Meeusen, Jeffrey W.

Background Accurate measurement of the cholesterol within lipoprotein(a) (Lp[a]‐C) and its contribution to low‐density lipoprotein cholesterol (LDL‐C) has important implications for risk assessment, diagnosis, and treatment of atherosclerotic cardiovascular disease, as well as in familial hypercholesterolemia. A method for estimating Lp(a)‐C from particle number using fixed conversion factors has been proposed (Lp[a]‐C from particle number divided by 2.4 for Lp(a) mass, multiplied by 30% for Lp[a]‐C). The accuracy of this method, which theoretically can isolate “Lp(a)‐free LDL‐C,” has not been validated. Methods and Results In 177 875 patients from the VLDbL (Very Large Database of Lipids), we compared estimated Lp(a)‐C and Lp(a)‐free LDL‐C with measured values and quantified absolute and percent error. We compared findings with an analogous data set from the Mayo Clinic Laboratory. Error in estimated Lp(a)‐C and Lp(a)‐free LDL‐C increased with higher Lp(a)‐C values. Median error for estimated Lp(a)‐C <10 mg/dL was −1.9 mg/dL (interquartile range, −4.0 to 0.2); this error increased linearly, overestimating by +30.8 mg/dL (interquartile range, 26.1–36.5) for estimated Lp(a)‐C ≥50 mg/dL. This error relationship persisted after stratification by overall high‐density lipoprotein cholesterol and high‐density lipoprotein cholesterol subtypes. Similar findings were observed in the Mayo cohort. Absolute error for Lp(a)‐free LDL‐C was +2.4 (interquartile range, −0.6 to 5.3) for Lp(a)‐C<10 mg/dL and −31.8 (interquartile range, −37.8 to −26.5) mg/dL for Lp(a)‐C≥50 mg/dL. Conclusions Lp(a)‐C estimations using fixed conversion factors overestimated Lp(a)‐C and subsequently underestimated Lp(a)‐free LDL‐C, especially at clinically relevant Lp(a) values. Application of inaccurate Lp(a)‐C estimations to correct LDL‐C may lead to undertreatment of high‐risk patients.

AbstractBackgroundCeramides are bioactive lipid species that mediate numerous cell-signaling events. Elevated plasma ceramides concentration constitutes a risk factor for several pathologies. Multiple studies have affirmed the plasma concentrations of 4 specific ceramides (Cer16:0, Cer18:0, Cer24:0, and Cer24:1) can predict cardiovascular disease risk. Furthermore, these ceramides can be altered by many lipid-lowering therapies. Understanding the biological variability within an individual, and within a population, will further inform the clinical use of plasma ceramides as a biomarker. In this study, we aimed to define the intra- and interbiological variability of ceramides in a healthy reference population in a weekly and monthly manner.MethodsFasting plasma from 24 healthy adults was collected daily (5 days), weekly (4 weeks), and monthly (7 months). Ceramide concentrations were measured with liquid chromatography–mass spectrometry (LC–MS). For analysis, we used random-effects regression models to estimate variance components.ResultsThe analytical variability was smaller compared to the biological variability overall. The greatest variation reported was between-subject variation for all ceramide species. The critical difference-reference change value (RCV) for within-subject variations monthly were 0.07 mcmol/L (Cer16:0), 0.04 mcmol/L (Cer18:0), 1.09 mcmol/L (Cer24:0), and 0.27 mcmol/L (Cer24:1). The index of individuality (IOI) of ceramides were 0.82 (Cer16:0), 0.96 (Cer18:0), 1.06 (Cer24:0), and 0.89 (Cer24:1). The most consistent ceramide species was Cer18:0 with the lowest within- and between-subject critical differences in weekly and monthly measurements.ConclusionsOverall, this study demonstrates that the variability of ceramide concentrations at different time points is minimal within individuals, allowing a single draw to be sufficient at least in a yearly time frame.

