Beta Quantification Research Articles

Should the Sampson LDL cholesterol equation replace the Friedewald equation in routine clinical practice? A comparison of three equations against a beta quantification method

Should the Sampson LDL cholesterol equation replace the Friedewald equation in routine clinical practice? A comparison of three equations against a beta quantification method

A-214 Modified CDC Beta-Quantification Reference Method for HDL-C and LDL-C Determinations Using Isotope-Dilution Mass Spectrometry—Pilot Report

Abstract Background It is known that there is average positive 1.6% bias of total cholesterol by modified Abell-Levy-Brodie-Kendall (AK) colorimetric method, which have been the traceable reference measurement procedure (RMP) used by most of clinical guidelines, comparing to those by isotope-dilution mass spectrometry (ID-MS), the most accurate RMP. The CDC beta-quantification (BQ) reference method is currently the only RMP registered JCTLM database for high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) using the AK colorimetric assay after ultracentrifugation. We compared the modified BQ method using ID-MS assay after ultracentrifugation with the original CDC BQ reference method of HDL-C or LDL-C. Methods For this study, 18 commutable serum pools according to the CLSI 37A and 6 external quality assessment survey materials operated by Cholesterol Reference Method Laboratory Network (CRMLN) were used. We used the same ultracentrifugation procedure as in the original CDC BQ reference method, and the bottom fraction cholesterol (BFC) and HDL-C from supernatant after apo B-containing lipoprotein precipitation using heparin/manganese were measured for each sample using both AK and ID-MS methods, then LDL-C was calculated as the difference between BFC and HDL-C. The comparability analysis between methods at multiple medical decision levels (MDL), and Passing-Bablok regression analysis for each analyte were performed. Results Each Passing-Bablok regression equation of modified CDC BQ reference method vs. original CDC BQ reference method for three fractions, BFC, HDL-C, and LDL-C, were as follows; BFC was y (IDMS) = 0.996x (AK) - 0.342 (R = 0.999), for HDL-C was y (IDMS) = 1.007x (AK)-1.037 (R = 0.995), and for LDL-C was y (IDMS) = 0.990x (AK) + 0.860 (R = 0.999). Both cholesterol results by two methods showed excellent correlation and agreement of the three fractions showing regression R larger than 0.995 and slope or intercept containing 1 and 0 in their 95% confidence interval. The mean differences of IDMS against AK method were −0.56% for BFC, −0.51 mg/dL for HDL-C, and −0.35% for LDL-C, respectively. When the regression prediction at MDLs, 40/50/60 mg/dL for HDL-C and 100/130/160 mg/dL for LDL-C were estimated, all the differences were confirmed to be within allowable level claimed by CRMLN member laboratory accreditation criteria, ±1mg/dL for HDL-C and ±2.0% for LDL-C, showing equivalent results against CDC BQ reference method, but average negative bias of −0.72%, −1.59%, and −0.28% for BFC, HDL-C, and LDL-C, respectively are still present. These results of the modified BQ method using ID-MS assay may be promising, because the tedious and less accurate AK-assay can be switched to the ID-MS assay, not sacrificing trueness LDL-C or changing clinical guidelines, but quite large negative bias of HDL-C for some samples should require further investigation. Conclusion We got comparable HDL-C and LDL-C results using modified BQ method using ID-MS assay with those by original CDC BQ reference method using AK colorimetric assay. The quite large negative bias of HDL-C for some samples require large-scale additional further multi-center study among CRMLN network laboratories to evaluate the results observed in our study.

A-203 An Equation based on the Standard Lipid Panel for Calculating Low-Density Lipoproteins-Triglycerides

