Irina Shalaurova

Low-Density Lipoprotein and High-Density Lipoprotein Particle Subclasses Predict Coronary Events and Are Favorably Changed by Gemfibrozil Therapy in the Veterans Affairs High-Density Lipoprotein Intervention Trial

Background— Changes in conventional lipid risk factors with gemfibrozil treatment only partially explain the reductions in coronary heart disease (CHD) events experienced by men in the Veterans Affairs High-Density Lipoprotein Intervention Trial (VA-HIT). We examined whether measurement of low-density lipoprotein (LDL) and high-density lipoprotein (HDL) particle subclasses provides additional information relative to CHD risk reduction. Methods and Results— This is a prospective nested case-control study of 364 men with a new CHD event (nonfatal myocardial infarction or cardiac death) during a 5.1-year (median) follow-up and 697 age-matched controls. Nuclear magnetic resonance (NMR) spectroscopy was used to quantify levels of LDL and HDL particle subclasses and mean particle sizes in plasma obtained at baseline and after 7 months of treatment with gemfibrozil or placebo. Odds ratios for a 1-SD increment of each lipoprotein variable were calculated with adjusted logistic regression models. Gemfibrozil treatment increased LDL size and lowered numbers of LDL particles (−5%) while raising numbers of HDL particles (10%) and small HDL subclass particles (21%). Concentrations of these LDL and HDL particles achieved with gemfibrozil were significant, independent predictors of new CHD events. For total LDL and HDL particles, odds ratios predicting CHD benefit were 1.28 (95% CI, 1.12 to 1.47) and 0.71 (95% CI, 0.61 to 0.81), respectively. Mean LDL and HDL particle sizes were not associated with CHD events. Conclusions— The effects of gemfibrozil on NMR-measured LDL and HDL particle subclasses, which are not reflected by conventional lipoprotein cholesterol measures, help to explain the demonstrated benefit of this therapy in patients with low HDL cholesterol.

Clinical implications of discordance between low-density lipoprotein cholesterol and particle number

BACKGROUND The amount of cholesterol per low-density lipoprotein (LDL) particle is variable and related in part to particle size, with smaller particles carrying less cholesterol. This variability causes concentrations of LDL cholesterol (LDL-C) and LDL particles (LDL-P) to be discordant in many individuals. METHODS LDL-P measured by nuclear magnetic resonance spectroscopy, calculated LDL-C, and carotid intima-media thickness (IMT) were assessed at baseline in the Multi-Ethnic Study of Atherosclerosis, a community-based cohort of 6814 persons free of clinical cardiovascular disease (CVD) at entry and followed for CVD events (n = 319 during 5.5-year follow-up). Discordance, defined as values of LDL-P and LDL-C differing by ≥ 12 percentile units to give equal-sized concordant and discordant subgroups, was related to CVD events and to carotid IMT in models predicting outcomes for a 1 SD difference in LDL-C or LDL-P, adjusted for age, gender, and race. RESULTS LDL-C and LDL-P were associated with incident CVD overall: hazard ratios (HR 1.20, 95% CI [CI] 1.08-1.34; and 1.32, 95% CI 1.19-1.47, respectively, but for those with discordant levels, only LDL-P was associated with incident CVD (HR 1.45, 95% CI 1.19-1.78; LDL-C HR 1.07, 95% CI 0.88-1.30). IMT also tracked with LDL-P rather than LDL-C, ie, adjusted mean IMT of 958, 932, and 917 microm in the LDL-P > LDL-C discordant, concordant, and LDL-P < LDL-C discordant subgroups, respectively, with the difference persisting after adjustment for LDL-C (P = .002) but not LDL-P (P = .60). CONCLUSIONS For individuals with discordant LDL-C and LDL-P levels, the LDL-attributable atherosclerotic risk is better indicated by LDL-P.

