Clinical validation of the PrecivityAD2 blood test: A mass spectrometry-based test with algorithm combining %p-tau217 and Aß42/40 ratio to identify presence of brain amyloid.

BACKGROUND: With the availability of disease-modifying therapies for Alzheimer's disease (AD), it is important for clinicians to have tests to aid in AD diagnosis, especially when the presence of amyloid pathology is a criterion for receiving treatment. METHODS: High-throughput, mass spectrometry-based assays were used to measure %p-tau217 and amyloid beta (Aß)42/40 ratio in blood samples from 583 individuals with suspected AD (53% positron emission tomography [PET] positive by Centiloid > 25). An algorithm (PrecivityAD2 test) was developed using these plasma biomarkers to identify brain amyloidosis by PET. RESULTS: The area under the receiver operating characteristic curve (AUC-ROC) for %p-tau217 (0.94) was statistically significantly higher than that for p-tau217 concentration (0.91). The AUC-ROC for the PrecivityAD2 test output, the Amyloid Probability Score 2, was 0.94, yielding 88% agreement with amyloid PET. Diagnostic performance of the APS2 was similar by ethnicity, sex, age, and apoE4 status. DISCUSSION: The PrecivityAD2 blood test showed strong clinical validity, with excellent agreement with brain amyloidosis by PET.

Standardization of Apolipoprotein B, LDL-Cholesterol, and Non-HDL-Cholesterol.

Concern continues about whether the measurement of apolipoprotein B (apoB) is adequately standardized, and therefore, whether apoB should be applied widely in clinical care. This concern is misplaced. Our objective is to explain why and what the term "standardization" means. To produce clinically valid results, a test must accurately, precisely, and selectively measure the marker of interest. That is, it must be standardized. Accuracy refers to how closely the result obtained with 1 method corresponds to the result obtained with the standard method, precision to how reproducible the result is on repeated testing, and selectivity to how susceptible the method is to error by inclusion of other classes of lipoprotein particles. Multiple expert groups have determined that the measurement of apoB is adequately standardized for clinical care, and that apoB can be measured inexpensively, using widely available automated methods, more accurately, precisely, and selectively than low-density lipoprotein cholesterol or non-high-density lipoprotein cholesterol. ApoB is a standard superior to low-density lipoprotein cholesterol and high-density lipoprotein cholesterol because it is a defined molecule, whereas the cholesterol markers are the mass of cholesterol within lipoprotein particles defined by their density, not by their molecular structure. Nevertheless, the standardization of apoB is being further improved by the application of mass spectrophotometric methods, whereas the limitations in the standardization and, therefore, the accurate, precise, and selective measurement of low-density lipoprotein cholesterol and high-density lipoprotein cholesterol are unlikely to be overcome. We submit that greater accuracy, precision, and selectivity in measurement is a decisive advantage for apoB in the modern era of intensive lipid-lowering therapies.

Independent study demonstrates amyloid probability score accurately indicates amyloid pathology.

BACKGROUND: The amyloid probability score (APS) is the model read-out of the analytically validated mass spectrometry-based PrecivityAD® blood test that incorporates the plasma Aß42/40 ratio, ApoE proteotype, and age to identify the likelihood of brain amyloid plaques among cognitively impaired individuals being evaluated for Alzheimer's disease. PURPOSE: This study aimed to provide additional independent evidence that the pre-established APS algorithm, along with its cutoff values, discriminates between amyloid positive and negative individuals. METHODS: The diagnostic performance of the PrecivityAD test was analyzed in a cohort of 200 nonrandomly selected Australian Imaging, Biomarker & Lifestyle Flagship Study of Aging (AIBL) study participants, who were either cognitively impaired or healthy controls, and for whom a blood sample and amyloid PET imaging were available. RESULTS: In a subset of the dataset aligned with the Intended Use population (patients aged 60 and older with CDR ≥0.5), the pre-established APS algorithm predicted amyloid PET with a sensitivity of 84.9% (CI: 72.9-92.1%) and specificity of 96% (CI: 80.5-99.3%), exclusive of 13 individuals for whom the test was inconclusive. INTERPRETATION: The study shows individuals with a high APS are more likely than those with a low APS to have abnormal amounts of amyloid plaques and be on an amyloid accumulation trajectory, a dynamic and evolving process characteristic of progressive AD pathology. Exploratory data suggest APS retains its diagnostic performance in healthy individuals, supporting further screening studies in the cognitively unimpaired.