Abstract Background There is growing evidence that low-density lipoprotein-triglyceride (LDL-TG) may be a better biomarker to define atherosclerotic cardiovascular disease (ASCVD) risk than LDL-cholesterol (LDL-C), which is currently used to stratify risk and as a treatment goal. Because LDL-TG typically requires additional advanced lipid testing, we developed an equation for estimating LDL-TG (eLDL-TG) from the results of the standard lipid panel. Methods Results from a general dyslipidemic population (N = 40 202), which were obtained with beta-quantification (BQ) reference method, were randomly divided into a training and validation datasets and used to develop the equation for estimating LDL-TG shown in Fig. 1A. Association of Sampson-NIH-LDL-C (NIH-LDL-C) and eLDL-TG with ASCVD risk markers was done in the National Heart and Nutrition Examination Survey (NHANES) (N = 37 053) and with ASCVD events in the Atherosclerosis Risk in Communities (ARIC) study (N = 14 749). Results The comparison between eLDL-TG and measured LDL-TG was only modest (R2 = 0.601, slope = 0.611), but eLDL-TG (Fig. 1B) showed better risk stratification than NIH-LDL-C (Fig. 1C) by survival curve analysis in ARIC. Moreover, receiver-operating characteristic (ROC) analysis showed that eLDL-TG was better than all other lipid-marker tests for ASCVD events (AUC: eLDL-TG = 0.633, HDL-C = 0.627, sdLDL-C = 0.621, remnant-cholesterol = 0.613, NonHDL-C = 0.613, TG = 0.603, apoB = 0.598, NIH-LDL-C = 0.590, TC = 0.568). In NHANES, eLDL-TG was more strongly associated with hypertriglyceridemia, obesity, diabetes, metabolic syndrome and increased high-sensitivity C-reactive protein than NIH-LDL-C. Inclusion of eLDL-TG in a Cox-Proportional Hazards Model along with other conventional risk factors (age, sex, race, diabetes, systolic blood pressure, smoking, HDL-C, and total cholesterol) did not further improve risk prediction. Conclusions Like LDL-C, LDL-TG can also be estimated from the results of the standard lipid panel. It is a better univariate risk marker than LDL-C and hence can be useful for initial ASCVD risk stratification.

Comparison of low-density lipoprotein cholesterol equations in patients with dyslipidaemia receiving cholesterol ester transfer protein inhibition

Abstract Background Low-density lipoprotein (LDL-C) lowering is imperative in cardiovascular disease prevention. Effectively translating the evidence for LDL-C lowering to maximize clinical and public health benefits depends on the availability of accurate LDL-C results from clinical laboratories to guide therapy. Furthermore, prior work has raised the possibility that cholesterol esterase transfer protein (CETP) inhibition could interfere with accurate assessment of LDL-C. Purpose We aimed to compare accuracy of three clinically implemented LDL-C equations in a clinical trial of CETP inhibition. Methods Men and women aged 18–75 years with dyslipidaemia were recruited from 17 sites in the Netherlands and Denmark. Patients were randomly assigned to one of nine groups using various combinations of the CETP inhibitor TA-8995, statin therapy, and placebo. In pooled measurements over 12 weeks, we calculated LDL-C by the Friedewald, Martin/Hopkins, and Sampson equations, and compared values with preparative ultracentrifugation (PUC) LDL-C as the reference measure (also known as “beta quantification”). Based on prior literature and dyslipidaemia guidelines, we examined correct classifications across the LDL-C 1.81 mmol/L cutpoint in the subgroup of patients with triglycerides of 1.69–4.51 mmol/L. Results The analysis included 242 patients contributing 921 observations. The full distributions of differences between LDL-C estimates and PUC are shown in Figure 1. Overall median LDL-C differences between estimates and PUC were small: Friedewald, 0.00 (25th, 75th: −0.10, 0.08) mmol/L; Martin/Hopkins, 0.02 (−0.08, 0.10) mmol/L; and Sampson, 0.05 (−0.03, 0.15) mmol/L. In the subgroup with estimated LDL-C <1.81 mmol/L and triglycerides 1.69–4.51 mmol/L, the Friedewald equation underestimated LDL-C with a median difference versus PUC of −0.25 (−0.33, −0.10) mmol/L, whereas the Martin/Hopkins equation corrected this issue with a median difference of 0.00 (−0.08, 0.10) mmol/L and the Sampson equation showed tendency towards underestimation with a median difference of −0.06 (−0.13, 0.00) mmol/L. In patients with triglyceride levels of 1.69–4.51 mmol/L, Figure 2 shows the proportion of LDL-C levels classified by the equations as < or ≥1.81 mmol/L that were correctly classified when compared with PUC. All three equations showed >95% accuracy when estimated LDL-C levels were ≥1.81 mmol/L. However, the proportion of LDL-C observations <1.81 mmol/L that were correctly classified compared with PUC was 71.4% by Friedewald versus 100.0% by Martin/Hopkins and 93.1% by Sampson. Conclusion In Europeans with dyslipidaemia, our analysis shows improved accuracy in LDL-C when using contemporary LDL-C equations over the Friedewald equation, particularly when using the Martin/Hopkins equation. High levels of accuracy with the Martin/Hopkins equation were seen in individuals treated with CETP inhibition and even in the context of low LDL-C and high triglyceride levels. Funding Acknowledgement Type of funding sources: Private company. Main funding source(s): Dezima and NewAmsterdam Pharma

Identification of Dysbetalipoproteinemia by an Enhanced Sampson-NIH Equation for Very Low-Density Lipoprotein-Cholesterol.

