LDL Phenotype Research Articles

To Determine LDL Phenotypes Using Lipids, Lipoproteins, Apoproteins, and sdLDL Through Association Rule Mining

To Determine LDL Phenotypes Using Lipids, Lipoproteins, Apoproteins, and sdLDL Through Association Rule Mining

The association of Sort1 expression with LDL subfraction and inflammation in patients with coronary artery disease

Background Controversial effect of sortilin on lipoprotein metabolism in the development of atherosclerosis reveals the need for more extensive research Objectives The aim of this study was to investigate the association between Sort1 gene expression and lipids, lipoprotein subfractions, and inflammation in CAD. Methods The study population included 162 subjects with CAD and 49 healthy individuals. The Sort1 gene expression level was determined by qRT-PCR using Human Sortilin TaqMan Gene Expression Assays. Lipoprotein subclasses were analysed by the Lipoprint system. Serum levels of apolipoprotein and CRP were measured by autoanalyzer. Results Sort1 gene expression and atherogenic subfraction (SdLDL) levels were significantly higher (p < 0.001) while atheroprotective subfraction (LbLDL) was lower in the subjects with CAD (p < 0.050). Also, increased Sort1 gene expression levels were observed in those with higher CRP values. Conclusions Our findings reveal that the high Sort1 gene expression has a prominent linear relationship with both the atherogenic LDL phenotype and proinflammation, thereby might contribute to the occurrence of CAD.

P24-041-23 Effects of LDL Phenotype and Differences in Risk Stratification in Response to Dairy Fat Consumption

P24-041-23 Effects of LDL Phenotype and Differences in Risk Stratification in Response to Dairy Fat Consumption

Atherogenicity of low-density lipoproteins after switching from a protease inhibitor to dolutegravir: a substudy of the NEAT022 study.

The aim of this study was to investigate whether switching from a ritonavir-boosted PI-based regimen to a dolutegravir-based regimen improved the atherogenic properties of LDL particles in patients with HIV. This was a substudy of the NEAT022 study (ClinicalTrials.gov NCT02098837). Adults with HIV with a Framingham score >10% or aged >50 years and being treated with a stable boosted PI-based regimen were randomized to either switch to dolutegravir or continue with boosted PI. At baseline and Week 48, we assessed atherogenic LDL properties: LDL particle size and phenotype (A, intermediate, B), oxidized LDL (ox-LDL) and lipoprotein-associated phospholipase A2 (Lp-PLA2) activity. Eighty-six participants (dolutegravir 44; PI 42) were included. Participants had a median (IQR) age of 54 (51-57) years and 79.1% were male. In the dolutegravir arm, after 48 weeks, we observed: (1) an increase in LDL size [median 1.65 Å (IQR -0.60 to 4.20); P = 0.007], correlated with the decrease in triglyceride concentration [Spearman correlation = -0.352 (P = 0.001)], with a corresponding decrease of subjects with atherogenic LDL phenotype B (36.4% to 20.5%; P = 0.039); (2) a decrease in Lp-PLA2 activity [median 1.39 μmol/min/mL (IQR -2.3 to 0.54); P = 0.002]; and (3) a decrease in ox-LDL [median 14 U/L (IQR -102 to 13); P = 0.006]. In the PI arm, none of these favourable lipid modifications was observed. Forty-eight weeks after switching from a PI-based to a dolutegravir-based regimen, patients with Framingham score >10% or aged >50 years showed improvement of several atherogenic lipid features, including LDL particle phenotype, ox-LDL and Lp-PLA2.

Performance of Different LDL-C Equations in an Intervention Improving Atherogenic Dyslipidemia in Participants with Type 2 Diabetes