Effects of pravastatin treatment on lipoprotein subclass profiles and particle size in the PLAC-I trial

Lipoprotein subclass analyses may facilitate coronary heart disease (CHD) risk stratification and provide insight into the cardioprotective benefits of statins (3-hydroxymethylglutaryl-coenzyme A reductase inhibitors). This study evaluated the influence of pravastatin on lipoprotein subclass profiles to determine whether subjects with predominantly large LDL (LDL size >20.5 nm) or small LDL (LDL size < or =20.5 nm) at baseline differ in responsiveness to drug treatment. Frozen plasma specimens were analyzed from a subset of participants in the Pravastatin Limitation of Atherosclerosis in the Coronaries (PLAC-I) trial at baseline and after treatment for 6 months with pravastatin (n=154) or placebo (n=138). Lipids were measured by standard chemical methods and lipoprotein subclasses by nuclear magnetic resonance (NMR) spectroscopy. Pravastatin-induced changes in lipid levels were similar in subjects with large or small LDL at baseline. Levels of the most abundant LDL subclass were preferentially lowered by pravastatin, resulting in an increase in average LDL size for those with a predominance of small LDL. High-risk CHD subjects with small LDL particles gain at least as much pharmacological benefit from pravastatin as those with large LDL, as evidenced by reductions in the numbers of total and small LDL particles, and increases in average LDL and HDL particle size.

GlycA: A Composite Nuclear Magnetic Resonance Biomarker of Systemic Inflammation

BACKGROUND Nuclear magnetic resonance (NMR) spectra of serum obtained under quantitative conditions for lipoprotein particle analyses contain additional signals that could potentially serve as useful clinical biomarkers. One of these signals that we named GlycA originates from a subset of glycan N-acetylglucosamine residues on enzymatically glycosylated acute-phase proteins. We hypothesized that the amplitude of the GlycA signal might provide a unique and convenient measure of systemic inflammation. METHODS We developed a spectral deconvolution algorithm to quantify GlycA signal amplitudes from automated NMR LipoProfile(®) test spectra and assessed analytic precision and biological variability. Spectra of acute-phase glycoproteins and serum fractions were analyzed to probe the origins of the GlycA signal. GlycA concentrations obtained from archived NMR LipoProfile spectra of baseline plasma from 5537 participants in the Multi-Ethnic Study of Atherosclerosis (MESA) were used to assess associations with demographic and laboratory parameters including measures of inflammation. RESULTS Major acute-phase protein contributors to the serum GlycA signal are α1-acid glycoprotein, haptoglobin, α1-antitrypsin, α1-antichymotrypsin, and transferrin. GlycA concentrations were correlated with high-sensitivity C-reactive protein (hsCRP) (r = 0.56), fibrinogen (r = 0.46), and interleukin-6 (IL-6) (r = 0.35) (all P < 0.0001). Analytic imprecision was low (intra- and interassay CVs 1.9% and 2.6%, respectively) and intraindividual variability, assessed weekly for 5 weeks in 23 healthy volunteers, was 4.3%, lower than for hsCRP (29.2%), cholesterol (5.7%), and triglycerides (18.0%). CONCLUSIONS GlycA is a unique inflammatory biomarker with analytic and clinical attributes that may complement or provide advantages over existing clinical markers of systemic inflammation.

Lipoprotein insulin resistance index: a lipoprotein particle-derived measure of insulin resistance.

UNLABELLED Abstract Background: Lipoprotein particle sizes and concentrations are characteristically altered in patients with insulin resistance (IR) or type 2 diabetes mellitus (T2DM). This study assessed the ability of an IR score, based on nuclear magnetic resonance (NMR)-derived lipoprotein information, to detect IR in otherwise healthy individuals. METHODS Lipoprotein subclass and size information were evaluated for strength of association with IR, as measured by homeostasis model assessment of insulin resistance (HOMA-IR) in the Multi-Ethnic Study of Atherosclerosis (MESA). To increase the likelihood of identifying subjects with IR, six lipoprotein measures were combined into a single algorithm. The resulting assay [Lipoprotein Insulin Resistance Index (LP-IR)] was developed using HOMA-IR in 4972 nondiabetic subjects from MESA and verified independently using glucose disposal rates (GDRs) measured during hyperinsulinemic-euglycemic clamps in 56 insulin-sensitive, 46 insulin-resistant, and 46 untreated subjects with T2DM. RESULTS LP-IR exhibited stronger associations with HOMA-IR (r=0.51) and GDR (r=-0.53) than each of the individual lipoprotein parameters as well as the triglycerides/high-density lipoprotein cholesterol (TGs/HDL-C) ratio (r=0.41 and -0.44, respectively). In MESA, associations between the LP-IR score and HOMA-IR were strong in men (r=0.51), women (r=0.52), European Americans (r=0.58), African Americans (r=0.48), Chinese Americans (r=0.49), and Hispanic Americans (r=0.45). When LP-IR was categorized by HOMA-IR and either body mass index (BMI) or fasting plasma glucose (FPG), subgroups were revealed whose LP-IR scores were high (≥ 50), despite having normal BMIs (<24 kg/m(2)) or FPG (<100 mg/dL). CONCLUSIONS LP-IR scores had strong associations with multiple measures, HOMA-IR, and GDR, the former being more reflective of hepatic and the latter of peripheral insulin sensitivity, and may represent a simple means to identify individuals with IR.