Dysbetalipoproteinemia (hyperlipoproteinemia type III, HLP3) is a genetic disorder that results in the accumulation of cholesterol on highly atherogenic remnant particles. Traditionally, the diagnosis of HLP3 depended upon lipoprotein gel electrophoresis or density gradient ultracentrifugation. Because these two methods are not performed by most clinical laboratories, we describe here two new equations for estimating the cholesterol content of VLDL (VLDL-C), which can then be used for the diagnosis of HLP3. Using results from the beta-quantification (BQ) reference method on a large cohort of dyslipidemic patients (N = 24,713), we identified 115 patients with HLP3 based on having a VLDL-C to plasma TG ratio greater than 0.3 and plasma TG between 150 and 1,000 mg/dl. Next, we developed two new methods for identifying HLP3 and compared them to BQ and a previously described dual lipid apoB ratio method. The first method uses results from the standard lipid panel and the Sampson-NIH equation 1 for estimating VLDL-C ( S -VLDL-C), which is then divided by plasma TG to calculate the VLDL-C/TG ratio. The second method is similar, but the Sampson-NIH equation 1 is modified or enhanced ( eS -VLDL-C) by including apoB as an independent variable for predicting VLDL-C. At a cut-point of 0.194, the first method showed a modest ability for identifying HLP3 (sensitivity = 73.9%; specificity = 82.6%; and area under the curve (AUC) = 0.8685) but was comparable to the existing dual lipid apoB ratio method. The second method based on eS -VLDL-C showed much better sensitivity (96.5%) and specificity (94.5%) at a cut-point of 0.209. It also had an excellent AUC score of 0.9912 and was superior to the two other methods in test classification. In summary, we describe two new methods for the diagnosis of HLP3. The first one just utilizes the results of the standard lipid panel and the Sampson-NIH equation 1 for estimating (VLDL-C) ( S -VLDL-C) and can potentially be used as a screening test. The second method ( eS -VLDL-C), in which the Sampson-NIH equation 1 is modified to include apoB, is nearly as accurate as the BQ reference method. Because apoB is widely available at most clinical laboratories, the second method should improve both the accessibility and the accuracy of the HLP3 diagnosis.

LDL-C calculated by Friedewald, Martin-Hopkins, or NIH equation 2 versus beta-quantification: pooled alirocumab trials

Accurate assessment of LDL-C levels is important, as they are often used for treatment recommendations. For many years, plasma LDL-C levels were calculated using the Friedewald equation, but there are limitations to this method compared with direct measurement via beta-quantification (BQ). Here, we assessed differences between the Friedewald, Martin-Hopkins, and NIH equation 2 methods of calculating LDL-C and the “gold standard” BQ method using pooled phase 3 data with alirocumab. All randomized patients were included irrespective of the treatment arm (n = 6,122). We compared pairs of LDL-C values (n = 17,077) determined by each equation and BQ. We found that BQ-derived LDL-C values ranged from 1 to 397 mg/dl (mean 90.68 mg/dl). There were strong correlations between Friedewald-calculated, Martin-Hopkins–calculated, and NIH equation 2–calculated LDL-C with BQ-determined LDL-C values (Pearson's correlation coefficient = 0.985, 0.981, and 0.985, respectively). Importantly, for BQ-derived LDL-C values ≥70 mg/dl, only 3.2%, 1.4%, and 1.8% of Friedewald-calculated, Martin-Hopkins–calculated, and NIH equation 2–calculated values were <70 mg/dl, respectively. When triglyceride (TG) levels were <150 mg/dl, differences between calculated and BQ-derived LDL-C values were minimal, regardless of the LDL-C level (<40, <55, or <70 mg/dl). However, when TG levels were >150 mg/dl, NIH equation 2 provided greater accuracy than Friedewald or Martin-Hopkins. When TGs were >250 mg/dl, inaccuracies were seen with all three methods, although NIH equation 2 remained the most accurate. In conclusion, LDL-C calculated by any of the three methods can guide treatment decisions for most patients, including those treated with proprotein convertase subtilisin/kexin type 9 inhibitors.