<h3>Lead Author's Financial Disclosures</h3> S.J.A. is an employee of Virta Health and offered stock options from Virta Health. <h3>Study Funding</h3> None. <h3>Background/Synopsis</h3> LDL-C estimated using the Friedewald equation (LDL-CF) is limited in type 2 diabetes (T2D) due to hypertriglyceridemia (HTG). In our recent study of 262 patients with T2D, a low carbohydrate intervention with nutritional ketosis significantly improved atherogenic dyslipidemia (ALP) in participants with T2D, where a majority of the participants transitioned from a predominantly small, dense LDL phenotype (phenotype B) to a large, buoyant LDL phenotype (phenotype A). However, the improvement in ALP was associated with an increase in LDL-CF. <h3>Objective/Purpose</h3> This study assessed differences between LDL-CF versus other recently adopted LDL-C equations to estimate the effect of our intervention on LDL-C, and assess the performance of these equations across a broad range of HTG. <h3>Methods</h3> LDL-C were recalculated using Martin-Hopkins (LDL-CMH) and the new proposed NIH 2 (LDL-CN2) equations. The effect size of the intervention on LDL-C change from baseline to 2 years was assessed using each LDL-C equation with repeated measure ANOVA. Since LDL-CN2 is recommended for use with triglycerides (TG) up to 800mg/dL, we calculated LDL-C with this equation using two cut-offs: TG≤400mg/dL and TG≤800mg/dL. We then assessed the differences between LDL-CMH, LDL-CN2 and LDL-CF at each time point among those with TG≤400mg/dL using a linear mixed effect model (LMM) and covariates that were initially used for the assessment of LDL-CF (Table 1). <h3>Results</h3> There was an increase in LDL-C in all three LDL-C equations, with medium effect sizes in both LDL-CF (ηp2=0.08, +13.5% from 100.9mg/dL) and LDL-CN2 (ηp2 =0.07 for TG≤400mg/dL, +11.6% from 104.8mg/dL or ηp2 =0.06 for TG≤800mg/dL, +10.7% from 104.6mg/dL) and a small effect with LDL-CMH (ηp2=0.04, +9.2% from 106.5mg/dL). At baseline, LDL-CMH estimated significantly greater LDL-C than the other two equations, especially in individuals with HTG and phenotype B (Table 1). At 1 and 2 years when the proportion of individuals with ALP and HTG significantly decreased in the intervention, there were no significant differences in the estimated LDL-C between the equations. <h3>Conclusions</h3> In patients with T2D where HTG is a common lipid abnormality, LDL-CMH may be the most appropriate equation to use in assessing change in LDL-C. For patients with greater than 400mg/dL of TG, LDL-CN2 can be alternatively considered. Future studies should compare these equations with direct LDL-C measurements in patients with T2D.

Analysis of pleiotropic genetic effects on cognitive decline and systemic inflammation in the Women’s Health Initiative Memory Study

SNPs associated with C-reactive protein (CRP) and plasma lipids have been investigated for polygenic overlap with Alzheimer's disease (AD) risk SNPs. Previously, we reported pleiotropic effects between SNPs associated with cognitive impairment (CI) and SNPs associated with systemic inflammation as measured by CRP and plasma lipids in the Health and Retirement Study (HRS). We sought to replicate our results in the Women's Health Initiative Memory Study (WHIMS). Analysis of SNP pleiotropic effects was completed using data from 6,078 non-Hispanic White women (aged 71.4 [SD 7.4] at baseline) for whom genetic, cognitive, and/or biomarker data were available. We identified CI using WHIMS adjudicated case status (normal vs. mild cognitive impairment or probable dementia). Secondary phenotypes included baseline CRP and plasma lipid levels (HDL, LDL, and total cholesterol [TC]). Genome-wide association analyses were conducted for all phenotypes. A conditional false discovery rate framework defined genetic pleiotropy. Genetic pleiotropy was identified if SNPs were associated with CI conditional on association with secondary phenotypes (CRP, HDL, LDL, TC) at an FDR < 0.05. Functional genomic bioinformatics analysis and comparison with prior findings were conducted. Genetic pleiotropy was observed for CI conditional on association with the secondary phenotypes of plasma CRP, HDL, LDL, and TC. These results replicate associations for SNPs in the APOE, APOC1, PVRL2/NECTIN2 loci reported in the prior HRS study for CRP, LDL, TC. The odds ratios for the association of these SNPs with CI ranged from 0.5 to 4.0, consistent with moderate effect sizes for the APOE ε2 or ε4 alleles. For WHIMS, FDR significant results were observed in both directions for several of the traits (CRP, lipids), further supporting evidence of genetic pleiotropy. Moreover, we observed associations for SNPs in the APOE, APOC1, PVRL2/NECTIN2 loci for CI conditional on HDL. We identified polygenic overlap between CI and CRP, LDL, HDL, and TC phenotypes in WHIMS, largely replicating prior results in the HRS. The variants and associated genes identified are involved in pathological processes including metabolic, cardiovascular, and immune response and are potentially important for AD risk prediction and development of therapeutic approaches based on anti-inflammatory mechanisms.

