Research ArticleArticle

Reference Measurement Procedure for Total Glycerides by Isotope Dilution GC-MS

Selvin H. Edwards, Shelton L. Stribling, Susan D. Pyatt, Mary M. Kimberly
DOI: 10.1373/clinchem.2011.177063 Published March 2012

Abstract

BACKGROUND: The CDC's Lipid Standardization Program established the chromotropic acid (CA) reference measurement procedure (RMP) as the accuracy base for standardization and metrological traceability for triglyceride testing. The CA RMP has several disadvantages, including lack of ruggedness. It uses obsolete instrumentation and hazardous reagents. To overcome these problems the CDC developed an isotope dilution GC-MS (ID-GC-MS) RMP for total glycerides in serum.

METHODS: We diluted serum samples with Tris-HCl buffer solution and spiked 200-μL aliquots with [13C3]-glycerol. These samples were incubated and hydrolyzed under basic conditions. The samples were dried, derivatized with acetic anhydride and pyridine, extracted with ethyl acetate, and analyzed by ID-GC-MS. Linearity, imprecision, and accuracy were evaluated by analyzing calibrator solutions, 10 serum pools, and a standard reference material (SRM 1951b).

RESULTS: The calibration response was linear for the range of calibrator concentrations examined (0–1.24 mmol/L) with a slope and intercept of 0.717 (95% CI, 0.7123–0.7225) and 0.3122 (95% CI, 0.3096–0.3140), respectively. The limit of detection was 14.8 μmol/L. The mean %CV for the sample set (serum pools and SRM) was 1.2%. The mean %bias from NIST isotope dilution MS values for SRM 1951b was 0.7%.

CONCLUSIONS: This ID-GC-MS RMP has the specificity and ruggedness to accurately quantify total glycerides in the serum pools used in the CDC's Lipid Standardization Program and demonstrates sufficiently acceptable agreement with the NIST primary RMP for total glyceride measurement.

Clinical measurement of serum glyceride concentrations is an important parameter for assessing and managing cardiovascular disease (CVD)3 risk. Triglycerides are an independent risk factor for CVD (1,–,3) and a therapeutic target in hypertriglyceridemic patients. In addition, with the use of the Friedewald equation triglycerides are factored into approximating LDL cholesterol, a major therapeutic target for treatment. Hence a need persists for well-characterized reference measurement procedures (RMPs) to guarantee the accuracy and traceability of serum glycerides obtained from routine procedures. In past years, traceability of clinical triglyceride measurements was established through participation in the CDC's Lipid Standardization Program (LSP), which standardized triglyceride measurements by the chromotropic acid (CA) RMP as the accuracy base for triglyceride measurements. Indeed, the Adult Treatment Panel III–derived guidelines for managing CVD risk factors from epidemiological and clinical studies that were standardized by secondary RMPs (total cholesterol, HDL cholesterol, LDL cholesterol, and triglycerides) at the CDC (4).

Although the CDC has been standardizing triglyceride measurements for more than 40 years with the CA RMP, maintenance of the method has become progressively more challenging because it uses obsolete instrumentation that was difficult to replace. In addition, it uses highly toxic reagent chemicals and is not specific for triglycerides (5). Clinical methods that are standardized to the CA RMP also are not specific for triglycerides because the reagents hydrolyze not only triglycerides, but also monoglycerides and diglycerides to glycerol. Thus, the measurement is actually a measurement of total glyceride rather than triglycerides (6). To overcome these challenges the CDC has developed a robust isotope dilution–GC-MS (ID-GC-MS) secondary RMP for total glycerides in serum to more accurately standardize routine clinical serum glyceride measurements.

ID–mass spectrometry (MS) procedures permit rapid interference-free measurement of glycerides in serum. The selectivity and specificity are enhanced when this technique is coupled with a separation technique such as gas chromatography. ID-GC-MS offers several advantages over other non-MS techniques, which makes it better suited as an RMP. These advantages include lack of dependence on analyte recovery as well as low imprecision and excellent reliability. Moreover, optimization of assay performance for analyte separation from possible matrix interferences can occur in either the chromatographic or the spectrometry zone.