Discordantly Elevated Apolipoprotein B versus Low-Density Lipoprotein Cholesterol is Associated with Remnant Lipoproteins and Increased Cardiovascular Events

Abstract Atherosclerotic cardiovascular disease is a result of low-density lipoprotein (LDL) particles becoming trapped in arterial walls and forming plaques which ultimately restrict blood-flow. LDL cholesterol (LDL-C) and apolipoprotein B (apoB) are highly correlated measures of plaque-causing LDL particles. Both have been shown to predict major adverse cardiac events (MACE). ApoB is also carried on remnant lipoproteins (RLP). RLP-cholesterol (RLP-C) is increasingly appreciated as a MACE risk-factor. This study aimed to define discordances between apoB and LDL-C in a large data set from a clinical reference laboratory. We then applied this definition to evaluate which measure predicted the risk of MACE in a patient cohort referred for coronary angiography with &amp;gt;10 years follow-up. LDL-C was measured by beta-quantification and RLP-C was defined as total cholesterol – LDL-C – HDL-C. Apo B discordance relative to LDL-C was determined by linear regression in a discovery cohort (n=17,203) using beta quantification. Discordance was defined by quartiles of the residual-apoB (expected–actual); discordant-low (&amp;lt;25th percentile), concordant (25th to 75th percentile) and discordant-high (&amp;gt;75th percentile). Associations with prevalence and incident of MACE were evaluated by odds-ratio and logistic regression. Risk of MACE was calculated based on the apoB-discordance and reported MACE events by several years follow up in a separate cohort (n=501). In the discovery cohort, age ranged from 18-95 years, 51% were female and mean (±SD) lipid values were: ApoB: 100.4 ± 30.0mg/dl, LDL-C: 121.7 ± 47.9mg/dl, and RLP-C: 17.2 ± 26.9mg/dl. Expected-apoB was described by the formula: (LDL-c X 0.6278 + 24.07, R=0.88). Residual-apoB (discordance) ranged from -1037 to 581.2 with a mean 0.01±18.6, and notably increased with triglyceride concentration (rho=0.65) and with RLP-C (rho=0.64), but was minimally influenced by apoB (rho=0.35) and LDL-C (rho=0.009) (p&amp;lt;0.001 all cases). In the clinical follow-up cohort, age ranged from 26-77 years, 42% were female, 64% were current/former smokers, and 28% were on lipid-lowering therapy. Mean (±SD) lipids were: apoB: 97.8 ± 20.9mg/dl, LDL-C: 124.6 ± 36.6mg/dl, and RLP-C: 34.9 ± 25.6mg/dl. Serum triglycerides among subjects discordant-low apoB, concordant and discordant-high apoB were 148mg/dL, 157mg/dL and 238mg/dL, respectively; similarly for RLP-C. A total of 192 events occurred during a mean of 9 years follow-up. Subjects with discordantly elevated apoB had a significantly higher incidence of MACE compared to those with concordant values (47% vs. 36%, p=0.03). There was no difference in MACE for subjects with discordantly low apoB (35% vs. 36%). These data support previous reports of an association between apoB and LDL-C and the superior performance of apoB when discordantly elevated. Our data expand on previous studies by applying an externally defined threshold for discordant-apoB. Our data indicate that triglycerides, RLP-C are associated with discordances and MACE.

Comparison of the Japan Society of Clinical Chemistry reference method and CDC method for HDL and LDL cholesterol measurements using fresh sera

ObjectivesIn 2009, the Japan Society of Clinical Chemistry (JSCC) recommended a reference method for the measurement of serum high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C) levels. This automated method uses cholesterol esterase-cholesterol dehydrogenase to measure cholesterol levels in fractions obtained after ultracentrifugation and dextran sulfate/magnesium chloride precipitation. In the present study, using fresh samples, we compared the LDL-C and HDL-C levels measured using this method with those measured using the traditional Centers for Disease Control and Prevention (CDC)-beta-quantification (BQ) method. Designand methods: Using both the JSCC and CDC-BQ methods, LDL-C/HDL-C levels were measured in 47 non-diseased and 126 diseased subjects, whose triglyceride levels were lower than 11.29 ​mmol/L (1000 ​mg/dL). ResultsFor LDL-C, the equation of the line representing the correlation between the two methods was y ​= ​0.991x + 0.009 ​mmol/L; r ​= ​0.999; and Sy/x ​= ​0.025 ​mmol/L, where x is the mean LDL-C level measured using the CDC-BQ method. Similarly, for HDL-C, the equation of the line representing the correlation between the two methods was y ​= ​0.988x + 0.041 ​mmol/L, r ​= ​0.999, and Sy/x ​= ​0.019 ​mmol/L, where x is the mean HDL-C level measured using the CDC-BQ method. ConclusionsThe JSCC method agreed with the CDC-BQ method in cases of both non-diseased and diseased subjects, including those with dyslipidemia.

Verification of Low-Density Lipoprotein Cholesterol Levels Measured by Anion-Exchange High-Performance Liquid Chromatography in Comparison with Beta Quantification Reference Measurement Procedure.

