The triglyceride-glucose index is superior to homeostasis model assessment of insulin resistance in predicting metabolic syndrome in an adult population in the United States.

BACKGROUND: Metabolic Syndrome (MetS) is a cluster of cardio-metabolic features portending an increased risk for both type 2 diabetes mellitus (T2DM) and premature atherosclerotic cardiovascular disease (ASCVD). Homeostasis Model Assessment of Insulin Resistance (HOMA-IR) is a widely used surrogate measure of insulin resistance. The triglyceride-glucose (TyG) index is another validated measure of insulin resistance that predicts both diabetes and cardiovascular disease in low and medium-income countries, but only diabetes in high income countries. OBJECTIVE: Due to the paucity of data on the TyG index in the US population, we compared the validity of the TyG index and HOMA-IR in predicting MetS. METHODS: Data from the National Health and Nutrition Examination Survey (NHANES) between 2005 and 2018 on Non-Hispanic White(NHW), Hispanic American(HA), and African American(AA) individuals(n = 5380) aged 20-80 years were used for analysis. Individuals were classified as having MetS based on three or more of its components. HOMA-IR and the TyG index were determined from fasting samples. RESULTS: Both the TyG index and HOMA-IR were significantly increased in MetS and increased significantly with increasing severity of the syndrome. Also both indices correlated significantly with all 5 features of MetS, hsCRP and non-HDL-C. ROC-AUC analysis for TyG index was significantly greater than that of HOMA-IR in predicting MetS: 0.87(95 % CI 0.85-0.88) versus 0.82(95 % CI 0.81-0.83) respectively, p < 0.0001. This was not evident for the small AA subgroup. CONCLUSION: The TyG index outperformed HOMA-IR in predicting MetS, a proxy for both T2DM and ASCVD, in a general US population and is a valuable biomarker.

An improved method for estimating low LDL-C based on the enhanced Sampson-NIH equation.

BACKGROUND: The accurate measurement of Low-density lipoprotein cholesterol (LDL-C) is critical in the decision to utilize the new lipid-lowering therapies like PCSK9-inhibitors (PCSK9i) for high-risk cardiovascular disease patients that do not achieve sufficiently low LDL-C on statin therapy. OBJECTIVE: To improve the estimation of low LDL-C by developing a new equation that includes apolipoprotein B (apoB) as an independent variable, along with the standard lipid panel test results. METHODS: Using ß-quantification (BQ) as the reference method, which was performed on a large dyslipidemic population (N = 24,406), the following enhanced Sampson-NIH equation (eS LDL-C) was developed by least-square regression analysis: [Formula: see text] RESULTS: The eS LDL-C equation was the most accurate equation for a broad range of LDL-C values based on regression related parameters and the mean absolute difference (mg/dL) from the BQ reference method (eS LDL-C: 4.51, Sampson-NIH equation [S LDL-C]: 6.07; extended Martin equation [eM LDL-C]: 6.64; Friedewald equation [F LDL-C]: 8.3). It also had the best area-under-the-curve accuracy score by Regression Error Characteristic plots for LDL-C < 100 mg/dL (eS LDL-C: 0.953; S LDL-C: 0.920; eM LDL-C: 0.915; F LDL-C: 0.874) and was the best equation for categorizing patients as being below or above the 70 mg/dL LDL-C treatment threshold for adding new lipid-lowering drugs by kappa score analysis when compared to BQ LDL-C for TG < 800 mg/dL (eS LDL-C: 0.870 (0.853-0.887); S LDL-C:0.763 (0.749-0.776); eM LDL-C:0.706 (0.690-0.722); F LDL-C:0.687 (0.672-0.701). Approximately a third of patients with an F LDL-C < 70 mg/dL had falsely low test results, but about 80% were correctly reclassified as higher (≥ 70 mg/dL) by the eS LDL-C equation, making them potentially eligible for PCSK9i treatment. The M LDL-C and S LDL-C equations had less false low results below 70 mg/dL than the F LDL-C equation but reclassification by the eS LDL-C equation still also increased the net number of patients correctly classified. CONCLUSIONS: The use of the eS LDL-C equation as a confirmatory test improves the identification of high-risk cardiovascular disease patients, who could benefit from new lipid-lowering therapies but have falsely low LDL-C, as determined by the standard LDL-C equations used in current practice.

A High-Throughput NMR Method for Lipoprotein-X Quantification.