Assessment of a Plasma Amyloid Probability Score to Estimate Amyloid Positron Emission Tomography Findings Among Adults With Cognitive Impairment.

Importance: The diagnostic evaluation for Alzheimer disease may be improved by a blood-based diagnostic test identifying presence of brain amyloid plaque pathology. Objective: To determine the clinical performance associated with a diagnostic algorithm incorporating plasma amyloid-ß (Aß) 42:40 ratio, patient age, and apoE proteotype to identify brain amyloid status. Design, Setting, and Participants: This cohort study includes analysis from 2 independent cross-sectional cohort studies: the discovery cohort of the Plasma Test for Amyloidosis Risk Screening (PARIS) study, a prospective add-on to the Imaging Dementia-Evidence for Amyloid Scanning study, including 249 patients from 2018 to 2019, and MissionAD, a dataset of 437 biobanked patient samples obtained at screenings during 2016 to 2019. Data were analyzed from May to November 2020. Exposures: Amyloid detected in blood and by positron emission tomography (PET) imaging. Main Outcomes and Measures: The main outcome was the diagnostic performance of plasma Aß42:40 ratio, together with apoE proteotype and age, for identifying amyloid PET status, assessed by accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC). Results: All 686 participants (mean [SD] age 73.2 [6.3] years; 368 [53.6%] men; 378 participants [55.1%] with amyloid PET findings) had symptoms of mild cognitive impairment or mild dementia. The AUC of plasma Aß42:40 ratio for PARIS was 0.79 (95% CI, 0.73-0.85) and 0.86 (95% CI, 0.82-0.89) for MissionAD. Ratio cutoffs for Aß42:40 based on the Youden index were similar between cohorts (PARIS: 0.089; MissionAD: 0.092). A logistic regression model (LRM) incorporating Aß42:40 ratio, apoE proteotype, and age improved diagnostic performance within each cohort (PARIS: AUC, 0.86 [95% CI, 0.81-0.91]; MissionAD: AUC, 0.89 [95% CI, 0.86-0.92]), and overall accuracy was 78% (95% CI, 72%-83%) for PARIS and 83% (95% CI, 79%-86%) for MissionAD. The model developed on the prospectively collected samples from PARIS performed well on the MissionAD samples (AUC, 0.88 [95% CI, 0.84-0.91]; accuracy, 78% [95% CI, 74%-82%]). Training the LRM on combined cohorts yielded an AUC of 0.88 (95% CI, 0.85-0.91) and accuracy of 81% (95% CI, 78%-84%). The output of this LRM is the Amyloid Probability Score (APS). For clinical use, 2 APS cutoff values were established yielding 3 categories, with low, intermediate, and high likelihood of brain amyloid plaque pathology. Conclusions and Relevance: These findings suggest that this blood biomarker test could allow for distinguishing individuals with brain amyloid-positive PET findings from individuals with amyloid-negative PET findings and serve as an aid for Alzheimer disease diagnosis.

The PrecivityAD™ test: Accurate and reliable LC-MS/MS assays for quantifying plasma amyloid beta 40 and 42 and apolipoprotein E proteotype for the assessment of brain amyloidosis.

BACKGROUND: There is an unmet need for an accessible, less invasive, cost-effective method to facilitate clinical trial enrollment and aid in clinical Alzheimer's disease (AD) diagnosis. APOE genotype affects the clearance and deposition of amyloid-beta (Aß) with APOE4 carriers having increased risk while APOE2 alleles appear to be protective. Lower plasma Aß42/40 correlates with brain amyloidosis. In response, C2N has developed the PrecivityAD™ test; plasma LC-MS/MS assays for Aß isoform quantitation and qualitative APOE isoform-specific proteotyping. METHODS: In accord with CLIA standards, we developed and validated assay performance: precision, accuracy, linearity, limit of detection (LoD), interferences. RESULTS: Within-day precision varied from 1.5-3.0% (Aß40) and 2.5-8.4% (Aß42). Total (within-lab) variability was 2.7-7.7% (Aß40) and 3.1-9.5% (Aß42). Aß40 quantitation was linear from 10 to 1780 pg/mL; Aß42 was linear from 2 to 254 pg/mL. LoD was 11 and 2 pg/mL for Aß40 and Aß42, respectively. APOE proteotypes were 100% concordant with genotype, while LoD (fM) was much lower than APOE concentrations observed in plasma (mM). CONCLUSIONS: The PrecivityAD™ assays are precise, accurate, sensitive, and linear over a wide analytical range, free from significant interferences, and suitable for use in the clinical laboratory.