A new lipoprotein testing method based on anion-exchange HPLC (AEX-HPLC) was recently established. We verified the accuracy of LDL-C levels, a primary therapeutic target for the prevention of cardiovascular disease (CVD), measured by AEX-HPLC comparing with LDL-C levels measured by beta quantification-reference measurement procedure (BQ-RMP), homogenous assays, and calculation methods. We compared LDL-C levels measured by AEX-HPLC (adLDL-Ch: LDL-Ch and IDL-Ch) and BQ-RMP using blood samples from 52 volunteers. AdLDL-Ch levels were also compared with those measurements by homogeneous assays and calculation methods (Friedewald equation, Martin equation, and Sampson equation) using blood samples from 411 participants with dyslipidemia and/or type 2 diabetes. The precision and accuracy of adLDL-Ch were verified by BQ-RMP. The mean percentage bias [bias (%)] for LDL-C was 1.2%, and the correlation was y = 0.990x + 3.361 (r = 0.990). These results met the acceptable range of accuracy prescribed by the National Cholesterol Education Program. Additionally, adLDL-Ch levels were correlated with LDL-C levels measured by the 2 homogeneous assays (r > 0.967) and the calculation methods (r > 0.939), in serum samples from patients with hypertriglyceridemia. AEX-HPLC is a reliable method for measuring LDL-C levels for CVD risk in daily clinical laboratory analyses.

Measuring the contribution of Lp(a) cholesterol towards LDL-C interpretation

BackgroundLipoprotein(a) [Lp(a)] is a pro-atherogenic and pro-thrombotic LDL-like particle recognized as an independent risk factor for cardiovascular disease (CVD). The cholesterol within Lp(a) (Lp(a)-C) contributes to the reported LDL-cholesterol (LDL-C) concentration by nearly all available methods. Accurate LDL-C measurements are critical for identification of genetic dyslipidemias such as familial hypercholesterolemia (FH). FH diagnostic criteria, such as the Dutch Lipid Clinic Network (DLCN) criteria, utilize LDL-C concentration cut-offs to assess the likelihood of FH. Therefore, failure to adjust for Lp(a)-C can impact accurate FH diagnosis and classification, appropriate follow-up testing and treatments, and interpretation of cholesterol-lowering treatment efficacy. ObjectiveIn this study, we use direct Lp(a)-C measurements to assess the potential misclassification of FH from contributions of Lp(a)-C to reported LDL-C in patient samples submitted for advanced lipoprotein profiling. MethodsA total of 31,215 samples submitted for lipoprotein profiling were included. LDL-C was measured by beta quantification or calculated by one of three equations. Lp(a)-C was measured by quantitative lipoprotein electrophoresis. DLCN LDL-C cut-offs were applied to LDL-C results before and after accounting for Lp(a)-C contribution. ResultsLp(a)-C was detected in 8665 (28%) samples. A total of 940 subjects were reclassified to a lower DLCN LDL-C categories; this represents 3% of the total patient series or 11% of subjects with measurable Lp(a)-C. ConclusionLp(a)-C is present in a significant portion of samples submitted for advanced lipid testing and could cause patient misclassification when using FH diagnostic criteria. These misclassifications could trigger inappropriate follow-up, treatment, and cascade testing for suspected FH.

Appropriate reference region selection of 18F-florbetaben and 18F-flutemetamol beta-amyloid PET expressed in Centiloid

The Centiloid (CL) is a method for standardizing amyloid beta (Aβ) quantification through different ligands and methods. To find the most appropriate reference region to reduce the variance in the Aβ CL unit between 18F-florbetaben (FBB) and 18F-flutemetamol (FMM), we conducted head-to-head comparisons from 56 participants using the direct comparison of FBB-FMM CL (dcCL) method with four reference regions: cerebellar gray (CG), whole cerebellum (WC), WC with brainstem (WC + B), and pons. The FBB and FMM dcCL units were highly correlated in four reference regions: WC (R2 = 0.97), WC + B (R2 = 0.98), CG (R2 = 0.92), and pons (R2 = 0.98). WC showed the largest effect size in both FBB and FMM. Comparison of the variance of the dcCL values within the young control group showed that with FBB, WC + B had the smallest variance and with FMM, the WC had the smallest variance. Additionally, WC + B showed the smallest absolute difference between FBB and FMM, followed by the WC, pons, and CG. We found that it would be reasonable to use the WC or WC + B as the reference region when converting FBB and FMM SUVRs into dcCL, which can increase the accuracy of standardizing FBB and FMM PET results.