Low-Density Lipoprotein Subfractionation: What Is the Role of the Lab When Reporting Discrepant Results?

Abstract Plasma concentrations of low-density-lipoprotein cholesterol (LDL-C) are directly associated with risk for coronary artery disease (CAD). Multisociety guidelines define LDL-C&amp;gt;160mg/dL as a risk factor for CAD and LDL-C&amp;gt;190mg/dL as an indication for lipid lowering medication, regardless of other clinical factors. Subfractionation of LDL according to size (LDL-s) enables differentiation between two LDL phenotypes: large-buoyant LDL and small-dense LDL. The small-dense LDL phenotype reportedly conveys increased risk for CAD. Major societies do not recommend LDL subfractions be used for clinical decision making and most payers do not cover LDL subfraction testing. Despite these restrictions, LDL subfraction is routinely requested by clinicians. Nuclear magnetic resonance (NMR) spectroscopy measures LDL-C and LDL-s. Following inquiries regarding interpretation of conflicting LDL-C and LDL-s results, we investigated associations between LDL-C and LDL-s measured by NMR in order to determine how often they provide contradicting or additive information. Verification of NMR LDL-C accuracy was confirmed by ß-quantification in a subset of patient samples (n=250). The average bias was -4.5mg/dL and the correlation coefficient was 0.92. High-risk was defined as LDL-C&amp;gt;160mg/dL or LDL-s&amp;lt;20.5 nm (small-dense LDL); and low-risk was defined as LDL-C&amp;lt;70mg/dL or LDL-s&amp;gt;20.5nm (large-buoyant LDL). In 26,710 clinical NMR analyses, the median LDL-C was 94.0mg/dL (range:5-436mg/dL) with median LDL-s of 20.8 nm (range:19.4–23.0nm). LDL-s moderately correlated with LDL-C (Ï#129;=0.51;p&amp;lt;0.01). Small-dense-LDL was identified in only 18% (407/2,191) of patients with elevated LDL-C (&amp;gt;160mg/dL) and was more common (73.2% of 6,093) in patients with low LDL-C (&amp;lt;70mg/dL;p&amp;lt;0.001). Associations with CAD were investigated among patients without cholesterol-lowering medication treatment referred for angiography (n=356). CAD (defined as stenosis &amp;gt;50% in one or more coronary artery) was diagnosed in 14% (1/7) of subjects with low LDL-C (&amp;lt;70mg/dL) compared to 59% (47/80) of subjects with elevated LDL-C (p=0.01). When stratifying by LDL-s, CAD was diagnosed in 50% (57/115) of subjects with small-dense LDL compared to 43% (104/241) of subjects with large-buoyant LDL (p=0.2). Small-dense LDL was identified in only 33% (26/80) of cases with elevated LDL-C. Limiting to subjects with elevated LDL-C, CAD was diagnosed in 50% (13/26) of subjects with concordant (high-risk) small-dense LDL compared to 61% (33/54) of subjects with discordant (low-risk) large-buoyant LDL (LDL-s&amp;gt;20.5nm) (p=0.3). Our data confirm that LDL-s subfraction measured by NMR is reported discordantly in most cases when LDL-C is unequivocally high or low. Furthermore, CAD diagnosis was significantly associated with LDL-C, but not with LDL-s. Our data also show that in discrepant samples, elevated LDL-C correlates better with disease state compared to LDL-s. Therefore, LDL-s should not be used to justify treatment decisions in patients with elevated LDL-C. Laboratories should consider carefully whether or not to report LDL-s when it is known that misleading and discordant values will be reported in a majority of cases.

Relationship between resolution of non-alcoholic steatohepatitis and changes in lipoprotein sub-fractions: a post-hoc analysis of the PIVENS trial.

