Increased particle size of triacylglycerol-enriched remnant lipoproteins, but not their plasma concentration or lipid content, augments risk prediction of incident type 2 diabetes.

AIMS/HYPOTHESIS: Type 2 diabetes prevention requires the accurate identification of those at high risk. Beyond the association of fasting serum triacylglycerols with diabetes, triacylglycerol-enriched remnant lipoproteins (TRLs) more accurately reflect pathophysiological changes that underlie progression to diabetes, such as hepatic insulin resistance, pancreatic steatosis and systemic inflammation. We hypothesised that TRL-related factors could improve risk prediction for incident diabetes. METHODS: We included individuals from the Brazilian Longitudinal Study of Adult Health cohort. We trained a logistic regression model for the risk of incident diabetes in 80% of the cohort using tenfold cross-validation, and tested the model in the remaining 20% of the cohort (test set). Variables included medical history and traits of the metabolic syndrome, followed by TRL-related measurements (plasma concentration, TRL particle diameter, cholesterol and triacylglycerol content). TRL features were measured using NMR spectroscopy. Discrimination was assessed using the area under the receiver operating characteristic curve (AUROC) and the area under the precision-recall curve (AUPRC). RESULTS: Among 4463 at-risk individuals, there were 366 new cases of diabetes after a mean (±SD) of 3.7 (±0.63) years of follow-up. We derived an 18-variable model with a global AUROC of 0.846 (95% CI: 0.829, 0.869). Overall TRL-related markers were not associated with diabetes. However, TRL particle diameter increased the AUROC, particularly in individuals with HbA1c <39 mmol/mol (5.7%) (hold-out test set [n = 659]; training-validation set [n = 2638]), but not in individuals with baseline HbA1c 39-46 mmol/mol (5.7-6.4%) (hold-out test set [n = 233]; training-validation set [n = 933]). In the subgroup with baseline HbA1c <39 mmol/mol (5.7%), AUROC in the test set increased from 0.717 (95% CI 0.603, 0.818) to 0.794 (95% CI 0.731, 0.862), and AUPRC in the test set rose from 0.582 to 0.701 when using the baseline model and the baseline model plus TRL particle diameter, respectively. TRL particle diameter was highly correlated with obesity, insulin resistance and inflammation in those with impaired fasting glucose at baseline, but less so in those with HbA1c <39 mmol/mol (5.7%). CONCLUSIONS/INTERPRETATION: TRL particle diameter improves the prediction of diabetes, but only in individuals with HbA1c <39 mmol/mol (5.7%) at baseline. These data support TRL particle diameter as a risk factor that is changed early in the course of the pathophysiological processes that lead to the development of type 2 diabetes, even before glucose abnormalities are established. Graphical abstract.

Fasting Versus Nonfasting and Low-Density Lipoprotein Cholesterol Accuracy.

BACKGROUND: Recent recommendations favoring nonfasting lipid assessment may affect low-density lipoprotein cholesterol (LDL-C) estimation. The novel method of LDL-C estimation (LDL-CN) uses a flexible approach to derive patient-specific ratios of triglycerides to very low-density lipoprotein cholesterol. This adaptability may confer an accuracy advantage in nonfasting patients over the fixed approach of the classic Friedewald method (LDL-CF). METHODS: We used a US cross-sectional sample of 1 545 634 patients (959 153 fasting ≥10-12 hours; 586 481 nonfasting) from the second harvest of the Very Large Database of Lipids study to assess for the first time the impact of fasting status on novel LDL-C accuracy. Rapid ultracentrifugation was used to directly measure LDL-C content (LDL-CD). Accuracy was defined as the percentage of LDL-CD falling within an estimated LDL-C (LDL-CN or LDL-CF) category by clinical cut points. For low estimated LDL-C (<70 mg/dL), we evaluated accuracy by triglyceride levels. The magnitude of absolute and percent differences between LDL-CD and estimated LDL-C (LDL-CN or LDL-CF) was stratified by LDL-C and triglyceride categories. RESULTS: In both fasting and nonfasting samples, accuracy was higher with the novel method across all clinical LDL-C categories (range, 87%-94%) compared with the Friedewald estimation (range, 71%-93%; P≤0.001). With LDL-C <70 mg/dL, nonfasting LDL-CN accuracy (92%) was superior to LDL-CF accuracy (71%; P<0.001). In this LDL-C range, 19% of fasting and 30% of nonfasting patients had differences ≥10 mg/dL between LDL-CF and LDL-CD, whereas only 2% and 3% of patients, respectively, had similar differences with novel estimation. Accuracy of LDL-C <70 mg/dL further decreased as triglycerides increased, particularly for Friedewald estimation (range, 37%-96%) versus the novel method (range, 82%-94%). With triglycerides of 200 to 399 mg/dL in nonfasting patients, LDL-CN <70 mg/dL accuracy (82%) was superior to LDL-CF (37%; P<0.001). In this triglyceride range, 73% of fasting and 81% of nonfasting patients had ≥10 mg/dL differences between LDL-CF and LDL-CD compared with 25% and 20% of patients, respectively, with LDL-CN. CONCLUSIONS: Novel adaptable LDL-C estimation performs better in nonfasting samples than the fixed Friedewald estimation, with a particular accuracy advantage in settings of low LDL-C and high triglycerides. In addition to stimulating further study, these results may have immediate relevance for guideline committees, laboratory leadership, clinicians, and patients. CLINICAL TRIAL REGISTRATION: URL: https://www.clinicaltrials.gov. Unique identifier: NCT01698489.