Underestimation of Low Density Lipoprotein-Cholesterol With the Friedewald Equation Versus a Direct Homogenous Low Density Lipoprotein-Cholesterol Assay.

Low-density lipoprotein cholesterol (LDL-C) concentrations are the primary therapeutic target in patients with atherosclerotic cardiovascular disease (ASCVD). However, at low LDL-C concentrations, there is a significant underestimation using the Friedewald equation compared with ultracentrifugation. In this pilot study, we compared LDL-C concentrations obtained using the Friedewald equation (LDL-F) vs those concentrations from a direct LDL-C (LDL-D) assay in 152 consecutive specimens from patients with triglyceride levels between 200-399 mg/dL and LDL-F <100 mg/dL. Also, we compared LDL-F and LDL-D results to the novel formula (LDL-N). The LDL-F value was significantly lower than that of LDL-D when LDL concentrations were 70-99 mg/dL (P <.001, 14% negative bias), and this decrease was accentuated in specimens with LDL <70 mg/dL, (P <.001, 27% negative bias). When compared with the LDL-N value, LDL-F and LDL-D values showed a 17% and 2% negative bias for specimens with LDL-C values of 70-99 mg/dL and 36% and 1% negative bias, respectively, at LDL-C <70 mg/dL (P <.001 for comparisons of LDL-F and LDL-N values). To provide accurate LDL-C levels in patients at high risk for ASCVD, if beta quantification by ultracentrifugation is unavailable and if LDL-C is <100 mg/dL and triglycerides are 200-399 mg/dL, laboratories should revert to direct LDL-C measurements or use the novel formula. Although LDL-N is more cost-effective, LDL-D can be run on most platforms, does not require a specimen from a fasting individual, is standardized, and has the advantage of being validated in large trials such as the Heart Protection Study.

Safety and efficacy of LY3015014, a monoclonal antibody to proprotein convertase subtilisin/kexin type 9 (PCSK9): a randomized, placebo-controlled Phase 2 study.

AimsThe objective of this study was to evaluate the efficacy, safety, and tolerability of LY3015014 (LY), a neutralizing antibody of proprotein convertase subtilisin/kexin type 9 (PCSK9), administered every 4 or 8 weeks in patients with primary hypercholesterolaemia, when added to a background of standard-of-care lipid-lowering therapy, including statins.Methods and resultsDouble-blind, placebo-controlled trial randomized 527 patients with primary hypercholesterolaemia from June 2013 to January 2014 at 61 community and academic centres in North America, Europe, and Japan. Patients were randomized to subcutaneous injections of LY 20, 120, or 300 mg every 4 weeks (Q4W); 100 or 300 mg every 8 weeks (Q8W) alternating with placebo Q4W; or placebo Q4W. The primary endpoint was percentage change from baseline in low-density lipoprotein cholesterol (LDL-C) by beta quantification at Week 16. The mean baseline LDL-C by beta quantification was 136.3 (SD, 45.0)mg/dL. LY3015014 dose-dependently decreased LDL-C, with a maximal reduction of 50.5% with 300 mg LY Q4W and 37.1% with 300 mg LY Q8W compared with a 7.6% increase with placebo maintained at the end of the dosing interval. There were no treatment-related serious adverse events (AEs). The most common AE terms (>10% of any treatment group) reported more frequently with LY compared with placebo were injection site (IS) pain and IS erythema. No liver or muscle safety issues emerged.ConclusionsLY3015014 dosed every 4 or 8 weeks, resulted in robust and durable reductions in LDL-C. No clinically relevant safety issues emerged with the administration of LY. The long-term effects on cardiovascular outcomes require further investigation.

LDL cholesterol performance of beta quantification reference measurement procedure

BackgroundAccurate measurement of blood lipids is crucial in cardiovascular disease risk management. The Centers for Disease Control and Prevention (CDC) Cholesterol Reference Method Laboratory Network (CRMLN) has assured the accuracy of these measurements forover 20years using beta quantification (BQ) method as reference measurement procedure (RMP) for high- and low-density lipoprotein cholesterol (HDL-C, LDL-C). Only limited data exist about the performance of the BQ RMP. MethodsBottom fraction cholesterol (BFC), HDL-C, and LDL-C results after ultracentrifugation from the CDC lipid reference laboratory and the Japanese CRMLN laboratory were compared using 280 serum samples measured over the past 15years. Data were compared statistically using method comparison and bias estimation analysis. ResultsRegression analysis between CDC (x) and Osaka (y) for BFC, HDL-C, and LDL-C were y=0.988x+1.794 (R2=0.997), y=0.980x+1.118 (R2=0.994), and y=0.987x+1.200 (R2=0.997), respectively. The Osaka laboratory met performance goals for 90% to 95% of the CDC reference values. ConclusionsThe BQ method by the Osaka CRMLN laboratory is highly accurate and has been stable for over 15years. Accurate measurement of BFC is critical for the determination of LDL-C.