A blood-based diagnostic test incorporating plasma Aß42/40 ratio, ApoE proteotype, and age accurately identifies brain amyloid status: findings from a multi cohort validity analysis.

BACKGROUND: The development of blood-based biomarker tests that are accurate and robust for Alzheimer's disease (AD) pathology have the potential to aid clinical diagnosis and facilitate enrollment in AD drug trials. We developed a high-resolution mass spectrometry (MS)-based test that quantifies plasma Aß42 and Aß40 concentrations and identifies the ApoE proteotype. We evaluated robustness, clinical performance, and commercial viability of this MS biomarker assay for distinguishing brain amyloid status. METHODS: We used the novel MS assay to analyze 414 plasma samples that were collected, processed, and stored using site-specific protocols, from six independent US cohorts. We used receiver operating characteristic curve (ROC) analyses to assess assay performance and accuracy for predicting amyloid status (positive, negative, and standard uptake value ratio; SUVR). After plasma analysis, sites shared brain amyloid status, defined using diverse, site-specific methods and cutoff values; amyloid PET imaging using various tracers or CSF Aß42/40 ratio. RESULTS: Plasma Aß42/40 ratio was significantly (p < 0.001) lower in the amyloid positive vs. negative participants in each cohort. The area under the ROC curve (AUC-ROC) was 0.81 (95% CI = 0.77-0.85) and the percent agreement between plasma Aß42/40 and amyloid positivity was 75% at the optimal (Youden index) cutoff value. The AUC-ROC (0.86; 95% CI = 0.82-0.90) and accuracy (81%) for the plasma Aß42/40 ratio improved after controlling for cohort heterogeneity. The AUC-ROC (0.90; 95% CI = 0.87-0.93) and accuracy (86%) improved further when Aß42/40, ApoE4 copy number and participant age were included in the model. CONCLUSIONS: This mass spectrometry-based plasma biomarker test: has strong diagnostic performance; can accurately distinguish brain amyloid positive from amyloid negative individuals; may aid in the diagnostic evaluation process for Alzheimer's disease; and may enhance the efficiency of enrolling participants into Alzheimer's disease drug trials.

Lipoprotein(a) particle number assay without error from apolipoprotein(a) size isoforms.

BACKGROUND: Lipoprotein(a) [Lp(a)] is an important cardiovascular risk factor, but clinical immunoassays are flawed. Apolipoprotein(a) [apo(a)], the characteristic protein of Lp(a), contains a variable number of kringle repeats (size isoforms) that make accurate measurement of Lp(a) difficult. We developed a sandwich enzyme immunoassay that uses a murine monoclonal anti-apo(a) antibody for capture and a polyclonal anti-apolipoprotein B (apo B) for detection. Because Lp(a) contains one molecule each of apo(a) and apo B, the assay measures the number of Lp(a) particles [Lp(a)-P] in the circulation without bias due to apo(a) size isoforms. METHODS: After developing and choosing the best anti-apo(a) clone for Lp(a) capture, we identified suitable reagents and ELISA conditions, and validated assay performance (precision, linearity, limit of detection, interferences, and apo(a) size isoform bias). RESULTS: The Lp(a)-P assay was precise with within-run precision of 5.5% to 7.2% and total imprecision of 6.9% to 12.1%. The assay had a limit of detection of 13 nmol/l and was linear from 2 to 499 nmol/l. There was no interference from plasminogen or apolipoprotein B up to 80 and 200 mg/dl, respectively, and bias plot showed no bias related to apo(a) size (kringle 4 type 2 repeats). CONCLUSIONS: Lp(a)-P assay is sensitive, precise and linear over a wide analytical range and is a suitable alternative for laboratories concerned about inaccuracy due to apo(a) size polymorphism and the poor performance of immunoturbidimetric assays.