Impact of Novel Low-Density Lipoprotein-Cholesterol Assessment on the Utility of Secondary Non-High-Density Lipoprotein-C and Apolipoprotein B Targets in Selected Worldwide Dyslipidemia Guidelines.

BACKGROUND: Selected dyslipidemia guidelines recommend non-high-density lipoprotein-cholesterol (non-HDL-C) and apolipoprotein B (apoB) as secondary targets to the primary target of low-density lipoprotein-cholesterol (LDL-C). After considering 2 LDL-C estimates that differ in accuracy, we examined: (1) how frequently non-HDL-C guideline targets could change management; and (2) the utility of apoB targets after meeting LDL-C and non-HDL-C targets. METHODS: We analyzed 2518 adults representative of the US population from the 2011 to 2012 National Health and Nutrition Examination Survey and 126 092 patients from the Very Large Database of Lipids study with apoB. We identified all individuals as well as those with high-risk clinical features, including coronary artery disease, diabetes mellitus, and metabolic syndrome who met very high- and high-risk guideline targets of LDL-C <70 and <100 mg/dL using Friedewald estimation (LDL-CF) and a novel, more accurate method (LDL-CN). Next, we examined those not meeting non-HDL-C (<100, <130 mg/dL) and apoB (<80, <100 mg/dL) guideline targets. In those meeting dual LDL-C and non-HDL-C targets (<70 and <100 mg/dL, respectively, or <100 and <130 mg/dL, respectively), we determined the proportion of individuals who did not meet guideline apoB targets (<80 or <100 mg/dL). RESULTS: A total of 7% to 9% and 31% to 36% of individuals had LDL-C <70 and <100 mg/dL, respectively. Among those with LDL-CF<70 mg/dL, 14% to 15% had non-HDL-C ≥100 mg/dL, and 7% to 8% had apoB ≥80 mg/dL. Among those with LDL-CF<100 mg/dL, 8% to 10% had non-HDL-C ≥130 mg/dL and 2% to 3% had apoB ≥100 mg/dL. In comparison, among those with LDL-CN<70 or 100 mg/dL, only ≈2% and ≈1% of individuals, respectively, had non-HDL-C and apoB values above guideline targets. Similar trends were upheld among those with high-risk clinical features: ≈0% to 3% of individuals with LDL-CN<70 mg/dL had non-HDL-C ≥100 mg/dL or apoB ≥80 mg/dL compared with 13% to 38% and 9% to 25%, respectively, in those with LDL-CF<70 mg/dL. With LDL-CF or LDL-CN<70 mg/dL and non-HDL-C <100 mg/dL, 0% to 1% had apoB ≥80 mg/dL. Among all dual LDL-CF or LDL-CN<100 mg/dL and non-HDL-C <130 mg/dL individuals, 0% to 0.4% had apoB ≥100 mg/dL. These findings were robust to sex, fasting status, and lipid-lowering therapy status. CONCLUSIONS: After more accurately estimating LDL-C, guideline-suggested non-HDL-C targets could alter management in only a small fraction of individuals, including those with coronary artery disease and other high-risk clinical features. Furthermore, current guideline-suggested apoB targets provide modest utility after meeting cholesterol targets. CLINICAL TRIAL REGISTRATION: URL: https://www.clinicaltrials.gov. Unique identifier: NCT01698489.

Associations between very low concentrations of low density lipoprotein cholesterol, high sensitivity C-reactive protein, and health outcomes in the Reasons for Geographical and Racial Differences in Stroke (REGARDS) study.

Aims: Recent findings have demonstrated the important contribution of inflammation to the risk of cardiovascular disease (CVD) in individuals with optimally managed low density lipoprotein cholesterol (LDL-C). We explored relationships between LDL-C, high sensitivity C-reactive protein (hs-CRP), and clinical outcomes in a free-living US population. Methods and results: We used data from the REasons for Geographical And Racial Differences in Stroke (REGARDS), and selected individuals at 'high risk' for coronary events with a Framingham Coronary Risk Score of ≥10% or atherosclerotic cardiovascular disease (ASCVD) risk ≥7.5% in order to explore relationships between low LDL-C [<70 mg/dL (1.8 mmol/L) in comparison to ≥70 mg/dL (1.8 mmol/L)]; hs-CRP <2 compared with ≥2 mg/L and clinical outcomes [all-cause mortality, incident coronary heart disease (CHD), and incident stroke]. To assess the association between the LDL-C and hs-CRP categories and each outcome, a series of incremental Cox proportional hazards models were employed on complete cases. To account for missing observations, the most adjusted model was used to interrogate the data using multiple imputation with chained equations (MICE). In this analysis, 6136 REGARDS high-risk participants were included. In the MICE analysis, participants with high LDL-C (≥70 mg/dL) and low hs-CRP (<2 mg/L) had a lower risk of incident stroke [hazard ratio (HR) 0.69, 0.47-0.997], incident CHD (HR 0.71, 0.53-0.95), and CHD death (HR 0.70, 0.50-0.99) than those in the same LDL-C category high hs-CRP (≥2 mg/L). In participants with high hs-CRP (≥2 mg/dL), low LDL-C [<70 mg/dL (1.8 mmol/L)] was not associated with additional risk reduction of any investigated outcome, but with the significant increase of all-cause mortality (HR 1.37, 1.07-1.74). Conclusions: In this high-risk population, we found that low hs-CRP (<2 mg/L) appeared to be associated with reduced risk of incident stroke, incident CHD, and CHD death, whereas low LDL-C (<70 mg/dL) was not associated with protective effects. Thus, our results support other data with respect to the importance of inflammatory processes in the pathogenesis of CVD.