Pancreas++: Automated Quantification of Pancreatic Islet Cells in Microscopy Images

The microscopic image analysis of pancreatic Islet of Langerhans morphology is crucial for the investigation of diabetes and metabolic diseases. Besides the general size of the islet, the percentage and relative position of glucagon-containing alpha-, and insulin-containing beta-cells is also important for pathophysiological analyses, especially in rodents. Hence, the ability to identify, quantify and spatially locate peripheral, and “involuted” alpha-cells in the islet core is an important analytical goal. There is a dearth of software available for the automated and sophisticated positional quantification of multiple cell types in the islet core. Manual analytical methods for these analyses, while relatively accurate, can suffer from a slow throughput rate as well as user-based biases. Here we describe a newly developed pancreatic islet analytical software program, Pancreas++, which facilitates the fully automated, non-biased, and highly reproducible investigation of islet area and alpha- and beta-cell quantity as well as position within the islet for either single or large batches of fluorescent images. We demonstrate the utility and accuracy of Pancreas++ by comparing its performance to other pancreatic islet size and cell type (alpha, beta) quantification methods. Our Pancreas++ analysis was significantly faster than other methods, while still retaining low error rates and a high degree of result correlation with the manually generated reference standard.

Secreted APP and amyloid beta quantification in SH‐SY5Y cell media using high sensitivity AlphaLISA kits

The aggregation and accumulation of amyloid beta peptides is one of the pathological hallmarks of Alzheimer's disease (AD). Amyloid beta is produced by sequential proteolytic cleavage of Amyloid Precursor Protein (APP) by beta‐ and gamma‐secretase, which are plausible molecular targets for AD treatment. Thus, identification of modulators of these secretases could lead to new therapeutics for this prevalent and debilitating disease. SH‐SY5Y are human neuroblastoma cells that express APP and the various secretases that cleave this membrane‐bound protein into sAPPβ, sAPPα and amyloid beta peptides. We have developed new highly sensitive and specific AlphaLISA kits that allow the detection of endogenous amounts of these various APP metabolites. Specific inhibitors of alpha‐, beta‐ and gamma‐secretase were used to modulate the relative activities of these enzymes. Application of these inhibitors resulted in characteristic signature levels of product sAPPα, sAPPβ, Aβ 1–40 and Aβ x‐40 (defined as the combined amount of both Aβ 1–40 and Aβ 17–40) from SH‐SY5Y cell culture supernatants. These results show that the new AlphaLISA kits have sufficient sensitivity and specificity to study this pathway, even in wild‐type cells that do not overexpress APP or BACE. The Z′‐factor obtained for these cell‐based secretase assays was greater than 0.6, indicating reproducible and robust assays for HTS. In summary, these new AlphaLISA detection kits can accurately quantitate endogenous APP cleavage products. This will in turn result in a better understanding of the APP degradation pathway and facilitate the identification of novel therapeutic drugs for the treatment of Alzheimer's disease.

Friedewald equation underestimates low‐density lipoprotein cholesterol at low concentrations in young people with and without Type 1 diabetes

Although the limitations of the Friedewald-calculated serum low-density lipoprotein cholesterol (LDL-C) are well recognized, many diabetes and lipid guidelines propose LDL-C as a therapeutic target. The validity of calculated LDL-C in people with Type 1 diabetes (T1DM) is uncertain and the use of alternatives such as non-high-density lipoprotein cholesterol (non-HDL-C) or apolipoprotein measurement unexplored. We have therefore measured LDL-C with the designated reference method and examined some of the potential sources of such bias, including plasma concentrations of other lipids and apolipoproteins. Seventy-four people with T1DM and 80 healthy control subjects were recruited. Fasting samples were collected for analysis of lipid profiles by a beta-quantification (BQ) reference method and by routine laboratory methods including direct HDL-C and calculation of LDL-C using the Friedewald formula. Overall, Friedewald LDL-C was 0.29 +/- 0.02 (mean +/- SE) mmol/l (P < 0.001) lower in the two groups than by the BQ method. This resulted in misclassification of approximately 50% of people with a calculated LDL-C < 2.0 mmol/l. Overestimation of HDL-C by the routine assay [0.08 +/- 0.01 mmol/l (P < 0.001)] accounted for approximately 28% of the error in calculation of LDL-C and the remainder appeared to be as a result of triglyceride in lipoprotein particles other than very-low-density lipoprotein (VLDL). Correlation of non-HDL-C with apolipoprotein B was better than LDL-C with apolipoprotein B for both assays in both diabetic and non-diabetic populations. Calculated LDL-C is unsuitable as a therapeutic target in T1DM. Consideration should be give to the greater use of apolipoprotein B or non-HDL-C in clinical practice.