Several MS methods (5, 7,–,10) have been reported as primary RMP and secondary RMP for serum glycerides. These procedures hydrolyze glycerides in serum to detect and quantify the released glycerol by MS. Because glycerol is a highly polar molecule the samples are converted to a stable derivative that is compatible with GC analysis. Ellerbe et al. (5) combined butylboronic acid and N,O-bis(trimethylsilyl)trifluroacetamide to form a stable trimethylsilyl (TMS) derivative. Siekmann (10) reacted hydrolyzed glycerol with heptafluorobutyric anhydride to produce a fluorinated derivative, and Bernert et al. (9) also formed the TMS derivative for ID-GC-MS analysis. These derivatives permit reliable quantification of total glycerides, but the reactions are very sensitive to moisture.

It is known that reaction of glycerol with acetic anhydride/pyridine is an easy mechanism to produce glycerol triacetate for GC-MS analysis (11, 12) and the reaction can occur in the presence of water and an excess of the derivatization mixture. This procedure can reduce the total extraction and derivatization time before GC-MS without a need for complete dry-down. Furthermore, the derivative is stable and readily extractable by organic solvents. Hence, we developed an ID-GC-MS RMP based on a multilevel linear calibration procedure to measure total glycerides (the sum of monoglycerides, diglycerides, triglycerides, and free glycerol) in Tris-HCl–diluted serum as glycerol triacetate derivative.

Materials and Methods

REAGENTS AND CHEMICALS

We purchased standard reference materials (SRMs) for pure tripalmitin (SRM 1595) and lipids in frozen (liquid) human serum (SRM 1951b) from NIST. Serum pools were prepared at Solomon Park Research Laboratories according to CLSI C37A guidelines (13). Solomon Park Research Laboratories also provided a set of 10 frozen native serum samples from unidentified individuals. Lyophilized serum samples were obtained through participation in the IFCC External Quality Assessment Scheme for Reference Laboratories in Laboratory Medicine (IFCC–RELA) (14). We used [13C3]-glycerol (calculated purity, 70%) supplied by Cambridge Isotopes as the internal standard (IS). Absolute ethanol (200 proof) was obtained from Aaper Alcohol & Chemical Company. Potassium hydroxide (85%), sodium bicarbonate, Tris-HCl buffer, Triton X-100, ethyl acetate (American Chemical Society grade), pyridine, acetic anhydride (American Chemical Society grade), and N,O-bis(trimethylsilyl)acetamide:pyridine (Trisil BSA) were purchased from Fisher Scientific.

INSTRUMENTATION

We used a Digiflex TP (Titertek) automatic pipettor equipped with dual microprocessor-controlled, direct-drive stepper motors for aspirating and dispensing solutions, and a Turbovap LV evaporator (Caliper Life Sciences) for drying samples. Sartorius AG supplied an analytical balance. The automatic pipettors and analytical balance were gravimetrically calibrated using NIST-certified weights. Chromatography was conducted on an Agilent 6890 GC (Agilent Technologies) with an HP series, 6890 autosampler and an Agilent autosampler controller. A Phenomenex ZB50-ms (50% phenyl)-methylpolysiloxane capillary column (Phenomenex) was installed between the GC and an Agilent 5973 mass selective detector (MSD). We used Agilent ChemStation software for instrument control, data acquisition, and processing.

CALIBRATOR SOLUTION PREPARATION

A detailed description of the preparation of primary standard solution, reagents, and sample processing can be found in Supplemental Data File I in the Data Supplement that accompanies the online version of this article at http://www.clinchem.org/content/vol58/issue4. We prepared stock solutions of pure tripalmitin SRM 1595 in toluene at 12.38 mmol/L and prepared 100-mL portions of the working calibrator solutions from this solution. We used calibrated volumetric pipettes to transfer exact volumes of stock solution (5, 10, 20, 30, 40, 60, and 100 mL) to prepare 3 sets of working calibrators at 0.06, 0.12, 0.25, 0.37, 0.49, 0.74 and 1.24 mmol/L in toluene.

An aqueous solution of [13C3]-glycerol (2.15 mmol/L) for use as the IS was prepared by weighing 0.43 mmol (40 mg) and dissolving it in 200 mL of deionized water at ambient temperature.