GlycA, a marker of acute phase glycoproteins, and the risk of incident type 2 diabetes mellitus: PREVEND study

BACKGROUND GlycA is a recently developed glycoprotein biomarker of systemic inflammation that may be predictive of incident type 2 diabetes mellitus (T2DM). METHODS Analytical performance of the GlycA test, measured on the Vantera® Clinical Analyzer, was evaluated. To test its prospective association with T2DM, GlycA was measured in 4524 individuals from the PREVEND study and a survival analysis was performed with a mean follow-up period of 7.3y. RESULTS Imprecision for the GlycA test ranged from 1.3-2.3% and linearity was established between 150 and 1588μmol/l. During the follow-up period, 220 new T2DM cases were ascertained. In analyses adjusted for relevant covariates, GlycA was associated with incident T2DM; hazard ratio (HR) for the highest vs. lowest quartile 1.77 [95% Confidence Interval (CI): 1.10-2.86, P=0.01], whereas the association of high sensitivity C-reactive protein (hsCRP) with T2DM was not significant. GlycA remained associated with incident T2DM after additional adjustment for hsCRP; HR 1.71 [1.00-2.92, P=0.04]. A multivariable adjusted analysis of dichotomized subgroups showed that the hazard for incident T2DM was highest in the subgroup with high GlycA and low hsCRP (P=0.03). CONCLUSIONS The performance characteristics of the GlycA test reveal that it is suitable for clinical applications, including assessment of the risk of future T2DM.

NMR measurement of LDL particle number using the Vantera® Clinical Analyzer

BACKGROUND The Vantera Clinical Analyzer was developed to enable fully-automated, high-throughput nuclear magnetic resonance (NMR) spectroscopy measurements in a clinical laboratory setting. NMR-measured low-density lipoprotein particle number (LDL-P) has been shown to be more strongly associated with cardiovascular disease outcomes than LDL cholesterol (LDL-C) in individuals for whom these alternate measures of LDL are discordant. OBJECTIVE The aim of this study was to assess the analytical performance of the LDL-P assay on the Vantera Clinical Analyzer as per Clinical Laboratory Standards Institute (CLSI) guidelines. RESULTS Sensitivity and linearity were established within the range of 300-3500 nmol/L. For serum pools containing low, medium and high levels of LDL-P, the inter-assay, intra-assay precision and repeatability gave coefficients of variation (CVs) between 2.6 and 5.8%. The reference interval was determined to be 457-2282 nmol/L and the assay was compatible with multiple specimen collection tubes. Of 30 substances tested, only 2 exhibited the potential for assay interference. Moreover, the LDL-P results from samples run on two NMR platforms, Vantera Clinical Analyzer and NMR Profiler, showed excellent correlation (R(2)=0.96). CONCLUSIONS The performance characteristics suggest that the LDL-P assay is suitable for routine testing in the clinical laboratory on the Vantera Clinical Analyzer, the first automated NMR platform that supports NMR-based clinical assays.

HDL particle number measured on the Vantera®, the first clinical NMR analyzer.

