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Background Clinical laboratory patient databases are an untapped source of valuable diagnostic and prognostic information. However, the lack of associated clinical and/or demographic information and questionable generalizability to nonpatient populations often limit utility of these data. Objectives This study compared levels of cardiometabolic biomarkers between a national clinical laboratory patient cohort (Health Diagnostic Laboratory [HD Lab]) and the US population as inferred from the National Health and Nutrition Examination Survey (NHANES, 2011–2012). Methods Sample sizes for HD Lab ranged from 199,000 to 739,000 and for NHANES from 2200 to 5300. The latter were weighted to represent the adult US population (∼220 million). Descriptive statistics were compared for body mass index, 5 lipid biomarkers, and 3 glycemic biomarkers. Results Using age- and sex-matched data, mean biomarker values (mg/dL unless noted) and percent differences (%) for HD Lab vs NHANES were body mass index (kg/m 2 ), 29.1 vs 28.6 (1.7%); total cholesterol, 185 vs 193 (–4.1%); apolipoprotein B, 92 vs 90 (2.2%); low-density lipoprotein cholesterol, 107 vs 115 (–7%); high-density lipoprotein cholesterol, 53 vs 53 (0%); triglycerides, 128 vs 127 (0.8%); glucose, 99 vs 108 (–8.3%); insulin (uU/mL), 13.7 vs 13.4 (2.2%); and hemoglobin A1c (%), 5.6 vs 5.8 (–3.4%). Although all differences were statistically significant, only low-density lipoprotein cholesterol and glucose differed by more than 5%. These may reflect a greater use of medications among HD Lab patients and/or preanalytical factors. Conclusions Cardiometabolic risk markers from a national clinical laboratory were broadly similar to those of the US population; thus, with certain caveats, data from the former may be generalizable to the latter. [ABSTRACT FROM AUTHOR]

Background Discordance between measures of atherogenic lipoprotein particle number (apolipoprotein B [ApoB] and low-density lipoprotein [LDL] particle number by nuclear magnetic resonance spectroscopy [LDL-P NMR ]) is not well understood. Appropriate treatment considerations in such cases are unclear. Objectives To assess discordance between apoB determined by immunoassay and LDL-P NMR in routine clinical practice, and to characterize biomarker profiles and other clinical characteristics of patients identified as discordant. Methods Two retrospective cohorts were evaluated. First, 412,013 patients with laboratory testing performed by Health Diagnostic Laboratory, Inc., as part of routine care; and second, 1411 consecutive patients presenting for risk assessment/reduction at 6 US outpatient clinics. Discordance was quantified as a percentile difference (LDL-P NMR percentile − apoB percentile) and attainment of percentile cutpoints (LDL-P NMR ≥ 1073 nmol/L or apoB ≥ 69 mg/dL). A wide range of cardiovascular risk factors were compared. Results ApoB and LDL-P NMR values were highly correlated ( R 2 = 0.79), although substantial discordance was observed. Similar numbers of patients were identified as at-risk by LDL-P NMR when apoB levels were < 69 mg/dL (5%-6%) and by apoB values when LDL-P NMR was < 1073 nmol/L (6%-7%). Discordance (LDL-P NMR > apoB) was associated with insulin resistance, smaller LDL particle size, increased systemic inflammation, and low circulating levels of “traditional” lipids, whereas discordance (apoB > LDL-P NMR ) was associated with larger LDL particle size, and elevated levels of lipoprotein(a) and lipoprotein-associated phospholipase A2 (Lp-PLA 2 ). Conclusion Discordance between apoB and LDL-P NMR in routine clinical practice is more widespread than currently recognized and may be associated with insulin resistance. [ABSTRACT FROM AUTHOR]

The importance of lipoprotein (a)—Lp(a)—as a cardiovascular (CV) risk marker has been underscored by recent findings that CV risk is directly related to baseline Lp(a) levels, even in well-treated patients. Although there is currently little that can be done pharmacologically to lower Lp(a) levels, knowledge of its serum concentration is important in overall risk assessment. This review focuses on 1 aspect of Lp(a) that is rarely discussed directly: how to express its levels in serum. There is considerable confusion on this point, and a fuller understanding of what the concentration units mean will help improve study-to-study comparisons and thereby advance our understanding of the pathobiology of this lipoprotein particle. As discussed here, the term Lp(a) mass refers to the entire mass of the particle: lipids, proteins, and carbohydrates combined. At present, there are no commercially available assays that are completely insensitive to the variability in particle mass, which arises not only from differences in apo(a) isoform mass but also from variations in lipid mass. Because lipoprotein “particle number” (molar concentration) has been found to be superior to component-based metrics (ie, low-density lipoprotein particle vs cholesterol concentrations) for CV disease risk prediction, the development of a mass-insensitive Lp(a) assay should be a high priority. [ABSTRACT FROM AUTHOR]

Background: Omega-3 fatty acid (n-3 FA) biostatus can be estimated with red blood cell (RBC) membranes or plasma. The matrix that exhibits the lower within-person variability and is less affected by an acute dose of n-3 FA is preferred in clinical practice. Objective: We compared the acute effects of a large dose of n-3 FA on RBC and plasma levels of eicosapentaenoic acid (EPA) plus docosahexaenoic acid (DHA). Methods: Healthy volunteers (n = 20) were given 4 capsules containing 3.6 g of n-3 FA with a standardized breakfast. Blood samples were drawn at 0, 2, 4, 6, 8, and 24 hours. The EPA + DHA content of RBC membranes and plasma (the latter expressed as a percentage of total FA and as a concentration) were determined. General linear mixed models were used to analyze the mean response profiles in FA changes over time for plasma and RBCs. Results: At 6 hours after load, the plasma concentration of EPA + DHA had increased by 47% (95% confidence interval [CI], 24% to 73%) and the plasma EPA + DHA percentage of total FA by 19% (95% CI, 4.7% to 36%). The RBC EPA + DHA percentage of composition was unchanged [–0.6% (95% CI, −2.6% to 1.5%)]. At 24 hours, the change in both of the plasma EPA + DHA markers was 10-fold greater than that in RBCs. Conclusions: An acute dose of n-3 FA (eg, a meal of oily fish or fish oil supplements) taken within a day before a doctor’s visit can elevate levels of EPA + DHA in plasma, whether expressed as a percentage or a concentration, but not in RBC membranes. Similar to hemoglobin A1c, which is not affected by an acute glycemic deviation, RBCs provide a more reliable estimate of a patient’s chronic EPA + DHA status than does plasma. [Copyright &y& Elsevier]

Abstract: 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. [Copyright &y& Elsevier]