Dyslipidaemia is frequent in non-alcoholic steatohepatitis (NASH); however, it is unclear if improvement in liver histology is associated with favourable changes in cardiovascular disease (CVD) risk. To evaluate the relationship of NASH resolution and lipoprotein subfraction levels, markers of endothelial dysfunction, and macrophage activation. One hundred and seventeen individuals with NASH who participated in the Pioglitazone vs Vitamin E vs Placebo for the Treatment of Nondiabetic Patients with NASH (PIVENS) trial with paired liver biopsies and serum samples available at baseline and after 96weeks of treatment were included. Participants in the PIVENS trials received vitamin E, pioglitazone, or placebo for 96weeks. Lipoprotein subfraction levels, intracellular adhesion molecule 1 (ICAM-1), vascular cellular adhesion molecule 1 (VCAM-1), E-selectin, and sCD163 levels were assessed at baseline and week 96 and their relationship with NASH resolution was examined. Fifty-seven individuals had NASH resolution and 60 individuals did not have resolution of NASH. NASH resolution was associated with favourable changes in lipoprotein subfraction levels compared to those without NASH resolution. Individuals with resolution of NASH had a significantly increased mean peak LDL diameter (ratio of geometric means [96weeks vs baseline] 1.007 vs 0.996, P=0.004), and higher frequency of LDL phenotype A (58% vs 33%, P=0.003) at week 96, after adjustment for relevant co-variates including treatment group. No differences in VCAM, ICAM, E-selectin, or sCD163 levels by NASH resolution were found. NASH resolution is associated with favourable changes in a subset of serum lipoprotein levels. More studies are warranted to understand if these favourable changes are associated with decreased risk of CVD.

Association of LDL phenotypes with cholesterol synthesis and HDL subclasses in statin-treated coronary artery disease patients and healthy subjects

Association of LDL phenotypes with cholesterol synthesis and HDL subclasses in statin-treated coronary artery disease patients and healthy subjects

Insulin Resistance Predicts Atherogenic Lipoprotein Profile in Nondiabetic Subjects.

Background Atherogenic diabetes is associated with an increased cardiovascular risk and mortality in diabetic individuals; however, the impact of insulin resistance (IR) in lipid metabolism in preclinical stages is generally underreported. For that, we evaluated the capacity of IR to predict an atherogenic lipid subfraction profile. Methods Complete clinical evaluation and biochemical analysis (lipid, glucose profile, LDL, and HDL subfractions and LDL phenotype and size) were performed in 181 patients. The impact of IR as a predictor of atherogenic lipoproteins was tested by logistic regression analysis in raw and adjusted models. Results HDL-C and Apo AI were significantly lower in individuals with IR. Individuals with IR had a higher percentage of small HDL particles, lower percentage in the larger ones, and reduced frequency of phenotype A (IR = 62%; non-IR = 83%). IR individuals had reduced probability to have large HDL (OR = 0.213; CI = 0.999–0.457) and had twice more chances to show increased small HDL (OR = 2.486; CI = 1.341–7.051). IR was a significant predictor of small LDL (OR = 3.075; CI = 1.341–7.051) and atherogenic phenotype (OR = 3.176; CI = 1.469–6.867). Conclusion IR, previously DM2 diagnosis, is a strong predictor of quantitative and qualitative features of lipoproteins directly associated with an increased atherogenic risk.

Oxidative stress and hemoglobin–cholesterol adduct in renal patients with different LDL phenotypes

Unfavorable lipid profile is a major risk factor for cardiovascular disease in renal pathology. In this study, we compared chronic renal patients and healthy controls with different LDL phenotypes (A or B) in respect of various biochemical parameters related to cardiovascular disease. Oxidative stress and anti-oxidative defense parameters [thiobarbituric acid-reacting substances (TBARS), total oxidative status (TOS), total anti-oxidative status (TAS), total protein sulfhydryl (-SH) groups], as well as red blood cell cholesterol distribution were assessed in 40 renal patients and 40 control subjects by standardized assays. LDL particle diameters were determined by polyacrylamide gradient gel electrophoresis. LDL particles are subdivided according to their size into large LDL A phenotype (diameter >25.5nm) and small LDL B phenotype (diameter ≤25.5nm). Renal patients with LDL A phenotype had increased oxidative stress (TOS: p<0.01, and TBARS: p<0.001) and decreased total SH- groups (p<0.001) compared to controls with the same LDL phenotype. A notable decrease in hemoglobin-cholesterol adduct was detected in patients with LDL A phenotype (p<0.001) and LDL B phenotype (p<0.05) compared with appropriate controls. LDL B phenotype was characterized with increased TBARS (p<0.05) compared with LDL A phenotype in control group. Increased oxidative stress, decreased anti-oxidative defense followed with unfavorable changes in hemoglobin-cholesterol binding capacity, could have important influence on cardiovascular disease risk in renal patients regardless of LDL phenotype.