Comparability of Lipoprotein Particle Number Concentrations Across ES-DMA, NMR, LC-MS/MS, Immunonephelometry, and VAP: In Search of a Candidate Reference Measurement Procedure for apoB and non-HDL-P Standardization.

BACKGROUND: Despite the usefulness of standard lipid parameters for cardiovascular disease risk assessment, undiagnosed residual risk remains high. Advanced lipoprotein testing (ALT) was developed to provide physicians with more predictive diagnostic tools. ALT methods separate and/or measure lipoproteins according to different parameters such as size, density, charge, or content, and equivalence of results across methods has not been demonstrated. METHODS: Through a split-sample study, 25 clinical specimens (CSs) were assayed in 10 laboratories before and after freezing using the major ALT methods for non-HDL particles (non-HDL-P) or apolipoprotein B-100 (apoB-100) measurements with the intent to assess their comparability in the current state of the art. RESULTS: The overall relative standard deviation (CV) of non-HDL-P and apoB-100 concentrations measured by electrospray differential mobility analysis, nuclear magnetic resonance, immunonephelometry, LC-MS/MS, and vertical autoprofile in the 25 frozen CSs was 14.1%. Within-method comparability was heterogeneous, and CV among 4 different LC-MS/MS methods was 11.4% for apoB-100. No significant effect of freezing and thawing was observed. CONCLUSIONS: This study demonstrates that ALT methods do not yet provide equivalent results for the measurement of non-HDL-P and apoB-100. The better agreement between methods harmonized to the WHO/IFCC reference material suggests that standardizing ALT methods by use of a common commutable calibrator will improve cross-platform comparability. This study provides further evidence that LC-MS/MS is the most suitable candidate reference measurement procedure to standardize apoB-100 measurement, as it would provide results with SI traceability. The absence of freezing and thawing effect suggests that frozen serum pools could be used as secondary reference materials.

Discordance analysis and the Gordian Knot of LDL and non-HDL cholesterol versus apoB.

PURPOSE OF REVIEW: Conventional methods, comparing the concentration of cholesterol to particle number as indices of cardiovascular risk, have not produced consistent results, in large part, because they treat these variables as independent and unrelated. However, although highly correlated, apolipoprotein B particles may contain a normal mass of cholesterol or may be cholesterol-depleted or cholesterol-enriched. Discordance analysis compares the predictive power of LDL-C and non-HDL-C to apolipoprotein B and LDL particle numbers in patients in whom they differ, that is, in whom they are discordant. The advantage of discordance analysis is that the results are not diluted by concordant data in which risk predictions cannot differ. RECENT FINDINGS: The evidence, to date, consistently demonstrates that apolipoprotein B and LDL particle numbers are more accurate indices of cardiovascular risk than LDL-C or non-HDL-C. SUMMARY: Discordance analysis is a methodological advance that allows the clinical value of closely correlated variables to be determined and demonstrates that cardiovascular risk is more closely related to the number of atherogenic particles than to the total mass of cholesterol within them.

Immunoprecipitation of apolipoprotein B-containing lipoproteins for isolation of HDL particles.

BACKGROUND: Immunoprecipitation (IP) of non-HDL particles with antisera provides the simplest and most specific method available for the separation of HDL. We compared the LipoSep™ IP reagent with the dextran sulfate/MgCl2 precipitation method (DS). METHODS: The IP reagent (200 µl) was added to an equal volume of serum, vortexed, incubated for 10 min at room temperature, and microcentrifuged at 12,000 rpm for 10 min. RESULTS: Equal volumes of a sample and the IP reagent precipitated apoB to 3.0 g/l without the coprecipitation of HDL. HDL-C measured in the supernatant after IP (Y) gave excellent agreement to DS precipitation (X) with a slope of 1.01, an intercept of 0.070 mmol/l (2.7 mg/dl), and a correlation of 0.99 (n=118; apoB 0.16-2.11 g/l). However, DS failed in most samples with moderate to elevated triglycerides. At triglyceride concentrations from 2.86 to 23.63 mmol/l (253-2091 mg/dl) the initial success rate was 65.4% for IP, while DS successfully precipitated only 5.8%. Success rate on repeat with additional reagent and/or sample dilution gave a success rate of 86.5% for IP and 40.4% for DS. CONCLUSION: The IP reagent and protocol is a simple, effective and highly specific tool for isolating HDL particles in human serum and is effective with high triglyceride samples.