Fasting or Non-fasting Lipids for Atherosclerotic Cardiovascular Disease Risk Assessment and Treatment?

PURPOSE OF REVIEW: Dyslipidemia is a major modifiable risk factor for atherosclerotic cardiovascular disease (ASCVD); however, lipid testing for risk assessment and treatment surveillance has been underutilized. Several factors likely account for this, including the common practice of measuring lipid levels in the fasting state, which often necessitates that patients return for an additional visit. In this review, we evaluate potential advantages and cautions associated with measuring lipids in the non-fasting state. RECENT FINDINGS: There is similar performance with the use of either fasting or non-fasting total cholesterol and HDL cholesterol in ASCVD risk assessment. Observational studies demonstrate that in comparison to fasting levels, non-fasting triglycerides are approximately 20% higher on average, although the magnitude of difference is subject to substantial inter-patient variability. Higher triglycerides can lead to the under-estimation of low-density lipoprotein cholesterol (LDL-C) by approximately 10 mg/dL or more when calculated using the Friedewald equation. This is especially clinically relevant at low LDL-C levels, although a novel validated algorithm for LDL-C estimation largely overcomes this limitation. Non-fasting lipid assessment is reasonable in many clinical circumstances given that ASCVD risk prediction is similar using fasting or non-fasting lipid values and because LDL-C can be accurately estimated using modern methods. Allowing the option for non-fasting lipid assessment can reduce a barrier to lipid testing and can facilitate a more convenient assessment of ASCVD risk with the ultimate potential effect of reducing the global burden of ASCVD. However, certain patients such as those with severe hypertriglyceridemias or high-risk patients being treated to low LDL-C levels may still need fasting lipid panels performed for precise diagnosis and to standardize therapeutic monitoring.

Accuracy of low-density lipoprotein cholesterol estimation at very low levels.

BACKGROUND: As the approach to low-density lipoprotein cholesterol (LDL-C) lowering becomes increasingly intensive, accurate assessment of LDL-C at very low levels warrants closer attention in individualized clinical efficacy and safety evaluation. We aimed to assess the accuracy of LDL-C estimation at very low levels by the Friedewald equation, the de facto clinical standard, and compare its accuracy with a novel, big data-derived LDL-C estimate. METHODS: In 191,333 individuals with Friedewald LDL-C < 70 mg/dL, we compared the accuracy of Friedewald and novel LDL-C values in relation to direct measurements by Vertical Auto Profile ultracentrifugation. We examined differences (estimate minus ultracentrifugation) and classification according to levels initiating additional safety precautions per clinical practice guidelines. RESULTS: Friedewald values were less than ultracentrifugation measurement, with a median difference (25th to 75th percentile) of -2.4 (-7.4 to 0.6) at 50-69 mg/dL, -7.0 (-16.2 to -1.2) at 25-39 mg/dL, and -29.0 (-37.4 to -19.6) at < 15 mg/dL. The respective values by novel estimation were -0.1 (-1.5 to 1.3), -1.1 (-2.5 to 0.3), and -2.7 (-4.9 to 0.0) mg/dL. Among those with Friedewald LDL-C < 15, 15 to < 25, and 25 to < 40 mg/dL, the classification was discordantly low in 94.9%, 82.6%, and 59.9% of individuals as compared with 48.3%, 42.4%, and 22.4% by novel estimation. CONCLUSIONS: Estimation of even lower LDL-C values (by Friedewald and novel methods) is even more inaccurate. More often than not, a Friedewald value < 40 mg/dL is underestimated, which translates into unnecessary safety alarms that could be reduced in half by estimation using our novel method.

Efficacy and Safety of Alternate-Day Versus Daily Dosing of Statins: a Systematic Review and Meta-Analysis.