Abnormal lipid metabolism in metabolic syndrome: an epigenetic perspective

Abstract Metabolic syndrome is a complex pathology including central obesity, impaired glucose tolerance/diabetes, an atherogenic dyslipidemia and a prothrombotic state. A new perspective on understanding the mechanisms underlying metabolic syndrome is provided by the epigenetic changes (mainly DNA methylation and histone covalent modifications), which influence gene expression without changing of the DNA sequence. DNA methylation (mainly in carnitine palmitoyltransferase 1A gene) and histone modifications were shown to be associated with VLDL and LDL phenotypes, with hyperglycemia and reduced level of HDL cholesterol, with hypertriglyceridemic waist phenotype and with progression of atherosclerotic occlusion in peripheral arteries. The epigenetic changes can occur in the prenatal period, throughout the life span, and can be transmitted to the offspring. Both poor maternal nutrition and maternal obesity, diabetes and overfeeding can result in epigenetic alterations that amplify the risk of metabolic syndrome for the offspring. Throughout life span, environmental factors, such as nutrition and exercise can induce epigenetic changes influencing the evolution of the metabolic syndrome (through adipocyte metabolism and insulin signaling pathway). The epigenetic modifications are not completely erased during gametogenesis and embryogensis, resulting in a transgenerational transmission of an epigenetic state up to the fifth generation. Epigenetic mechanisms are an interface between environmental stimuli and resulting phenotype by inducing a certain transcriptional state, which may be also transmitted to the next generation(s) and which may predispose to an increased risk for developing metabolic syndrome in the context of a mismatched environment. Elucidating epigenetic modulation might provide additional information about risk evaluation and more targeted therapeutical intervention.

FRI-309 - Non-Alcoholic Steatohepatitis Resolution is Associated with Improvements in LDL Size and Phenotype

FRI-309 - Non-Alcoholic Steatohepatitis Resolution is Associated with Improvements in LDL Size and Phenotype

Relationship of carotid intima-media thickness with ldl phenotype in elite runners

Relationship of carotid intima-media thickness with ldl phenotype in elite runners

Abstract 9258: LDL Phenotype-B is Strongly Associated With CHD Risk Among Individuals With CKD. The Multi-ethnic Study of Atherosclerosis (MESA)

Introduction: LDL phenotype B, characterized by high triglyceride (TG), small dense LDL (sd-LDL), and very low-density lipoprotein (VLDL) levels, and low high-density lipoprotein (HDL) levels, is the hallmark lipid phenotype of chronic kidney disease (CKD). Whether this phenotype is associated with clinical coronary heart disease (CHD) in individuals with CKD is not known. Methods: CKD was defined as an eGFR of 15-59 ml/min/1.63m2 (stage 3-4). Principal component analyses were used to account for the correlations among lipoproteins defining lipid phenotype B. Nuclear magnetic resonance spectroscopy was used to measure lipoprotein sub-fractions. CHD was defined as a new MI, angina followed by revascularization, resuscitated cardiac arrest or CHD death. Results: A total of 6,814 individuals free of CHD at baseline were followed for a median time of 8.5 years. CHD developed in 303 individuals (5%) with eGFR≥60 and in 72 individuals (12%) with CKD (p for difference&lt;0.001). Principal component 1 captured the lipoprotein abnormalities defining lipid phenotype B: high TG levels (r for correlation with PC1=0.78), VLDL (r=0.73), sd-LDL(r=0.82) and low levels of HDL (r=-0.80). Compared to those without CKD, this phenotype (and its components) was more common (p for difference&lt;0.001), and was more strongly associated with CHD in those with CKD (figure): adjusted hazard ratios and 95% confidence intervals 1.13 (1.00-1.28; p=0.05) and 1.51 (1.17-1.94; p=0.001) in eGFR≥60 and CKD respectively (p for interaction=0.04). Conclusion: LDL phenotype-B is strongly associated with CHD risk in individuals with CKD. Whether a modification of the components of this phenotype leads to a reduction in the cardiovascular disease burden of individuals with CKD should be established in future studies.