Association of apolipoprotein B and nuclear magnetic resonance spectroscopy-derived LDL particle number with outcomes in 25 clinical studies: assessment by the AACC Lipoprotein and Vascular Diseases Division Working Group on Best Practices.

BACKGROUND: The number of circulating LDL particles is a strong indicator of future cardiovascular disease (CVD) events, even superior to the concentration of LDL cholesterol. Atherogenic (primarily LDL) particle number is typically determined either directly by the serum concentration of apolipoprotein B (apo B) or indirectly by nuclear magnetic resonance (NMR) spectroscopy of serum to obtain NMR-derived LDL particle number (LDL-P). CONTENT: To assess the comparability of apo B and LDL-P, we reviewed 25 clinical studies containing 85 outcomes for which both biomarkers were determined. In 21 of 25 (84.0%) studies, both apo B and LDL-P were significant for at least 1 outcome. Neither was significant for any outcome in only 1 study (4.0%). In 50 of 85 comparisons (58.8%), both apo B and LDL-P had statistically significant associations with the clinical outcome, whereas in 17 comparisons (20.0%) neither was significantly associated with the outcome. In 18 comparisons (21.1%) there was discordance between apo B and LDL-P. CONCLUSIONS: In most studies, both apo B and LDL-P were comparable in association with clinical outcomes. The biomarkers were nearly equivalent in their ability to assess risk for CVD and both have consistently been shown to be stronger risk factors than LDL-C. We support the adoption of apo B and/or LDL-P as indicators of atherogenic particle numbers into CVD risk screening and treatment guidelines. Currently, in the opinion of this Working Group on Best Practices, apo B appears to be the preferable biomarker for guideline adoption because of its availability, scalability, standardization, and relatively low cost.

Reliability of low-density lipoprotein cholesterol, non-high-density lipoprotein cholesterol, and apolipoprotein B measurement.

There is little understanding of the reliability of laboratory measurements among clinicians. Low-density lipoprotein cholesterol (LDL-C) measurement is the cornerstone of cardiovascular risk assessment and prevention, but it is fraught with error. Therefore, we have reviewed issues related to accuracy and precision for the measurement of LDL-C and the related markers non-high-density lipoprotein cholesterol (non-HDL-C) and apolipoprotein B. Despite the widespread belief that LDL-C is standardized and reproducible, available data suggest that results can vary significantly as the result of methods from different manufacturers. Similar problems with direct HDL-C assays raise concerns about the reliability of non-HDL-C measurement. The root cause of method-specific bias relates to the ambiguity in the definition of both LDL and HDL, and the heterogeneity of LDL and HDL particle size and composition. Apolipoprotein B appears to provide a more reliable alternative, but assays for it have not been as rigorously tested as direct LDL-C and HDL-C assays.

A meta-analysis of low-density lipoprotein cholesterol, non-high-density lipoprotein cholesterol, and apolipoprotein B as markers of cardiovascular risk.

BACKGROUND: Whether apolipoprotein B (apoB) or non-high-density lipoprotein cholesterol (HDL-C) adds to the predictive power of low-density lipoprotein cholesterol (LDL-C) for cardiovascular risk remains controversial. METHODS AND RESULTS: This meta-analysis is based on all the published epidemiological studies that contained estimates of the relative risks of non-HDL-C and apoB of fatal or nonfatal ischemic cardiovascular events. Twelve independent reports, including 233 455 subjects and 22 950 events, were analyzed. All published risk estimates were converted to standardized relative risk ratios (RRRs) and analyzed by quantitative meta-analysis using a random-effects model. Whether analyzed individually or in head-to-head comparisons, apoB was the most potent marker of cardiovascular risk (RRR, 1.43; 95% CI, 1.35 to 1.51), LDL-C was the least (RRR, 1.25; 95% CI, 1.18 to 1.33), and non-HDL-C was intermediate (RRR, 1.34; 95% CI, 1.24 to 1.44). The overall comparisons of the within-study differences showed that apoB RRR was 5.7%>non-HDL-C (P<0.001) and 12.0%>LDL-C (P<0.0001) and that non-HDL-C RRR was 5.0%>LDL-C (P=0.017). Only HDL-C accounted for any substantial portion of the variance of the results among the studies. We calculated the number of clinical events prevented by a high-risk treatment regimen of all those >70th percentile of the US adult population using each of the 3 markers. Over a 10-year period, a non-HDL-C strategy would prevent 300 000 more events than an LDL-C strategy, whereas an apoB strategy would prevent 500 000 more events than a non-HDL-C strategy. CONCLUSIONS: These results further validate the value of apoB in clinical care.

