Triglyceride-Rich Lipoprotein Cholesterol, Small Dense LDL Cholesterol, and Incident Cardiovascular Disease

Duran, Edward K.; Aday, Aaron W.; Cook, Nancy R.; Buring, Julie E.; Ridker, Paul M.; Pradhan, Aruna D.

doi:10.1016/j.jacc.2020.02.059

Cited by 199 publications

(164 citation statements)

References 61 publications

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“…Sd-LDL-C values were most closely correlated with carotid artery intima-media thickness among lipid parameters tested [29]. In the recent epidemiological studies, sdLDL-C values are associated with increased risk of CV events [8,30] and incident myocardial infarction [31]. Consistently, in our large-scale prospective study of diabetic patients, we could clearly demonstrate that sdLDL-C is the good predictor of incident CV events among lipid parameters.…”

Section: Lipid Markers For Predicting CV Eventssupporting

confidence: 88%

“…One study has reported that ApoB/A1 is superior to LDL-C as a marker for predicting CV events [2]. More recently, LDL-C has been subdivided into granular fractions, among which small dense LDL-C (sdLDL-C) with a smaller particle size has attracted attention as a lipid marker that may be more sensitive for predicting CV events than LDL-C [7,8]. LDL-C with a smaller particle size is more easily oxidized and permeable to the cell wall [9], promoting atherosclerotic changes more than LDL-C with a larger particle size, so called large buoyant LDL-C (lbLDL-C).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Small dense low-density lipoprotein cholesterol is an effective target marker for predicting cardiovascular events and laser treatment for retinopathy in diabetic patients

Nakayama

Morita

Sato

et al. 2020

Preprint

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Background Small dense low-density lipoprotein cholesterol (sdLDL-C) has been recently reported as a sensitive marker for cardiovascular diseases. Objective We explored the superiority of sdLDL-C as a marker for predicting cardiovascular (CV) events and the need for laser treatment in patients with hypercholesterolemia and diabetic retinopathy. Methods We performed a sub-analysis of the intEnsive statin therapy for hyper-cholesteroleMic Patients with diAbetic retinopaTHY (EMPATHY) study (n = 5042), in which patients were assigned randomly to intensive or standard statin therapy targeting low-density lipoprotein cholesterol < 70 mg/dl or 100–120 mg/dl. Using the Cox hazard analysis and Kaplan-Meier analysis, the risks for CV events and the need for laser treatment were evaluated according to the following lipids: total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, triglycerides, apolipoprotein A1, apolipoprotein B (ApoB), and sdLDL-C one year after registration. Results The patients were 63 ± 11 years old and 48% of them were male. LDL-C and sdLDL-C levels were 98 ± 25 and 32 ± 14 mg/dl, respectively, one year after registration. The sdLDL-C level had a strong positive correlation with ApoB level (r = 0.83). SdLDL-C was a sensitive marker for predicting CV events when comparing among the quartiles according to sdLDL-C levels (hazard ratios: HR for quartiles 1–4 were 1.0, 1.4, 1.6, and 2.5, respectively; p for trend < 0.01). Also, sdLDL-C was a sensitive marker for predicting the need for laser treatment among lipids (log rank, p = 0.009), especially in patients with elderly (> 65 yrs) and obesity (BMI > 25 kg/m2). Conclusions SdLDL-C is a sensitive target marker to predict cardiovascular events as well as the need for laser treatment in patients with hypercholesterolemia and diabetic retinopathy. Trial registration: UMIN000003486, www.umin.ac.jp/ctr/.

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Section: Lipid Markers For Predicting CV Eventssupporting

confidence: 88%

Section: Introductionmentioning

confidence: 99%

Small dense low-density lipoprotein cholesterol is an effective target marker for predicting cardiovascular events and laser treatment for retinopathy in diabetic patients

Nakayama

Morita

Sato

et al. 2020

Preprint

View full text Add to dashboard Cite

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“…Recently, increased TRL-C levels were found to be associated with increased CV risk. [21][22][23] Mendelian randomization (MR) studies demonstrated that genetic variants that mimic LDL-C-lowering therapies and TG-lowering therapies were associated with the same reduction in ASCVD risk for the same change in apoB concentration, despite being associated with markedly different changes in plasma LDL-C or TG concentrations. 4 In RCTs, TGlowering has been associated with a lower risk of major vascular events, even after adjustment for LDL-C-lowering.…”

Section: Ezetimibementioning

confidence: 99%

New Trends in Dyslipidemia Treatment

Jang

Lim

et al. 2021

Circ J

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“…Although LDL has long been recognized as a primary associated risk factor for cardiovascular disease (CVD) [ 1 , 3 , 4 , 5 ], a lengthening list of LP subpopulations is of interest in the pathogenesis of arterial disease. These include small dense LDL (sdLDL) [ 6 , 7 ], lipoprotein (a) (Lp(a)) [ 8 , 9 ], and remnant lipoproteins (RLPs). sdLDL (18.0–20.5 nm) [ 10 ] is proposed to be more atherogenic than LDL by means of its small size, which could enhance penetration into the vessel wall.…”

Section: Introductionmentioning

confidence: 99%

Developing Electron Microscopy Tools for Profiling Plasma Lipoproteins Using Methyl Cellulose Embedment, Machine Learning and Immunodetection of Apolipoprotein B and Apolipoprotein(a)

Giesecke

Soete

Mackinnon

et al. 2020

IJMS

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Plasma lipoproteins are important carriers of cholesterol and have been linked strongly to cardiovascular disease (CVD). Our study aimed to achieve fine-grained measurements of lipoprotein subpopulations such as low-density lipoprotein (LDL), lipoprotein(a) (Lp(a), or remnant lipoproteins (RLP) using electron microscopy combined with machine learning tools from microliter samples of human plasma. In the reported method, lipoproteins were absorbed onto electron microscopy (EM) support films from diluted plasma and embedded in thin films of methyl cellulose (MC) containing mixed metal stains, providing intense edge contrast. The results show that LPs have a continuous frequency distribution of sizes, extending from LDL (> 15 nm) to intermediate density lipoprotein (IDL) and very low-density lipoproteins (VLDL). Furthermore, mixed metal staining produces striking “positive” contrast of specific antibodies attached to lipoproteins providing quantitative data on apolipoprotein(a)-positive Lp(a) or apolipoprotein B (ApoB)-positive particles. To enable automatic particle characterization, we also demonstrated efficient segmentation of lipoprotein particles using deep learning software characterized by a Mask Region-based Convolutional Neural Networks (R-CNN) architecture with transfer learning. In future, EM and machine learning could be combined with microarray deposition and automated imaging for higher throughput quantitation of lipoproteins associated with CVD risk.

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Triglyceride-Rich Lipoprotein Cholesterol, Small Dense LDL Cholesterol, and Incident Cardiovascular Disease

Cited by 199 publications

References 61 publications

Small dense low-density lipoprotein cholesterol is an effective target marker for predicting cardiovascular events and laser treatment for retinopathy in diabetic patients

Small dense low-density lipoprotein cholesterol is an effective target marker for predicting cardiovascular events and laser treatment for retinopathy in diabetic patients

New Trends in Dyslipidemia Treatment

Developing Electron Microscopy Tools for Profiling Plasma Lipoproteins Using Methyl Cellulose Embedment, Machine Learning and Immunodetection of Apolipoprotein B and Apolipoprotein(a)

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