Abstract Background The National Kidney Foundation recently endorsed the refit Chronic Kidney Disease Collaboration (CKD-EPI) equation for estimated glomerular filtration rate (eGFR) using creatinine, age and sex [2021 eGFRCr(AS)] without a coefficient for race. We evaluated the impact of adopting the 2021 eGFRCr(AS) equation or a variation of the 2009 CKD-EPI eGFR equation without race [2009 CKD-EPI eGFRCr(ASR-NB)] compared to the original CKD-EPI eGFR [2009 eGFRCr(ASR)]. Methods The studied population included patients with a clinically ordered iothalamate clearance (n = 33 889). Bias was assessed as the difference between measured and estimated GFR, P30 was defined as the percentage of estimates within 30% of measured GFR, and concordance was determined according to relevant clinical thresholds. Results Among Black patients, the median bias for 2009 eGFRCr(ASR), 2009 eGFRCr(ASR-NB), and 2021 eGFRCr(AS) was −1.32 mL min−1 (1.73 m2)−1 (95CI −2.46 to −0.26), −8.81 mL min−1 (1.73 m2)−1 (95CI −9.93 to −7.58), and −6.08 mL min−1 (1.73 m2)−1 (95CI −7.18 to −4.92), respectively. The median bias among non-Black patients was −0.15 m min−1 (1.73 m2)−1 (95CI −0.84 to −0.08) for 2021 eGFRcr(AS) compared to −3.09 mL min−1 (1.73 m2)−1 (95CI −3.17 to −3.03) for the 2009 eGFRCr(ASR). P30 and concordance were not significantly different in either racial group. The net reclassification improvement at a measured GFR &lt;20 mL min−1 (1.73 m2)−1 was 6.4% (95CI 0.36 to 12.4) for Black patients and −5.1% (95CI −6.0 to −4.1) for non-Black patients using the 2021 eGFRCr(AS) equation. Conclusions Overall, the change in reported eGFR was minimal. However, these changes led to significant reclassification improvements at lower eGFR, which will indirectly improve equitable access to CKD resources.

Assessment of renal function relies on the estimation of the glomerular filtration rate (eGFR). Existing eGFR equations, usually based on serum levels of creatinine and/or cystatin C, are not uniformly accurate across patient populations. In the present study, we expanded a recent proof-of-concept approach to optimize an eGFR equation targeting the adult population with and without chronic kidney disease (CKD), based on a nuclear magnetic resonance spectroscopy (NMR) derived ‘metabolite constellation’ (GFRNMR). A total of 1855 serum samples were partitioned into development, internal validation and external validation datasets. The new GFRNMR equation used serum myo-inositol, valine, creatinine and cystatin C plus age and sex. GFRNMR had a lower bias to tracer measured GFR (mGFR) than existing eGFR equations, with a median bias (95% confidence interval [CI]) of 0.0 (−1.0; 1.0) mL/min/1.73 m2 for GFRNMR vs. −6.0 (−7.0; −5.0) mL/min/1.73 m2 for the Chronic Kidney Disease Epidemiology Collaboration equation that combines creatinine and cystatin C (CKD-EPI2012) (p < 0.0001). Accuracy (95% CI) within 15% of mGFR (1-P15) was 38.8% (34.3; 42.5) for GFRNMR vs. 47.3% (43.2; 51.5) for CKD-EPI2012 (p < 0.010). Thus, GFRNMR holds promise as an alternative way to assess eGFR with superior accuracy in adult patients with and without CKD.

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 &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 (&lt;25th percentile), concordant (25th to 75th percentile) and discordant-high (&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&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.

Abstract The guideline-recommended lipid panel for cardiovascular disease (CVD) risk assessment measures total cholesterol, high-density lipoprotein (HDL) cholesterol, triglycerides, and calculated low-density lipoprotein (LDL) cholesterol. Measured cholesterol in subfractions of HDL and LDL purportedly improve CVD risk prediction. Homogenous enzymatic methods are now available for measurement of the cholesterol within small dense LDL (sLDL), small dense HDL (HDL3), and triglyceride-rich lipoproteins (TRL). For meaningful interpretation of these measurements, an understanding of the potential sources and extent of result variability is needed. The smallest difference between serial measurements within a patient that likely reflects a change in clinical status is called the reference change value (RCV). Biological variability and reference change values (RCV) are well-characterized for basic lipids but there is limited information for sLDL, HDL3 or TRL. The objective of this study was to determine intra- and inter-individual variability for sLDL, HDL3, and TRL in a healthy reference population. Serum samples were collected from 24 healthy subjects (n=14 female/10 male) daily for three days (non-fasting), daily for five days (fasting), weekly for four weeks (fasting), and monthly for 7 months (fasting). sLDL, HDL3, and TRL cholesterol were measured in duplicate by enzymatic colorimetric assays (Denka, Japan) on a Roche Cobas c501. Each source of variability (between subject, within subject, and analytical) was calculated using random-effects regression models to estimate each variance component including the overall variation, standard deviation (SD), coefficient of variation (CV), and proportion of total variance (between-subject, within-subject, and analytical). Using these analytical and biological variances, the reference change value (RCV), index of individuality (IoI), and intraclass correlation coefficient (ICC) were determined. Analytic variability (CVa) from monthly testing was 1.2%, 1.1%, and 1.5% for sLDL, HDL3, and TRL, respectively. Monthly within-subject variability (CVw) was 17.1% for sLDL, 7.4% for HDL3 and 25.7% for TRL. Monthly between-subject variability (CVb) was 32.2%, 13.93%, and 33.4% for sLDL, HDL3, and TRL, respectively. Most of the monthly variation was attributed to between-subject variation for all three tests. Within-subject variation accounted for 37% of TRL variation and 22% for both sLDL and HLD3. Within-subject RCVs for monthly measurements were 16.9mg/dL for sLDL, 5.3mg/dL for HDL3, and 15.1mg/dL for TRL. IoIs for monthly testing were 0.81 for TRL, 0.57 for sLDL, and 0.61 for HDL3. Our data demonstrate that sLDL, HDL3, and TRL show low analytical variability, moderate within-subject variability, but high between-subject variability when measured by homogenous assays in a healthy population. The IoI value (&gt;0.6) for TRL suggests use of a reference interval is appropriate for result interpretation. Conversely, clinical cut-points may be more useful than reference intervals for sLDL and HDL3 which had IoIs ~0.6. These findings may be useful for clinical interpretation, particularly when comparing successive measurements of these analytes.