Why is non-high-density lipoprotein cholesterol a better marker of the risk of vascular disease than low-density lipoprotein cholesterol?

Low-density lipoprotein cholesterol (LDL-C) has been the focus of managing lipoprotein disorders for decades. It is now time to consider a change. Both apolipoprotein B (apoB) and non-high-density lipoprotein cholesterol (HDL-C) have been shown to be more accurate markers of cardiovascular risk than LDL-C. ApoB measures total atherogenic particle number, of which 90% are LDL particles. Therefore, LDL particle number determines plasma apoB in most patients. Non-HDL-C is widely assumed to be superior to LDL-C when triglyceride concentrations are elevated (even modestly) because it includes the cholesterol in very-low-density lipoprotein. However, evidence does not support this concept. Rather, non-HDL-C appears to be an indirect way of estimating apoB. We argue that we should integrate the information from non-HDL-C and apoB for better risk assessment and a better target of therapy.

Apolipoprotein B and cardiovascular disease risk: position statement from the AACC Lipoproteins and Vascular Diseases Division Working Group on Best Practices.

BACKGROUND: Low-density lipoprotein cholesterol (LDL-C) has been the cornerstone measurement for assessing cardiovascular risk for nearly 20 years. CONTENT: Recent data demonstrate that apolipoprotein B (apo B) is a better measure of circulating LDL particle number (LDL-P) concentration and is a more reliable indicator of risk than LDL-C, and there is growing support for the idea that addition of apo B measurement to the routine lipid panel for assessing and monitoring patients at risk for cardiovascular disease (CVD) would enhance patient management. In this report, we review the studies of apo B and LDL-P reported to date, discuss potential advantages of their measurement over that of LDL-C, and present information related to standardization. CONCLUSIONS: In line with recently adopted Canadian guidelines, the addition of apo B represents a logical next step to National Cholesterol Education Program Adult Treatment Panel III (NCEP ATPIII) and other guidelines in the US. Considering that it has taken years to educate physicians and patients regarding the use of LDL-C, changing perceptions and practices will not be easy. Thus, it appears prudent to consider using apo B along with LDL-C to assess LDL-related risk for an interim period until the superiority of apo B is generally recognized.

Carbohydrate restriction and dietary cholesterol distinctly affect plasma lipids and lipoprotein subfractions in adult guinea pigs.

To evaluate the effects of carbohydrate restriction (CR) and dietary cholesterol on lipoprotein metabolism, adult male guinea pigs (10 guinea pigs/diet) were fed either low (0.04 g/100 g) or high (0.25 g/100 g) amounts of dietary cholesterol, in combination with either low (10% total energy) or high (54.2% total energy) dietary carbohydrate (control groups) for a total of four groups: high carbohydrate-low cholesterol (control-L), high carbohydrate-high cholesterol (control-H), low carbohydrate-low cholesterol (CR-L) and low carbohydrate-high cholesterol (CR-H). Plasma triglyceride concentrations were lower (P<.01%), while high-density lipoprotein cholesterol concentrations were higher (P<.05) in the CR groups compared to the control groups. In contrast, high dietary cholesterol (CR-H and control-H) resulted in higher concentrations of total and low-density lipoprotein (LDL) cholesterol compared to those guinea pigs fed the low-cholesterol diets (P<.01). Dietary cholesterol significantly increased the total number of LDL particles (P<.001) and the number of small LDL (P<.001), as determined by nuclear magnetic resonance. In contrast, carbohydrate restriction (CR-L and CR-H) resulted in lower concentrations of medium very-low-density lipoprotein and small LDL particles compared to the high-carbohydrate groups. Plasma lecithin:cholesterol acyltransferase (LCAT) activity was decreased and cholesterol ester transfer protein activity was increased by dietary cholesterol, whereas carbohydrate restriction increased LCAT activity (P<.05). These findings are similar to those observed in humans, thus validating the use of adult guinea pigs to study lipid responses to carbohydrate restriction. The results also indicate that the atherogenicity of lipoproteins induced by high dietary cholesterol is attenuated by carbohydrate restriction in guinea pigs.

