly higher, and HDLc was significantly decreased in prediabetic and diabetic groups compared with controls. Furthermore, HbA1c showed significant positive correlation with lipid profile and AI except atherogenic coefficient (TC-HDL/HDL).

Conclusion In conclusion, the current study showed the presence of dyslipidemia in both prediabetic and diabetic groups underlining their importance for screening at the prediabetic stage. Hence, we also recommend screening of the prediabetic group for dyslipidemia to arrest the development of early cardiovascular complications.

The association between low-density and non-high-density lipoprotein cholesterol with incident cardiovascular disease among low-risk Iranians during 2 decades follow-up

INTRODUCTION

To examine the associations between low-density and non-high-density lipoprotein cholesterol (LDL-C and non-HDL-C, respectively) with incident cardiovascular disease (CVD) in low-risk subjects.

MATERIALS AND METHODS

From a total of 2476 non-diabetic aged 40-70 years, free of CVD with LDL-C range 1.81≤LDL-C<4.91mmol/L with 10-year atherosclerotic cardiovascular disease (ASCVD) risk <7.5%, the associations of LDL-C and non-HDL-C with incident CVD were assessed using multivariable Cox proportional hazard regression analyses adjusted for age, sex, body mass index, waist circumference, HDL-C, triglycerides, chronic kidney disease, current smoking, hypertension, and family history of CVD.

RESULTS

During a median follow-up of 18 years, 559 CVD events occurred. Compared to the LDL-C <2.59 mmol/L as reference, the categories of 2.59≤LDL-C<3.36, 3.36≤LDL-C<4.14, and ≥4.14 mmol/L were associated with hazard ratios (95% confidence intervals) of 1.39(0.89-2.18), 1.72(1.11-2.68), and 2.19(1.36-3.51) for incident CVD (P for trend<0.0001), respectively. Compared to the non-HDL-C<3.36 as reference, the categories of 3.36≤non-HDL-C<4.14, 4.14≤non-HDL-C<4.91, and ≥4.91 mmol/L were associated with 1.48(0.96-2.30), 1.37(0.89-2.16), and 2.15(1.36-3.39) higher risk for incident CVD (P for trend <0.0001), respectively. Among those with ASCVD score <5% (n=2070), even the 2.59≤LDL-C<3.36 mmol/L increased the risk for CVD [1.73(1.01-2.97)]. Results for non-HDL-C categories remained unchanged except for the category of 4.14≤non-HDL-C<4.91 mmol/L that was not associated with CVD.

CONCLUSIONS

Among Iranian individuals with ASCVD risk as little as <5%, LDL-C≥2.59 mmol/L and non-HDL-C≥3.36 mmol/L, independent of traditional risk factors, were associated with a significantly higher risk of incident CVD, individuals that might potentially benefit from pharmacological therapy.

The U-Shaped Association of Non-High-Density Lipoprotein Cholesterol Levels With All-Cause and Cardiovascular Mortality Among Patients With Hypertension

Background: Non-high-density lipoprotein cholesterol (non-HDL-C) is a valuable indicator in routine blood lipid tests, but the associations of non-HDL-C with mortality in hypertensive population still remain uncertain.

Methods: In the National Health and Nutrition Examination Surveys from 1999 to 2014, participants having hypertension were included and grouped by non-HDL-C levels (<130, 130–159, 160–189, 190–219, and ≥220 mg/dl). Multivariate Cox regression was conducted for calculation of hazard ratios (HR) and 95% confidence interval (CI). To reveal the relationship between non-HDL-C and mortality, Kaplan–Meier survival curves, restricted cubic spline, linear regression, and subgroup analysis were also applied.

Results: A total of 12,169 participants (47.52% males, mean age 57.27 ± 15.79 years) were included. During average follow-up of 92.5 months, 1,946 (15.99%) all-cause deaths and 422 (3.47%) cardiovascular deaths occurred. After adjusting for confounders, the association of non-HDL-C with mortality was detected as U-shaped. Threshold values were observed at 158 mg/dl for all-cause mortality and 190 mg/dl as to cardiovascular mortality. Below the threshold, every 10 mg/dl increment in non-HDL-C attributed to relatively low all-cause mortality significantly (HR = 0.94, 95% CI: 0.92–0.96). Above the threshold, non-HDL-C has significant positive associations with both all-cause (HR = 1.03, 95% CI: 1.01–1.05) and cardiovascular mortality (HR = 1.09, 95% CI: 1.05–1.14). For subgroups analysis, similar results were found among participants age <65 years old, non-white population, those were not taking lipid-lowering drugs, and subjects with body mass index (BMI) ≥25 kg/m².

Conclusion: The U-shaped association was detected between non-HDL-C and mortality among hypertensive population.

Evaluation of twelve formulas for LDL-C estimation in a large, blinded, random Italian population

BACKGROUND AND AIMS

Low-density lipoprotein-cholesterol (LDL-C) is the major determinant of cardiovascular disease (CVD) burden. Being the direct assays time consuming, expensive, not fully standardized and not worldwide available, indirect formulas represent the most used laboratory estimation of LDL-C. In this study we analyzed the accuracy of twelve formulas for LDL-C estimation in an Italian population of 114,774 individuals.

METHODS

All lipid samples were analyzed using direct homogeneous assay. The population was divided into various subgroups based on triglycerides and directly dosed LDL-C (D-LDL) levels. Twelve formulas (Friedewald, DeLong, Hata, Hattori, Puavillai, Anandaraja, Ahmadi, Chen, Vujovic, de Cordova, Martin, and Sampson) were compared in terms of their mean absolute deviations and the correlation and concordance of their estimated LDL-C with the respective D-LDL values.

RESULTS

LCL-C measured by Friedewald formula and direct assay differed by more than 9 mg/dL. For D-LDL>115 mg/dl, we observed a concordance rate of only 55% between Friedewald and the respective D-LDL values. For TG<250 mg/dl, the proportion of reclassification between the different formulas and D-LDL was 14.1% with Vujovic, 14.4% Sampson, 15.9% DeLong, 16.5% Puavilai, 19.9% Martin, 21.9% Friedewald, 23.5% Chen, 29% Anandaraja, 31.1% Ahmadi, 31.5% Hata, 33.2% Hattori, and 44.4% with De Cordova formula.

CONCLUSIONS

Our study compared for the first time 12 different LDL-C formulas on a Southern European population of more than 100,000 people. 'Several formulas showed better accuracy compared to Friedewald. Sampson, Martin and Vujovic resulted the most accurate formulas.