OBJECTIVES Nuclear magnetic resonance (NMR) spectroscopy has been successfully applied to the measurement of high-density lipoprotein (HDL) particles, providing particle concentrations for total HDL particle number (HDL-P), HDL subclasses (small, medium, large) and weighted, average HDL size for many years. Key clinical studies have demonstrated that NMR-measured HDL-P was more strongly associated with measures of coronary artery disease and a better predictor of incident cardiovascular disease (CVD) events than HDL-cholesterol (HDL-C). Recently, an NMR-based clinical analyzer, the Vantera(®), was developed to allow lipoprotein measurements to be performed in the routine, clinical laboratory setting. The aim of this study was to evaluate and report the performance characteristics for HDL-P quantified on the Vantera(®) Clinical Analyzer. DESIGN AND METHODS Assay performance was evaluated according to Clinical and Laboratory Standards Institute (CLSI) guidelines. In order to ensure that quantification of HDL-P on the Vantera(®) Clinical Analyzer was similar to the well-characterized HDL-P assay on the NMR profiler, a method comparison was performed. RESULTS The within-run and within-lab imprecision ranged from 2.0% to 3.9%. Linearity was established within the range of 10.0 to 65.0 μmol/L. The reference intervals were different between men (22.0 to 46.0 μmol/L) and women (26.7 to 52.9 μmol/L). HDL-P concentrations between two NMR platforms, Vantera(®) Clinical Analyzer and NMR Profiler, demonstrated excellent correlation (R(2) = 0.98). CONCLUSIONS The performance characteristics, as well as the primary tube sampling procedure for specimen analysis on the Vantera(®) Clinical Analyzer, suggest that the HDL-P assay is suitable for routine clinical applications.

High-density lipoprotein and inflammation in cardiovascular disease.

Great advances are being made at the mechanistic level in the understanding of the structural and functional diversity of high-density lipoprotein (HDL). HDL particle subspecies of different sizes are now known to differ in the protein and lipid cargo they transport, conferring on them the ability to perform different functions that in aggregate would be expected to provide protection against the development of atherosclerosis and its downstream clinical consequences. Exacerbating what is already a very complex system is the finding that inflammation, via alteration of the proteomic and lipidomic composition of HDL subspecies, can modulate at least some of their functional activities. In contrast to the progress being made at the mechanistic level, HDL epidemiologic research has lagged behind, largely because the simple HDL biomarkers used (mainly just HDL cholesterol) lack the needed complexity. To address this deficiency, analyses will need to use multiple HDL subspecies and be conducted in such a way as to eliminate potential sources of confounding. To help account for the modulating influence of inflammation, effective use must also be made of inflammatory biomarkers including searching systematically for HDL-inflammation interactions. Using nuclear magnetic resonance (NMR)-measured HDL subclass data and a novel NMR-derived inflammatory biomarker, GlycA, we offer a case study example of the type of analytic approach considered necessary to advance HDL epidemiologic understanding.

Differences in GlycA and lipoprotein particle parameters may help distinguish acute kawasaki disease from other febrile illnesses in children

BackgroundGlycosylation patterns of serum proteins, such as α1-acid glycoprotein, are modified during an acute phase reaction. The response of acute Kawasaki disease (KD) patients to IVIG treatment has been linked to sialic acid levels on native IgG, suggesting that protein glycosylation patterns vary during the immune response in acute KD. Additionally, the distribution and function of lipoprotein particles are altered during inflammation. Therefore, the aim of this study was to explore the potential for GlycA, a marker of protein glycosylation, and the lipoprotein particle profile to distinguish pediatric patients with acute KD from those with other febrile illnesses.MethodsNuclear magnetic resonance was used to quantify GlycA and lipoprotein particle classes and subclasses in pediatric subjects with acute KD (n = 75), post-treatment subacute (n = 36) and convalescent (n = 63) KD, as well as febrile controls (n = 48), and age-similar healthy controls (n = 48).ResultsGlycA was elevated in acute KD subjects compared to febrile controls with bacterial or viral infections, IVIG-treated subacute and convalescent KD subjects, and healthy children (P <0.0001). Acute KD subjects had increased total and small low density lipoprotein particle numbers (LDL-P) (P <0.0001) and decreased total high density lipoprotein particle number (HDL-P) (P <0.0001) compared to febrile controls. Consequently, the ratio of LDL-P to HDL-P was higher in acute KD subjects than all groups tested (P <0.0001). While GlycA, CRP, erythrocyte sedimentation rate, LDL-P and LDL-P/HDL-P ratio were able to distinguish patients with KD from those with other febrile illnesses (AUC = 0.789–0.884), the combinations of GlycA and LDL-P (AUC = 0.909) or GlycA and the LDL-P/HDL-P ratio (AUC = 0.910) were best at discerning KD in patients 6–10 days after illness onset.ConclusionsHigh levels of GlycA confirm enhanced protein glycosylation as part of the acute phase response in KD patients. When combined with common laboratory tests and clinical characteristics, GlycA and NMR-measured lipoprotein particle parameters may be useful for distinguishing acute KD from bacterial or viral illnesses in pediatric patients.