Clinical utility of different lipid measures for prediction of coronary heart disease in men and women.

CONTEXT: Evidence is conflicting regarding the performance of apolipoproteins vs traditional lipids for predicting coronary heart disease (CHD) risk. OBJECTIVES: To compare performance of different lipid measures for CHD prediction using discrimination and calibration characteristics and reclassification of risk categories; to assess incremental utility of apolipoproteins over traditional lipids for CHD prediction. DESIGN, SETTING, AND PARTICIPANTS: Population-based, prospective cohort from, Framingham, Massachusetts. We evaluated serum total cholesterol, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), non-HDL-C, apolipoprotein (apo) A-I and apo B, and 3 lipid ratios (total cholesterol:HDL-C, LDL-C:HDL-C, and apo B:apo A-I) in 3322 middle-aged white participants who attended the fourth offspring examination cycle (1987-1991) and were without cardiovascular disease. Fifty-three percent of the participants were women. MAIN OUTCOME MEASURE: Incidence of first CHD event (recognized or unrecognized myocardial infarction, angina pectoris, coronary insufficiency, or coronary heart disease death). RESULTS: After a median follow-up of 15.0 years, 291 participants, 198 of whom were men, developed CHD. In multivariate models adjusting for nonlipid risk factors, the apo B:apo A-I ratio predicted CHD (hazard ratio [HR] per SD increment, 1.39; 95% confidence interval [CI], 1.23-1.58 in men and HR, 1.40; 95% CI, 1.16-1.67 in women), but risk ratios were similar for total cholesterol:HDL-C (HR, 1.39; 95% CI, 1.22-1.58 in men and HR, 1.39; 95% CI, 1.17-1.66 in women) and for LDL-C:HDL-C (HR, 1.35; 95% CI, 1.18-1.54 in men and HR, 1.36; 95% CI 1.14-1.63 in women). In both sexes, models using the apo B:apo A-I ratio demonstrated performance characteristics comparable with but not better than that for other lipid ratios. The apo B:apo A-I ratio did not predict CHD risk in a model containing all components of the Framingham risk score including total cholesterol:HDL-C (P = .12 in men; P = .58 in women). CONCLUSIONS: In this large, population-based cohort, the overall performance of apo B:apo A-I ratio for prediction of CHD was comparable with that of traditional lipid ratios but did not offer incremental utility over total cholesterol:HDL-C. These data do not support measurement of apo B or apo A-I in clinical practice when total cholesterol and HDL-C measurements are available.

Change in plasma lutein after egg consumption is positively associated with plasma cholesterol and lipoprotein size but negatively correlated with body size in postmenopausal women.

We investigated associations between plasma concentrations of cholesterol and lutein after consumption of eggs. Using a crossover design, 22 postmenopausal women (50-77 y) consumed an egg treatment (640 mg/d additional cholesterol and 600 mug/d additional lutein + zeaxanthin) or a baseline treatment (no additional cholesterol or lutein + zeaxanthin) for 30 d, followed by a 3-wk washout period and the alternate diet. The increases in plasma total cholesterol and lutein due to egg consumption were related (r = 0.48, P < 0.05). There was a positive correlation between LDL size (r = 0.45, P < 0.05), HDL size (r = 0.64, P < 0.01), and plasma lutein, but no relation with the number of LDL or HDL particles. The activities of cholesterol ester transfer protein and lecithin cholesterol acyltransferase, although important in the exchange of cholesterol among lipoproteins, were not associated with changes in plasma lutein. Plasma lutein concentrations observed during the baseline period were a strong predictor of the increase in plasma lutein after egg treatment (r = 0.50 P < 0.05). There was a negative association between the change in lutein due to egg consumption and BMI (r = -0.40, P < 0.06) and waist circumference (r = -0.49, P < 0.05). This was particularly evident in individuals with BMI >29. We conclude that the increase in plasma lutein after egg consumption is associated with the change in plasma total cholesterol, but that the effect is diminished by obesity. Lipoprotein size, but not number, also affects plasma response to dietary lutein.