SAMPLE PREPARATION FOR ANALYSIS

A extensive description of the preparation of all key reagents such as 0.30 mol/L ethanol/potassium hydroxide, Tris-HCl buffer solution (pH 7.5, 0.05 mmol/L, 2.5% TritonX-100), and sodium bicarbonate (0.9 mol/L) can be found in online Supplemental Data File 1. Fresh-frozen serum samples were thawed and homogenized on a hematology mixer. Lyophilized serum pools were prepared in accordance with the manufacturer's instructions (14). We used an automatic pipettor to dilute serum samples with Tris-HCl buffer (pH 7.5, 0.5 mmol/L, 0.25% Triton X-100), and 200 μL of the diluted serum and 200 μL of [13C3]-glycerol IS solution were hydrolyzed in 0.30 mol/L alcoholic KOH at 60 °C for 1 h (5). We evaporated the samples to dryness under nitrogen then derivatized the hydrolysate with a 3:1 mixture of pyridine and acetic anhydride at 65 °C. Subsequently, we extracted the derivatized product (glycerol triacetate) with HPLC grade ethyl acetate and washed the organic layer 2 times with 5.0 mL of sodium bicarbonate (80 g sodium bicarbonate in 1 L deionized water) and deionized water. We transferred 400 μL of the saturated organic layer into a microcentrifuge tube and centrifuged at approximately 12 100g for 1 min to completely separate the residual water from the ethyl acetate layer. The ethyl acetate was placed in a sample vial then analyzed by GC-MS.

GC-MS ANALYSIS

We performed GC-MS analysis on an Agilent 5973 bench-top MSD that was connected to a 6890 gas chromatograph. The gas chromatograph was equipped with a ZB50-ms capillary column (film thickness 30 m × 0.5 mm × 0.1 μm) (Phenomenex) and an auto sampler. The GC injector port was operated in splitless mode and the temperature was maintained at 295 °C. The initial column head pressure was 7.5 psi, and the helium carrier gas velocity was maintained at 40 cm/s. The GC oven was operated isothermally at 160 °C for the 6-min analysis. The transfer line between the GC and the MSD was maintained at 250 °C and the MS source and quadrupoles were 230 °C and 150 °C, respectively. The MS was operated in electron impact ionization mode and we performed mass ion detection in selected ion-monitoring mode with the electron voltage set at 70 eV. The selected ions used for quantification were m/z 145 and 147, corresponding to fragment ions from unlabeled and labeled glycerol triacetate, respectively. We analyzed all the calibration standard solutions in duplicate and used the ratios of the ion intensities (m/z 145/147) to construct a calibration curve that was used to quantify total glycerides (as glycerol triacetate) in serum samples with undetermined total glyceride concentration.

STATISTICAL ANALYSIS

We performed statistical analysis with Microsoft Excel and Analyse-it for Microsoft Excel (version 2.02). Simple least squares regression for calibration was performed in Microsoft Excel. ANOVA, Bland–Altman (15, 16), and weighted Deming regression were performed with Analyse-it software.

LINEARITY

We tested the linearity of mass ratios of unlabeled glycerol to [13C3]-glycerol in the range 0.30 (blank) to 1.22 (1.24 mmol/L) with calibrator solutions spiked with a constant concentration of IS. The fraction of the signal arising from labeled glycerol overlapping into the selected ion for unlabeled glycerol was determined experimentally by repeat injection of the calibration blank. We used simple least squares regression to establish the calibration curve. The limit of detection (LOD) was approximated by use of the equation: LOD = 3.3(SD)/S, (17) where SD and S are the SD of the y-intercept responses and the slope of the regression line from 22 runs, respectively.

IMPRECISION AND BIAS

We assessed the imprecision of the RMP by analyzing 10 serum pools and an SRM, 1951b; [concentrations 1.37 mmol/L (I) and 2.96 mmol/L (II)] in quadruplicate in 5 independent analytical runs and used the results to determine the intraassay, interassay, and total percent CVs (%CV) for the method. To assess the long-term variability and reliability of the procedure we calculated imprecision statistics from 2 QC materials used in each run for a period of 1 year.