Multicentric evaluation of the homogeneous LDL-cholesterol Plus assay: Comparison with beta-quantification and Friedewald formula

Objectives To evaluate the analytical and clinical performance of a new version of the LDL-C Plus assay and compare it with the beta-quantification (BQ) method in a multicenter study. Design and methods Direct LDL-C was measured in 169 fresh pooled samples and in 830 clinical samples with known LDL-C by BQ. The reactivity of lipoproteins and the effect of hemoglobin, bilirubin and chylomicrons (CM) were studied. Results Direct LDL-C total imprecision was < 2.2%; inaccuracy < ± 2.5% (unaffected by triglycerides up to 9.5 mmol/L); and total error 9.8%. Direct assay reacted with 95%, 50% and 25% of the cholesterol in the LDL, intermediate (IDL) and VLDL fractions, respectively. A significant association was observed with BQ. Icteric samples showed a negative bias and the effect of CM was variable. A positive bias was observed when VLDL-cholesterol/triglyceride ratio was > 0.57. Conclusions LDL-C Plus assay represents a valid alternative to BQ for clinical laboratories.

Sustained postprandial decrease in plasma levels of LDL cholesterol in patients with type‐2 diabetes mellitus

Objective. Low density lipoprotein cholesterol (LDL‐C) is an independent and modifiable risk factor for development of cardiovascular disease (CVD). Postprandial lipid metabolism has been linked to CVD, but little is known about the postprandial LDL‐C profile in patients with type‐2 diabetes (T2DM). We aimed to study the postprandial levels of LDL‐C in T2DM patients. Material and methods. After an overnight fast, 74 T2DM patients, mean age approximately 60 years, were served a standard fat‐rich meal of 3,515 kJ containing 54 % fat, 13 % protein and 33 % carbohydrates. Only drinking water was allowed postprandially. Blood samples were drawn at times 0 (fasting), 1.5, 3.0, 4.5 and 6.0 h (postprandial). In all samples, LDL‐C was measured with modified beta quantification (separation by ultracentrifugation followed by measurement of infranate high density lipoprotein cholesterol (HLD‐C) using a homogeneous assay). Results. At all postprandial times, levels of LDL‐C showed highly significant (p<0.005) decreases compared to time 0 (mean [95 % CI] maximum change in LDL‐C levels at 3.0 h: −0.16 mmol/L [−0.12; −0.20]; p<0.001). Independently of fasting LDL‐C levels and ongoing statin therapy, LDL‐C decreased significantly more in female compared to male patients postprandially (mean [95 % CI] maximum unadjusted change versus time 0 in LDL‐C for men [n = 56] at 3.0 h: −0.14 mmol/L [−0.19; −0.10], p<0.001; for women [n = 18] at 4.5 h: −0.26 mmol/L [−0.35; −0.18], p<0.001; −0.14 mmol/L [−0.24; −0.05], p = 0.005 between genders for the mean [95 % CI] fasting adjusted difference at 4.5 h in the change versus time 0 in LDL‐C; gender by time interaction: p = 0.007 (repeated measures mixed model)). Conclusions. In T2DM patients served a fat‐rich meal, levels of LDL‐C decreased significantly more in women compared to men postprandially, irrespective of fasting levels or ongoing statin therapy. This might have implications in the atherosclerotic process and on any difference in the risk of CVD between genders.

Nonfasting Low-Density Lipoprotein Testing: Utility for Cholesterol Screening in Pediatric Primary Care

This prospective study assessed the clinical application of a nonfasting low-density lipoprotein cholesterol measure in a pediatric primary care population. A homogenous direct low-density lipoprotein cholesterol assay was tested in healthy children, aged 4 to 12 years, at risk for hyperlipidemia, as defined by American Academy of Pediatrics, and including patients with incomplete family histories. This nonfasting homogeneous assay was comparable to modified beta quantification, the gold standard reference method of measuring low-density lipoprotein cholesterol, and the current recommended screening method, total cholesterol. Results from the study suggest that this nonfasting assay can provide more direct low-density lipoprotein cholesterol measurements for healthy children, with improved clinical utility and greater overall patient convenience in testing for important cholesterol abnormalities.