Ratio of Dense to Buoyant LDL Subclass is Associated with LDL Density Phenotype (VLDL-5)

Background: Dense LDL phenotypes are associated with increased atherogenicity, and are commonly evaluated for the purposes of atherosclerosis research and cardiovascular risk discrimination. Objective: To examine the ability of LDL subclasses, expressed as a ratio of dense-to-buoyant subclass, to predict LDL density phenotype. Methods: LDL subclasses and density phenotypes were measured with vertical auto profile ultracentrifugation in 1,339,898 consecutive lipid profiles between 2009 and 2011 from a clinical sample of US adults. Logarithmic LDL density ratio (LLDR) was calculated as ratio of dense-to-buoyant LDL subclasses, ln((LDL3-C + LDL4-C) / (LDL1-C +LDL2-C)); normally distributed after log-transformation. LLDR was compared to density phenotype using ROC C- statistic with optimum sensitivity and specificity cutpoints determined. Results: There was a strong, highly significant, monotonic increase in LLDR across progressively higher density phenotypes (p 0.905, sensitivity 81%, specificity 86%. There was also a positive correlation between LLDR and LDL Max Time (R 2 =0.802). Conclusion: LLDR is a convenient, easily calculated, and continuous variable that is strongly associated with LDL density phenotype and LDL Max Time. Further research is needed to investigate the relationship between lipoprotein density and size, and whether LLDR provides more cardiovascular risk discrimination than LDL density phenotype.

Dyslipidemia in obesity: mechanisms and potential targets.

Obesity has become a major worldwide health problem. In every single country in the world, the incidence of obesity is rising continuously and therefore, the associated morbidity, mortality and both medical and economical costs are expected to increase as well. The majority of these complications are related to co-morbid conditions that include coronary artery disease, hypertension, type 2 diabetes mellitus, respiratory disorders and dyslipidemia. Obesity increases cardiovascular risk through risk factors such as increased fasting plasma triglycerides, high LDL cholesterol, low HDL cholesterol, elevated blood glucose and insulin levels and high blood pressure. Novel lipid dependent, metabolic risk factors associated to obesity are the presence of the small dense LDL phenotype, postprandial hyperlipidemia with accumulation of atherogenic remnants and hepatic overproduction of apoB containing lipoproteins. All these lipid abnormalities are typical features of the metabolic syndrome and may be associated to a pro-inflammatory gradient which in part may originate in the adipose tissue itself and directly affect the endothelium. An important link between obesity, the metabolic syndrome and dyslipidemia, seems to be the development of insulin resistance in peripheral tissues leading to an enhanced hepatic flux of fatty acids from dietary sources, intravascular lipolysis and from adipose tissue resistant to the antilipolytic effects of insulin. The current review will focus on these aspects of lipid metabolism in obesity and potential interventions to treat the obesity related dyslipidemia.

Atherogenic changes in low-density lipoprotein particle profiles were not observed in non-obese women with polycystic ovary syndrome

Is a preponderance of small dense low-density lipoprotein-cholesterol (LDL-C) observed in non-obese women with polycystic ovary syndrome (PCOS)? Non-obese Korean women with PCOS have no quantitative or qualitative changes in LDL-C profiles. Small dense LDL particles (sd-LDL) are more atherogenic than large buoyant ones and are strongly associated with coronary artery disease independent of other risk factors. Many investigators have found an increased proportion of atherogenic sd-LDL or a decreased mean LDL particle size in women with PCOS, but all of these studies have been based primarily on obese or overweight women with PCOS. This was a case-control study evaluating complete lipid and lipoprotein profiles in 64 PCOS patients and 64 age- and BMI-matched controls. All women with PCOS in our study population were not obese. To determine the differences in the LDL particle profiles between PCOS phenotypes, the patients with PCOS were divided into two subgroups according to the presence of clinical or biochemical hyperandrogenism. Using the Rotterdam criteria, we recruited 64 women (18-40 years) with PCOS who were attending a tertiary university hospital. A total of 64 premenopausal control women were matched with patients based on exact age and BMI (± 1.0 kg/m(2)). All the participants fell within the non-obese range of the BMI (<25 kg/m(2)) according to the definition of obesity for Asians. The LDL subfraction was analyzed by 3% polyacrylamide gel tube electrophoresis. Seven LDL subclasses were quantified and LDL subclasses 3-7 were small LDL subfractions. LDL subfraction scores were calculated based on the following weighted scoring system developed by the manufacturer: scores of <5.5 were categorized as phenotype A (large, buoyant LDLs), and those >5.5 were categorized as non-A phenotype (sd-LDLs). The system also determined the mean LDL particle size diameter. There were no differences in the absolute level of LDL-C, mean LDL diameter or percentage of atherogenic sd-LDLs between PCOS patients and controls or between hyperandrogenic and non-hyperandrogenic PCOS subgroups. Also, none of the subjects showed a non-A LDL phenotype. The most notable finding of our study was the difference in the lipoprotein (a) levels and prevalence of its elevation in PCOS patients versus controls (P = 0.002 and P = 0.004, respectively), and between PCOS subgroups (P = 0.030 and P = 0.047, respectively). Inclusion of only non-obese subjects, small sample size and lack of information on other potential confounding factors, such as differences in diet and/or exercise patterns. Although our findings suggest that non-obese women with PCOS have no significant quantitative or qualitative changes in LDL-C profile, data on obese Korean women with PCOS could offer complementary findings about the possible relationship between the magnitude of obesity and LDL phenotype. Further investigations are needed to determine whether a change in lipoprotein (a) in non-obese women with PCOS is also found in other ethnic groups. No conflict of interest exists. This study was supported by a grant of the Korean Health Technology R&D Project, Ministry of Health & Welfare, Republic of Korea (A100624). N/A.