Lipoprotein X (LP-X) is an abnormal cholesterol-rich lipoprotein particle that accumulates in patients with cholestatic liver disease and familial lecithin-cholesterol acyltransferase deficiency (FLD). Because there are no high-throughput diagnostic tests for its detection, a proton nuclear magnetic resonance (NMR) spectroscopy-based method was developed for use on a clinical NMR analyzer commonly used for the quantification of lipoproteins and other cardiovascular biomarkers. The LP-X assay was linear from 89 to 1615 mg/dL (cholesterol units) and had a functional sensitivity of 44 mg/dL. The intra-assay coefficient of variation (CV) varied between 1.8 and 11.8%, depending on the value of LP-X, whereas the inter-assay CV varied between 1.5 and 15.4%. The assay showed no interference with bilirubin levels up to 317 mg/dL and was also unaffected by hemolysis for hemoglobin values up to 216 mg/dL. Samples were stable when stored for up to 6 days at 4 °C but were not stable when frozen. In a large general population cohort (n = 277,000), LP-X was detected in only 50 subjects. The majority of LP-X positive cases had liver disease (64%), and in seven cases, had genetic FLD (14%). In summary, we describe a new NMR-based assay for LP-X, which can be readily implemented for routine clinical laboratory testing.

Optimization of time interval for the measurement of plasma lipids for cardiovascular disease risk assessment.

BACKGROUND: Lipid testing for atherosclerotic cardiovascular disease (ASCVD) risk is often performed every 4-6 years, but we hypothesized that the optimum time interval may vary depending on baseline risk. RESEARCH DESIGN AND METHODS: Using lipid values and other risk factors from the National Health and Nutrition Examination Survey (NHANES) (n = 9,704), we calculated a 10-year risk score with the pooled-cohort equations. Future risk scores were predicted by increasing age and projecting systolic blood pressure (SBP) and lipid changes, using the mean-percentile age group change in NHANES for SBP (n = 17,329) and the Lifelines Cohort study for lipids (n = 133,540). The crossing of high and intermediate-risk thresholds were calculated by time to determine optimum intervals for lipid testing. RESULTS: Time to crossing risk thresholds depends on baseline risk, but the mean increase in the risk score plateaus at 1% per year for those with a baseline 10-year risk greater than 15%. Based on these findings, we recommend the following maximum time intervals for lipid testing: baseline risk < 15%: 5-years, 16%: 4-years, 17%: 3-years, 18%: 2-years, and 19%: ≤1-year. CONCLUSIONS: Testing patients for lipids who have a higher baseline risk more often could identify high-risk patients sooner, allowing for earlier and more effective therapeutic intervention.

Performance of the enhanced Sampson-NIH equation for VLDL-C and LDL-C in a population with familial combined hyperlipidemia.

INTRODUCTION: Low-density cholesterol (LDL-C) has long been estimated by the Friedewald formula (F-LDL-C); however, this method underestimates LDL-C in patients with hypertriglyceridemia (HTG) or low LDL-C levels. The Martin (M-LDL-C) and Sampson (S-LDL-C) formulas partially resolve these limitations. Recently, Sampson et al. developed a new equation (eS-VLDL-C) that includes ApoB. This new equation could be particularly useful in FCHL, which is characterized by the predominance of triglyceride-rich VLDL and a discordance between LDL-C and ApoB. METHODS: Very low-density lipoproteins (VLDL-C) was measured in 336 patients with FCHL by sequential ultracentrifugation. LDL-C was estimated by subtracting VLDL-C, estimated by the different equations, from non-HDL cholesterol. Spearman correlations, R2, mean squared error (RMSE), and bias were used to compare the accuracy of the different equations. Concordance of the estimated LDL-C values with LDL-C thresholds and ApoB was also assessed by their kappa coefficients and ROC analysis. RESULTS: Overall population had a mean age of 47 years, and 61.5% were women. 19.5% had type 2 diabetes, hypertension was present in 20.8%, and only 12.2% were on statin treatment. Both S-LDL-C and eS-LDL-C performed similarly, and better than M-LDL-C and F-LDL-C. In Bland-Altman analysis, eS-LDL-C showed the lowest bias, better performance in HTG, and better concordance with LDL-C treatment goals compared to other formulas (e.g. ρ: 0.87, 95% CI 0.84-0.89). CONCLUSIONS: LDL-S and LDL-eS equations estimate the concentration of LDL-C with greater accuracy than other formulas. The LDL-eS has best performance in estimating LDL-C with lower RMSE than other formulas.

Use of Apolipoprotein B in the Era of Precision Medicine: Time for a Paradigm Change?