PURPOSE: We conducted a meta-analysis of randomized controlled trials (RCTs) and quasi-RCTs to synthesize evidence about the efficacy and safety of alternate-day vs daily dosing of statins. METHODS: We searched selected databases through January 2, 2017 to identify relevant RCTs and quasi-RCTs. The primary outcome was change in low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), and triglycerides (TG), while secondary outcomes included adverse events and adherence. RESULTS: Twelve RCTs and 1 quasi-RCT (n = 1023 patients) were included in the analysis. Pooled analysis revealed no statistically significant difference between alternate-day and daily regimens of atorvastatin and rosuvastatin in terms of change in LDL-C (mean difference [MD] 6.79 mg/dL, 95% confidence interval [CI] -1.59, 15.17, p = 0.11, and 10.51 mg/dL, 95%CI -0.23, 21.26, p = 0.06, respectively) and TG (p > 0.05). Daily regimens of atorvastatin and rosuvastatin were superior to alternate-day regimes in term of change in TC (MD 12.45 mg/L, 95%CI 8.14, 16.76, p < 0.00001, and 15.80 mg/dL, 95%CI 5.66, 25.95, p = 0.002, respectively). For all outcomes, there was no statistically significant difference between alternate-day and daily regimens for both fluvastatin and pravastatin (p > 0.05). Both regimens of statins were generally well tolerated with good adherence. CONCLUSIONS: Alternate-day dosing of individual statins (especially atorvastatin and rosuvastatin) is as efficacious as daily dosing on LDL-C and TG.

Patient-Level Discordance in Population Percentiles of the Total Cholesterol to High-Density Lipoprotein Cholesterol Ratio in Comparison With Low-Density Lipoprotein Cholesterol and Non-High-Density Lipoprotein Cholesterol: The Very Large Database of Lipids Study (VLDL-2B).

BACKGROUND: The total cholesterol to high-density lipoprotein cholesterol (TC/HDL-C) ratio, estimated low-density lipoprotein cholesterol (LDL-C), and non-HDL-C are routinely available from the standard lipid profile. We aimed to assess the extent of patient-level discordance of TC/HDL-C with LDL-C and non-HDL-C, because discordance suggests the possibility of additional information. METHODS AND RESULTS: We compared population percentiles of TC/HDL-C, Friedewald-estimated LDL-C, and non-HDL-C in 1 310 432 US adults from the Very Large Database of Lipids. Lipid testing was performed by ultracentrifugation (Vertical Auto Profile, Atherotech, AL). One in 3 patients had ≥25 percentile units discordance between TC/HDL-C and LDL-C, whereas 1 in 4 had ≥25 percentile units discordance between TC/HDL-C and non-HDL-C. The proportion of patients with TC/HDL-C > LDL-C by ≥25 percentile units increased from 3% at triglycerides <100 mg/dL to 51% at triglycerides 200 to 399 mg/dL. On a smaller scale, TC/HDL-C > non-HDL-C discordance by ≥25 percentile units increased from 6% to 21%. In those with <15th percentile levels of LDL-C (<70 mg/dL) or non-HDL-C (<93 mg/dL), a respective 58% and 46% were above the percentile-equivalent TC/HDL-C of 2.6. Age, sex, and directly measured components of the standard lipid profile explained >86% of the variance in percentile discordance between TC/HDL-C versus LDL-C and non-HDL-C. CONCLUSIONS: In this contemporary, cross-sectional, big data analysis of US adults who underwent advanced lipid testing, the extent of patient-level discordance suggests that TC/HDL-C may offer potential additional information to LDL-C and non-HDL-C. Future studies are required to determine the clinical implications of this observation. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifier: NCT01698489.

Does vitamin D supplementation alter plasma adipokines concentrations? A systematic review and meta-analysis of randomized controlled trials.

We aimed to elucidate the role of vitamin D supplementation on adipokines through a systematic review and a meta-analysis of randomized placebo-controlled trials (RCTs). The search included PUBMED, Scopus, Web of Science and Google Scholar through July 1st, 2015. Finally we identified 9 RCTs and 484 participants. Meta-analysis of data from 7 studies did not find a significant change in plasma adiponectin concentrations following vitamin D supplementation (mean difference [MD]: 4.45%, 95%CI: -3.04, 11.93, p=0.244; Q=2.18, I(2)=0%). In meta-regression, changes in plasma adiponectin concentrations following vitamin D supplementation were found to be independent of treatment duration (slope: 0.25; 95%CI: -0.69, 1.19; p=0.603) and changes in serum 25-hydroxy vitamin D [25(OH)D] levels (slope: -0.02; 95%CI: -0.15, 0.12; p=0.780). Meta-analysis of data from 6 studies did not find a significant change in plasma leptin concentrations following vitamin D supplementation (MD: -4.51%, 95%CI: -25.13, 16.11, p=0.668; Q=6.41, I(2)=21.97%). Sensitivity analysis showed that this effect size is sensitive to one of the studies; removing it resulted in a significant reduction in plasma leptin levels (MD: -12.81%, 95%CI: -24.33, -1.30, p=0.029). In meta-regression, changes in plasma leptin concentrations following vitamin D supplementation were found to be independent of treatment duration (slope: -1.93; 95%CI: -4.08, 0.23; p=0.080). However, changes in serum 25(OH)D were found to be significantly associated with changes in plasma leptin levels following vitamin D supplementation (slope: 1.05; 95%CI: 0.08, 2.02; p=0.033). In conclusion, current data did not indicate a significant effect of vitamin D supplementation on adiponectin and leptin levels.