Atherogenic low density lipoprotein phenotype in long-term survivors of childhood acute lymphoblastic leukemia

Survivors of childhood acute lymphoblastic leukemia (ALL) have an increased risk of cardiovascular disease. Small density lipoproteins are atherogenic but have not been studied in this population. We conducted a cross-sectional analysis of 110 ALL survivors (mean age, 24.3 years) to determine prevalence of small dense LDL (pattern B) phenotype in ALL survivors and identify associated factors. Lipid subfractions were measured using Vertical Auto Profile-II. Participants with greater than 50% of LDL-cholesterol (LDL-c) in small dense LDL fractions (LDL(3+4)) were classified as LDL pattern B. Visceral and subcutaneous adipose tissue (VAT, SAT) volumes were also measured by computed tomography. While the mean LDL-c level of ALL survivors was 108.7 ± 26.8 mg/dl, 36% (40/110) of survivors had atherogenic LDL pattern B. This pattern was more common in males (26/47; 55%) than in females (14/63; 22%, P = 0.001) and more common in survivors treated with cranial radiotherapy (15/33; 45%) than in those who were treated with chemotherapy alone (25/77; 33%; P = 0.04, adjusted for age, gender, history of hypertension, and smoking history). VAT was associated with atherogenic lipids: LDL pattern B and LDL(3+4) levels. This association was independent of other measures of body fat. We conclude that a substantial proportion of ALL survivors had an atherogenic LDL phenotype despite normal mean LDL-c levels. An atherogenic LDL phenotype may contribute to the increase in cardiovascular mortality and morbidity in this population.

Laboratory approaches for predicting and managing the risk of cardiovascular disease: postanalytical opportunities of lipid and lipoprotein testing

Abstract Lipoprotein-related risk of cardiovascular disease (CVD) can be adequately predicted in subjects with elevated total cholesterol and low-density lipoprotein (LDL-)cholesterol using the available guidelines. However, individuals with dyslipidemia can have normal total- and LDL-cholesterol concentrations. Many statin-treated patients remain at high residual risk of CVD despite achieving LDL goals. The small dense LDL phenotype, frequently presenting with hypertriglyceridemia and low high-density lipoprotein (HDL-)cholesterol (lipid triad), may contribute to failure to identify and treat high-risk individuals. Therefore, calculated non-HDL-cholesterol is recommended as secondary therapeutic target to LDL-cholesterol in patients with hypertriglyceridemia and mixed dyslipidemia. On-treatment apolipoprotein B adds prognostic information to LDL- and non-HDL-cholesterol by indicating the total number of atherogenic lipoproteins, regardless of their cholesterol content. Risk may be higher than indicated in the risk estimation systems in additional subjects with elevated lipoprotein(a) and homocysteine concentrations. To improve the (post-)post-analytical phase of lipid tests, aiming for maximal health outcome effectiveness of test interpretation and utilization, laboratory professionals should deliver clinical added value services by providing readily interpreted and guideline-adjusted test reports, interpretative commenting, proactive reflex testing or recommending additional tests, and joining multidisciplinary cooperations in guideline development and cost/benefit studies.