Atherosclerotic cardiovascular disease (ASCVD) remains the leading cause of death worldwide and the risk of a major cardiovascular event is highest among those with established disease. Ongoing management of these patients relies on the accurate assessment of their response to any prescribed therapy, and their residual risk, in order to optimize treatment. Recent international guidelines and position statements concur that the plasma concentration of apolipoprotein B (apoB) is the most accurate measure of lipoprotein associated ASCVD risk. This is especially true for the growing number of individuals with diabetes, obesity, or the metabolic syndrome, and those on statin therapy. Most guidelines, however, continue to promote LDL-C as the primary risk marker due to uncertainty as to whether the greater accuracy of apoB is sufficient to warrant a paradigm shift. Recommendations regarding apoB measurement vary, and the information provided on how to interpret apoB results is sometimes insufficient, particularly for non-lipid specialists. Misinformation regarding the reliability of the assays is also frequently repeated despite its equivalent or better standardization than many other diagnostic assays. Thus, demand for apoB testing is relatively low, which means there is little incentive to increase its availability or reduce its cost. In this review, we examine the results of recent clinical outcomes studies and meta-analyses on the relative values of apoB, LDL-C, and non-HDL-C as markers of ASCVD risk. Although there is seemingly minimal difference among these markers when only population-based metrics are considered, it is evident from our analysis that, from a personalized or precision medicine standpoint, many individuals would benefit, at a negligible total cost, if apoB measurement were better integrated into the diagnosis and treatment of ASCVD.

HDL abnormalities in type 2 diabetes: Clinical implications.

Atherosclerotic cardiovascular disease (ASCVD) represents the primary cause of mortality among patients with Type 2 Diabetes Mellitus (T2DM). In this population, High-Density Lipoprotein (HDL) particles exhibit abnormalities in number, composition, and function, culminating in diminished anti-atherosclerotic capabilities despite normal HDL cholesterol (HDL-C) concentrations. Hyperglycemic conditions contribute to these alterations in HDL kinetics, composition, and function, causing T2DM patients' HDL particles to exhibit decreased concentrations of diverse lipid species and proteins. Treatment of hyperglycemia has the potential to correct abnormal HDL particle attributes in T2DM; however, pharmacological interventions, including metformin and thiazolidinediones, yield inconsistent outcomes with respect to HDL-C concentrations and functionality. Despite numerous attempts with diverse drugs, pharmacologically augmenting HDL-C levels has not resulted in clinical benefits in mitigating ASCVD risk. In contrast, reducing Low Density Lipoprotein cholesterol (LDL-C) via statins and ezetimibe has demonstrated significant efficacy in curtailing CVD risk among T2DM individuals. Promising results have been observed in animal models and early-phase trials utilizing recombinant HDL and Lecitin Cholesterol Acyl Transferase (LCAT) -enhancing agents, but the evaluation of their efficacy and safety in large-scale clinical trials is ongoing. While aberrant HDL metabolism constitutes a prevalent aspect of dyslipidemia in T2DM, HDL cholesterol concentrations and composition no longer offer valuable insights for informing therapeutic decisions. Nevertheless, HDL metabolism remains a critical research area in T2DM, necessitating further investigation to elucidate the role of HDL particles in the development of diabetes-associated complications.

Approach to the Patient With a Suboptimal Statin Response: Causes and Algorithm for Clinical Management.

CONTEXT: Statins are the lipid-lowering therapy of choice for the prevention of atherosclerotic cardiovascular disease (ASCVD) but their effectiveness in lowering low-density lipoprotein cholesterol (LDL-C) can substantially differ between individuals. In this mini-review, we describe the different causes for a suboptimal statin response and an algorithm for the diagnosis and clinical management of these patients. EVIDENCE ACQUISITION: A PubMed search using the terms "statin resistance," "statin sensitivity," "statin pharmacokinetics," "cardiovascular disease," and "lipid-lowering therapies" was performed. Published papers in the past 10 years that were relevant to the topic were examined to provide content for this mini-review. EVIDENCE SYNTHESIS: Suboptimal lowering of LDL-C by statins is a major problem in the clinical management of patients and limits the value of this therapeutic approach. There are multiple causes of statin hyporesponsiveness with compliance being the most common explanation. Other causes, such as analytical issues with LDL-C measurement and the presence of common lipid disorders (familial hypercholesterolemia, elevated lipoprotein[a] and secondary dyslipidemias) should be excluded before considering primary statin resistance from rare genetic variants in lipoprotein-related or drug-metabolism genes. A wide variety of nonstatin lipid-lowering drugs are now available and can be added to statins to achieve more effective LDL-C lowering. CONCLUSIONS: The evaluation of statin hyporesponsiveness is a multistep process that can lead to the optimization of lipid-lowering therapy for the prevention of ASCVD. It may also lead to the identification of distinct types of dyslipidemias that require specific therapies and/or the genetic screening of family members.