Head-to-head comparison of statins versus fibrates in reducing plasma fibrinogen concentrations: A systematic review and meta-analysis.

BACKGROUND: Several studies suggest differences between fibrates and statins in lowering plasma fibrinogen (Fib) concentrations, but the evidence is not definitive. Therefore, the aim of this meta-analysis of head-to-head randomized trials was to compare the efficacy of statins and fibrates on plasma Fib concentrations. METHODS: The literature search included Medline, Scopus, and Web of Science up to February 1st, 2015, to identify head-to-head comparative randomized trials investigating the efficacy of fibrates vs statins on plasma Fib concentrations. RESULTS: In total 22 trials with 2762 participants were included to the meta-analysis. Random-effect meta-analysis suggested a significantly greater effect of fibrates vs statins in lowering plasma Fib concentrations (weighted mean difference [WMD]: -40.7mg/dL, 95% confidence interval [CI]: -55.2, -26.3, p<0.001). When the analysis was stratified according to the type of fibrate administered, there were significant Fib-lowering effects with both bezafibrate (n=8 treatment arms; WMD: -23.7mg/dL, 95% CI: -41.8, -5.7, p=0.01) and fenofibrate (n=15 treatment arms; WMD: -43.7mg/dL, 95% CI: -61.3, -26.2, p<0.001). Overall, there was a numerically greater effect in the subgroup of trials with ≥12 weeks duration (n=17 treatment arms; WMD: -42.7mg/dL, 95% CI: -60.3, -25.1, p<0.001) compared with the subgroup of trials lasting <12 weeks (n=7 treatment arms; WMD: -36.7mg/dL, 95% CI: -52.0, -21.4, p<0.001). CONCLUSIONS: Monotherapy with either fibrates or statins suggested a significantly greater effect of fibrates in lowering plasma Fib concentrations. According to these findings, mechanisms associated with fibrinogen metabolism might be responsible for the distinct effects of statins and fibrates in reducing cardiovascular endpoints.

Entropy of cardiac repolarization predicts ventricular arrhythmias and mortality in patients receiving an implantable cardioverter-defibrillator for primary prevention of sudden death.

AIMS: The need for a readily available, inexpensive, non-invasive method for improved risk stratification of heart failure (HF) patients is paramount. Prior studies have proposed that distinct fluctuation patterns underlying the variability of physiological signals have unique prognostic value. We tested this hypothesis in an extensively phenotyped cohort of HF patients using EntropyXQT, a novel non-linear measure of cardiac repolarization dynamics. METHODS AND RESULTS: In a prospective, multicentre, observational study of 852 patients in sinus rhythm undergoing clinically indicated primary prevention implantable cardioverter-defibrillator (ICD) implantation (2003-10), exposures included demographics, history, physical examination, medications, laboratory results, serum biomarkers, ejection fraction, conventional electrocardiographic (ECG) analyses of heart rate and QT variability, and EntropyXQT. The primary outcome was first 'appropriate' ICD shock for ventricular arrhythmias. The secondary outcome was composite events (appropriate ICD shock and all-cause mortality). After exclusions, the cohort (n = 816) had a mean age of 60 ± 13 years, 28% women, 36% African Americans, 56% ischaemic cardiomyopathy, and 29 ± 16% Seattle HF risk score (SHFS) 5-year predicted mortality. Over 45 ± 24 months, there were 134 appropriate shocks and 166 deaths. After adjusting for 30 exposures, the hazard ratios (comparing the 5th to 1st quintile of EntropyXQT) for primary and secondary outcomes were 3.29 (95% CI 1.74-6.21) and 2.28 (1.53-3.41), respectively. Addition of EntropyXQT to a model comprised of the exposures or SHFS significantly increased net reclassification and the ROC curve area. CONCLUSIONS: EntropyXQT measured during ICD implantation strongly and independently predicts appropriate shock and all-cause mortality over follow-up. EntropyXQT complements conventional risk predictors and has the potential for broad clinical application.

Effect of alirocumab on specific lipoprotein non-high-density lipoprotein cholesterol and subfractions as measured by the vertical auto profile method: analysis of 3 randomized trials versus placebo.

BACKGROUND: The effect of alirocumab on potentially atherogenic lipoprotein subfractions was assessed in a post hoc analysis using the vertical auto profile (VAP) method. METHODS: Patients from three Phase II studies with low-density lipoprotein cholesterol (LDL-C) ≥ 2.59 mmol/L (100 mg/dL) at baseline on stable statin therapy were randomised to receive subcutaneous alirocumab 50-150 mg every 2 weeks (Q2W) or 150-300 mg every 4 weeks (according to study) or placebo for 8-12 weeks. Samples from patients treated with alirocumab 150 mg Q2W (n = 74; dose common to all three trials) or placebo (n = 71) were analysed by VAP. Percent change in lipoprotein subfractions with alirocumab vs. placebo was analysed at Weeks 6, 8 or 12 using analysis of covariance. RESULTS: Alirocumab significantly reduced LDL-C and the cholesterol content of subfractions LDL1, LDL2 and LDL3+4. Significant reductions were also observed in triglycerides, apolipoproteins CII and CIII and the cholesterol content of very low-density, intermediate-density, and remnant lipoproteins. CONCLUSION: Alirocumab achieved reductions across a spectrum of atherogenic lipoproteins in patients receiving background statin therapy. TRIAL REGISTRATION: Clinicaltrials.gov identifiers: NCT01288443, NCT01288469, NCT01266876.