Abstract BACKGROUND Dyslipoproteinemias can be classified by their distinct lipoprotein patterns, which helps determine atherosclerotic cardiovascular disease (ASCVD) risk and directs lipid management but this has required advanced laboratory testing. OBJECTIVE To develop a new algorithm for classifying lipoprotein disorders that only relies on the standard lipid panel. METHODS Lipid thresholds for defining the different lipoprotein phenotypes were derived for Non-High-Density Lipoprotein-Cholesterol (NonHDL-C) and Triglycerides (TG) to be concordant when possible with the current US Multi-Society guidelines for blood cholesterol management. RESULTS The new classification method categorizes patients into all the classical Fredrickson-like phenotypes except for Type III dysbetalipoproteinemia. In addition, a new hypolipidemic phenotype (Type VI) due to genetic mutations in apoB-metabolism is described. The validity of the new algorithm was confirmed by lipid analysis by NMR (N = 11,365) and by concordance with classification by agarose gel electrophoresis/beta-quantification (N = 5504). Furthermore, based on the Atherosclerosis Risk in Communities (ARIC) cohort (N = 14742), the lipoprotein phenotypes differ in their association with ASCVD (TypeV > IIb > IVb > IIa > IVa > normolipidemic) and can be used prognostically as risk enhancer conditions in the management of patients. CONCLUSIONS We describe a clinically useful lipoprotein phenotyping system that is only dependent upon the standard lipid panel. It, therefore, can be easily implemented for increasing compliance with current guidelines and for improving the care of patients at risk for ASCVD.

Objective: Cardiovascular disease remains a leading cause of mortality worldwide. Ceramide scores have been associated with adverse outcomes in patients with established coronary artery disease. The prognostic value of ceramide score has not been assessed in the general population. We tested the hypothesis that ceramide scores are associated with major adverse cardiac events (MACE) in a community-based cohort with average coronary artery disease burden at enrollment. Approach and results: In a prospective community-based cohort, we performed passive follow-up using a record linkage system to ascertain the composite outcome of MACE, defined as acute myocardial infarction, coronary revascularization (bypass grafting or percutaneous intervention), stroke, or death. Ceramides were analyzed as log-transformed continuous variables, ratios or scores, and quartiles with adjustment for confounders. We analyzed 1131 subjects, 52% females, mean age±(SD) 64±9 years. After a median follow-up of 13.3 years (Q1, 12.7; Q3, 14.4), 486 patients experienced a MACE: myocardial infarction (80), coronary artery bypass surgery (34), percutaneous coronary intervention (62), stroke (94), and all-cause death (362). Ceramide ratios were significantly associated with MACE independently of LDL-c (low-density lipoprotein cholesterol) and conventional coronary artery disease risk factors. Those in the highest quartile of ceramide score had nearly 1.5-fold risk of MACE, hazard ratio, 1.47 (95% CI, 1.12–1.92). There was a dose-response association across quartiles of ceramide ratios and MACE. Conclusions: Elevated ceramide score is a robust predictor of cardiovascular disease and MACE in the community. The risk conferred by the ceramide score has a dose-response behavior and is independent of conventional risk factors.