Accuracy and Clinical Impact of Estimating Low-Density Lipoprotein-Cholesterol at High and Low Levels by Different Equations.

New more effective lipid-lowering therapies have made it important to accurately determine Low-density lipoprotein-cholesterol (LDL-C) at both high and low levels. LDL-C was measured by the ß-quantification reference method (BQ) (N = 40,346) and compared to Friedewald (F-LDL-C), Martin (M-LDL-C), extended Martin (eM-LDL-C) and Sampson (S-LDL-C) equations by regression analysis, error-grid analysis, and concordance with the BQ method for classification into different LDL-C treatment intervals. For triglycerides (TG) < 175 mg/dL, the four LDL-C equations yielded similarly accurate results, but for TG between 175 and 800 mg/dL, the S-LDL-C equation when compared to the BQ method had a lower mean absolute difference (mg/dL) (MAD = 10.66) than F-LDL-C (MAD = 13.09), M-LDL-C (MAD = 13.16) or eM-LDL-C (MAD = 12.70) equations. By error-grid analysis, the S-LDL-C equation for TG > 400 mg/dL not only had the least analytical errors but also the lowest frequency of clinically relevant errors at the low (<70 mg/dL) and high (>190 mg/dL) LDL-C cut-points (S-LDL-C: 13.5%, F-LDL-C: 23.0%, M-LDL-C: 20.5%) and eM-LDL-C: 20.0%) equations. The S-LDL-C equation also had the best overall concordance to the BQ reference method for classifying patients into different LDL-C treatment intervals. The S-LDL-C equation is both more analytically accurate than alternative equations and results in less clinically relevant errors at high and low LDL-C levels.

Identification of a threshold to discriminate fasting hypertriglyceridemia with postprandial values.

BACKGROUND: Postprandial lipemia is an important cardiovascular risk factor. The assessment of postprandial lipid metabolism is a newly trend that several consortiums and countries have adopted. The aim of the study is to determine a postprandial triglyceride concentration cut-off point that accurately discriminate individuals with fasting normal triglyceride concentrations from those with fasting hypertriglyceridemia. METHODS: Cross sectional population-based study. A total of 212 subjects underwent an eight hours' oral fat tolerance test. Samples were taken fasting, three, four, five, six and eight hours after the meal. The area under the receiver operating characteristic curve (c-statistic) was computed using postprandial triglycerides concentrations as independent predictor, and fasting hypertriglyceridemia as dependent variable. RESULTS: The best threshold of postprandial lipemia to discriminate fasting hypertriglyceridemia was 280 mg/dL at any hour area under the curve 0.816 (95% confidence interval 0.753-0.866), bootstrap-corrected c-statistic = 0.733 (95% confidence interval 0.68-0.86). The same value was compared with apolipoprotein B concentrations (>90th percentile) having a good performance: area under the curve 0.687 95% confidence interval 0.624-0.751). Likewise, subjects with high postprandial lipemia have higher Globo risk scores. CONCLUSION: The 280 mg/dL cut-off point value of postprandial triglycerides concentration any time after a test meal discriminate subjects with fasting hypertriglyceridemia. This threshold has a good performance in a heterogeneous population and has a good concordance with cardiovascular risk surrogates.

The panorama of familial hypercholesterolemia in Latin America: a systematic review.

The burden caused by familial hypercholesterolemia (FH) varies among countries and ethnic groups. The prevalence and characteristics of FH in Latin American (LA) countries is largely unknown. We present a systematic review (following the PRISMA statement) of FH in LA countries. The epidemiology, genetics, screening, management, and unique challenges encountered in these countries are discussed. Published reports discussing FH in Hispanic or LA groups was considered for analysis. Thirty studies were included representing 10 countries. The bulk of the data was generated in Brazil and Mexico. Few countries have registries and there was little commonality in FH mutations between LA countries. LDL receptor mutations predominate; APOB and PCSK9 mutations are rare. No mutation was found in an FH gene in nearly 50% of cases. In addition, some country-specific mutations have been reported. Scant information exists regarding models of care, cascade screening, cost, treatment effectiveness, morbidity, and mortality. In conclusion, FH is largely underdiagnosed and undertreated in the LA region. The genetic admixture with indigenous populations, producing mestizo's groups, may influence the mutational findings in Latin America. Potential opportunities to close gaps in knowledge and health care are identified.