HDL cholesterol subclasses, myocardial infarction, and mortality in secondary prevention: the Lipoprotein Investigators Collaborative.

AIMS: High-density lipoprotein (HDL) is highly heterogeneous and the link of its subclasses to prognosis remains controversial. We aimed to rigorously examine the associations of HDL subclasses with prognosis in secondary prevention. METHODS AND RESULTS: We collaboratively analysed data from two, complementary prospective cohorts: the TRIUMPH study of 2465 acute myocardial infarction patients, and the IHCS study of 2414 patients who underwent coronary angiography. All patients had baseline HDL subclassification by vertical-spin density gradient ultracentrifugation. Given non-linearity, we stratified by tertiles of HDL-C and its two major subclasses (HDL2-C, HDL3-C), then compared multivariable-adjusted hazard ratios for mortality and mortality/myocardial infarction. Patients were middle-aged to elderly (TRIUMPH: 58.2 ± 12.2 years; IHCS: 62.6 ± 12.6 years), and the majority were men (TRIUMPH: 68.0%; IHCS: 65.5%). IHCS had lower mean HDL-C levels (34.6 ± 10.1 mg/dL) compared with TRIUMPH (40 ± 10.6 mg/dL). HDL3-C accounted for >3/4 of HDL-C (mean HDL3-C/HDL-C 0.78 ± 0.05 in both cohorts). During 2 years of follow-up in TRIUMPH, 226 (9.2%) deaths occurred, while death/myocardial infarction occurred in 401 (16.6%) IHCS patients over 5 years. No independent associations with outcomes were observed for HDL-C or HDL2-C. In contrast, the lowest tertile of HDL3-C was independently associated with >50% higher risk in each cohort (TRIUMPH: with middle tertile as reference, fully adjusted HR for mortality of HDL3-C, 1.57; 95% CI, 1.13-2.18; IHCS: fully adjusted HR for mortality/myocardial infarction, 1.55; 95% CI, 1.20-2.00). CONCLUSION: In secondary prevention, increased risk for long-term hard clinical events is associated with low HDL3-C, but not HDL2-C or HDL-C, highlighting the potential value of subclassifying HDL-C.

Dyslipidemia, coronary artery calcium, and incident atherosclerotic cardiovascular disease: implications for statin therapy from the multi-ethnic study of atherosclerosis.

BACKGROUND: Worldwide clinical practice guidelines for dyslipidemia emphasize allocating statin therapy to those at the highest absolute atherosclerotic cardiovascular disease (CVD) risk. METHODS AND RESULTS: We examined 5534 Multi-Ethnic Study of Atherosclerosis (MESA) participants who were not on baseline medications for dyslipidemia. Participants were classified by baseline coronary artery calcium (CAC) score (>0, ≥ 100) and the common clinical scheme of counting lipid abnormalities (LA), including low-density lipoprotein cholesterol ≥ 3.36 mmol/L (130 mg/dL), high-density lipoprotein cholesterol <1.03 mmol/L (40 mg/dL) for men or <1.29 mmol/L (50 mg/dL) for women, and triglycerides ≥ 1.69 mmol/L (150 mg/dL). Our main outcome measure was incident CVD (myocardial infarction, angina resulting in revascularization, resuscitated cardiac arrest, stroke, cardiovascular death). Over a median follow-up of 7.6 years, more than half of events (55%) occurred in the 21% of participants with CAC ≥ 100. Conversely, 65% of events occurred in participants with 0 or 1 LA. In those with CAC ≥ 100, CVD rates ranged from 22.7 to 29.5 per 1000 person-years across LA categories. In contrast, with CAC=0, CVD rates ranged from 2.7 to 5.9 per 1000 person-years across LA categories. Individuals with 0 LA and CAC ≥ 100 had a higher event rate compared with individuals with 3 LA but CAC=0 (22.7 versus 5.9 per 1000 person-years). Similar results were obtained when we classified LA using data set quartiles of total cholesterol/high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, non-high-density lipoprotein cholesterol, or low-density lipoprotein particle concentration and guideline categories of low-density lipoprotein cholesterol or non-high-density lipoprotein cholesterol. CONCLUSIONS: CAC may have the potential to help match statin therapy to absolute CVD risk. Across the spectrum of dyslipidemia, event rates similar to secondary prevention populations were observed for patients with CAC ≥ 100.

Statin therapy and plasma coenzyme Q10 concentrations--A systematic review and meta-analysis of placebo-controlled trials.

Statin therapy may lower plasma coenzyme Q10 (CoQ10) concentrations, but the evidence as to the significance of this effect is unclear. We assessed the impact of statin therapy on plasma CoQ10 concentrations through the meta-analysis of available RCTs. The literature search included selected databases up to April 30, 2015. The meta-analysis was performed using either a fixed-effects or random-effect model according to I(2) statistic. Effect sizes were expressed as weighted mean difference (WMD) and 95% confidence interval (CI). The data from 8 placebo-controlled treatment arms suggested a significant reduction in plasma CoQ10 concentrations following treatment with statins (WMD: -0.44 µmol/L, 95%CI: -0.52, -0.37, p<0.001). The pooled effect size was robust and remained significant in the leave-one-out sensitivity analysis. Subgroup analysis suggested that the impact of statins on plasma CoQ10 concentrations is significant for all 4 types of statins studied i.e. atorvastatin (WMD: -0.41 µmol/L, 95%CI: -0.53, -0.29, p<0.001), simvastatin (WMD: -0.47 µmol/L, 95% CI: -0.61, -0.33, p<0.001), rosuvastatin (WMD: -0.49 µmol/L, 95%CI: -0.67, -0.31, p<0.001) and pravastatin (WMD: -0.43 µmol/L, 95%CI: -0.69, -0.16, p=0.001). Likewise, there was no differential effect of lipophilic (WMD: -0.43 µmol/L, 95%CI: -0.53, -0.34, p<0.001) and hydrophilic statins (WMD: -0.47 µmol/L, 95%CI: -0.62, -0.32, p<0.001). With respect to treatment duration, a significant effect was observed in both subsets of trials lasting <12 weeks (WMD: -0.51 µmol/L, 95%CI: -0.64, -0.39, p<0.001) and ≥12 weeks (WMD: -0.40 µmol/L, 95%CI: -0.50, -0.30, p<0.001). The meta-analysis showed a significant reduction in plasma CoQ10 concentrations following treatment with statins. Further well-designed trials are required to confirm our findings and elucidate their clinical relevance.

Expanded genetic testing in familial hypercholesterolemia-A single center's experience.

Objective: Assess the yield of genetic testing for pathogenic variants in ABCG5, ABCG8, LIPA, and APOE in individuals with personal and family histories suggestive of familial hypercholesterolemia. Methods: Retrospective review of patients seen in the Advanced Lipid Disorders Clinic at Johns Hopkins. Results: In the lipid clinic at a single center during the years 2015-2023, 607 patients underwent genetic testing for familial hypercholesterolemia, of which 263 underwent the expanded genetic testing for sitosterolemia. Eighty-eight patients had genetic testing which included APOE, and 22 patients had testing which included LIPA. Among these, one patient was identified to have a pathogenic variant in APOE and another patient with a pathogenic variant in ABCG5 (0.7 % yield). The frequency of a positive result was double that of a variant of uncertain significance. Conclusion: These data suggest in rare cases expanded testing can provide answers for patients and families with a minimal likelihood of a variant of uncertain significance.

GlycA Levels Independently Predict Coronary Artery Calcium Incidence and Progression in the ELSA-Brasil Cohort (Brazilian Longitudinal Study of Adult Health).

Atherosclerosis is an inflammatory disease. Coronary artery calcium (CAC) is a marker of atherosclerotic disease events and mortality risk. Increased GlycA, an emerging marker of inflammation, is associated with a higher risk for coronary artery disease (CAD). However, there is conflicting evidence on whether GlycA predicts subclinical CAD progression. We hypothesized that GlycA can predict subclinical CAC incidence/progression in healthy participants. We included 2,690 ELSA-Brasil cohort participants without cardiovascular/chronic inflammatory disease not receiving statin therapy who had GlycA levels measured and 2 interval CAC assessments between 2010 and 2018. Multivariable logistic and linear regression models were computed to evaluate GlycA as a predictor of CAC incidence and progression. CAC incidence required a baseline CAC of 0. CAC progression required a baseline CAC >0. The mean age of participants was 48.6 ± 7.7 years, 56.7% were women, and 54.6% and 16.1% (429 of 2,690) were White and Black, respectively. The mean CAC interscan period was 5.1 ± 0.9 years, the mean GlycA level was 414.7 ± 65 µmol/L, and the incidence of CAC was 13.1% (280 of 2,129). The GlycA level odds ratio for CAC incidence was 1.002 (95% confidence interval 1.0005 to 1.005, p = 0.016), adjusted for demographics, lifestyle, a family history of early CAD (≤60 years), lipids, and co-morbidities. The GlycA (≤p25 vs ≥p75) odds ratio for CAC progression (Berry definition) was 1.77 (95% confidence interval 1.07 to 2.96, p = 0.03) in a similar multivariable-adjusted model. Higher GlycA levels were associated with CAC incidence and progression in a healthy Brazilian cohort.

Low-risk lifestyle, coronary calcium, cardiovascular events, and mortality: results from MESA.

Unhealthy lifestyle habits are a major contributor to coronary artery disease. The purpose of the present study was to investigate the associations of smoking, weight maintenance, physical activity, and diet with coronary calcium, cardiovascular events, and mortality. US participants who were 44-84 years of age (n = 6,229) were followed in the Multi-Ethnic Study of Atherosclerosis from 2000 to 2010. A lifestyle score ranging from 0 to 4 was created using diet, exercise, body mass index, and smoking status. Coronary calcium was measured at baseline and a mean of 3.1 (standard deviation, 1.3) years later to assess calcium progression. Participants who experienced coronary events or died were followed for a median of 7.6 (standard deviation, 1.5) years. Participants with lifestyle scores of 1, 2, 3, and 4 were found to have mean adjusted annual calcium progressions that were 3.5 (95% confidence interval (CI): 0.0, 7.0), 4.2 (95% CI: 0.6, 7.9), 6.8 (95% CI: 2.0, 11.5), and 11.1 (95% CI: 2.2, 20.1) points per year slower, respectively, relative to the reference group (P = 0.003). Unadjusted hazard ratios for death by lifestyle score were as follows: for a score of 1, the hazard ratio was 0.79 (95% CI: 0.61, 1.03); for a score of 2, the hazard ratio was 0.61 (95% CI: 0.46, 0.81); for a score of 3, the hazard ratio was 0.49 (95% CI: 0.32, 0.75); and for a score of 4, the hazard ratio was 0.19 (95% CI: 0.05, 0.75) (P < 0.001 by log-rank test). In conclusion, a combination of regular exercise, healthy diet, smoking avoidance, and weight maintenance was associated with lower coronary calcium incidence, slower calcium progression, and lower all-cause mortality over 7.6 years.

Comparison of a novel method vs the Friedewald equation for estimating low-density lipoprotein cholesterol levels from the standard lipid profile.

IMPORTANCE: In clinical and research settings worldwide, low-density lipoprotein cholesterol (LDL-C) is typically estimated using the Friedewald equation. This equation assumes a fixed factor of 5 for the ratio of triglycerides to very low-density lipoprotein cholesterol (TG:VLDL-C); however, the actual TG:VLDL-C ratio varies significantly across the range of triglyceride and cholesterol levels. OBJECTIVE: To derive and validate a more accurate method for LDL-C estimation from the standard lipid profile using an adjustable factor for the TG:VLDL-C ratio. DESIGN, SETTING, AND PARTICIPANTS: We used a convenience sample of consecutive clinical lipid profiles obtained from 2009 through 2011 from 1,350,908 children, adolescents, and adults in the United States. Cholesterol concentrations were directly measured after vertical spin density-gradient ultracentrifugation, and triglycerides were directly measured. Lipid distributions closely matched the population-based National Health and Nutrition Examination Survey (NHANES). Samples were randomly assigned to derivation (n = 900,605) and validation (n = 450,303) data sets. MAIN OUTCOMES AND MEASURES: Individual patient-level concordance in clinical practice guideline LDL-C risk classification using estimated vs directly measured LDL-C (LDL-CD). RESULTS: In the derivation data set, the median TG:VLDL-C was 5.2 (IQR, 4.5-6.0). The triglyceride and non-high-density lipoprotein cholesterol (HDL-C) levels explained 65% of the variance in the TG:VLDL-C ratio. Based on strata of triglyceride and non-HDL-C values, a 180-cell table of median TG:VLDL-C values was derived and applied in the validation data set to estimate the novel LDL-C (LDL-CN). For patients with triglycerides lower than 400 mg/dL, overall concordance in guideline risk classification with LDL-CD was 91.7% (95% CI, 91.6%-91.8%) for LDL-CN vs 85.4% (95% CI, 85.3%-85.5%) for Friedewald LDL-C (LDL-CF) (P < .001). The greatest improvement in concordance occurred in classifying LDL-C lower than 70 mg/dL, especially in patients with high triglyceride levels. In patients with an estimated LDL-C lower than 70 mg/dL, LDL-CD was also lower than 70 mg/dL in 94.3% (95% CI, 93.9%-94.7%) for LDL-CN vs 79.9% (95% CI, 79.3%-80.4%) for LDL-CF in samples with triglyceride levels of 100 to 149 mg/dL; 92.4% (95% CI, 91.7%-93.1%) for LDL-CN vs 61.3% (95% CI, 60.3%-62.3%) for LDL-CF in samples with triglyceride levels of 150 to 199 mg/dL; and 84.0% (95% CI, 82.9%-85.1%) for LDL-CN vs 40.3% (95% CI, 39.4%-41.3%) for LDL-CF in samples with triglyceride levels of 200 to 399 mg/dL (P < .001 for each comparison). CONCLUSIONS AND RELEVANCE: A novel method to estimate LDL-C using an adjustable factor for the TG:VLDL-C ratio provided more accurate guideline risk classification than the Friedewald equation. These findings require external validation, as well as assessment of their clinical importance. The implementation of these findings into clinical practice would be straightforward and at virtually no cost. TRIAL REGISTRATION: clinicaltrials.gov Identifier: NCT01698489.