We evaluated the method bias in a comparability assessment with the NIST ID-GC-MS primary RMP (5) by analyzing a set of 15 samples consisting of 1 SRM (SRM 1951b); 2 concentrations, 5 native serum samples, and 8 serum pools. NIST performed 2 analytical runs with duplicate measurements in every run. We analyzed the same samples in quadruplicate in 4 independent analytical runs. NIST did not analyze SRM 1951b in this study, so we compared our ID-GC-MS results for 1951b, concentrations I and II, to the total glycerides reference values published on the certificate of analysis for this SRM (18) and compared the total glycerides values for the other samples to measurements determined by NIST with the primary RMP during this study. We judged the bias of the procedure against prespecified performance goals established at the beginning of the study. These performance criteria are tighter than those recommended by the National Cholesterol Education Program's Working Group on Lipoprotein Measurement for field methods (19). This approach is similar to that used by the Cholesterol Reference Method Laboratory Network when they selected performance criteria for the cholesterol RMP (20). Briefly, the acceptance criterion for the mean bias was set at ±2% vs NIST-assigned reference values; the correlation coefficient (r2) must be >0.95 (21), and slope of the regression must be close to 1.0. To further validate this ID-GC-MS procedure, we analyzed a pair of lyophilized serum pools that we obtained through participation in 2 cycles of the IFCC–RELA (14).

Results

Fig. 1A shows the selected ion mass spectra for unlabeled and labeled glycerol triacetate derivative. The spectrum for the unlabeled derivative was consistent with the spectra for glycerol triacetate in the NIST mass spectral library (22). Fig. 1B shows the selected ion chromatogram of unlabeled glycerol (m/z = 145) and the IS (m/z = 147). The unlabeled glycerol and [13C3]-glycerol triacetate derivatives eluted from the capillary column at the same retention time (4.35 min). The ratio of ion intensities vs standard concentration was linear for the range of standards used. Ordinary least squares regression of the ion ratios of unlabeled and [13C3]-glycerol vs the concentration of the calibrators produced a slope, y intercept, and SE of the estimate (Sy|x) of 0.717 (95% CI, 0.7123–0.7225), 0.3122 (95% CI, 0.3096–0.3140), and 0.0023 mmol/L, respectively. The y intercept is consistent with the fraction of the labeled IS signal overlapping into the ion intensity of unlabeled glycerol. The calculated LOD was 14.8 μmol/L (n = 22 runs).

Fig. 1.
Fig. 1. (A), Mass spectrum and fragment ions for unlabeled and labeled glycerol triacetate derivatives; the circle highlights the quantitation mass ion (m/z 145) for the native glycerol triacetate derivative appearing in the mass spectrum of the labeled derivative.

Mass spectrum acquired at 70 eV. (B), Selected ion chromatogram for a glycerol triacetate (triacetin) derivative from a serum sample spiked with [13C3]-glycerol. The concentration of total glycerides in the sample was 2.57 mmol/L and the concentration of the IS was 2.15 mmol/L.

IMPRECISION AND BIAS

The total %CV for SRM 1951b, concentrations I and II, and the 10 serum pools ranged from 1.0% to 1.7% with a mean of 1.2% (Table 1). The mean total %CVs are consistent with the long-term variability of the procedure, which is reflected in the imprecision (mean %CV = 1.4%, n = 61) of the QC materials with time. Fig. 2 shows the control charts for 2 long-term QC materials used in our laboratory for approximately 12 months. The means (SDs) for low and high QCs, which were calculated from the control runs for the 12-month period, were 1.10 (0.021) mmol/L [97.4 (1.78) mg/dL] and 2.03 (0.022) mmol/L [181 (1.92) mg/dL], respectively.

View this table:
Table 1.

Imprecision evaluation for 10 serum pools and SRM 1951b.a

Fig. 2.
Fig. 2. (A), QC chart for a low total glyceride (TG) QC material used for approximately 12 months in the CDC LSP.

Each point represents the mean of 4 replicate measurements per run (n = 66). The broken lines represent upper and lower 95% and 99% confidence limits. (B), QC chart for a high-concentration total glyceride QC material used for approximately 12 months in the CDC LSP. Each point represents the mean of 4 replicate measurements per run (n = 66). The broken lines represent upper and lower 95% and 99% confidence limits.

The mean %bias between the proposed ID-GC-MS RMP and the NIST's primary ID-GC-MS RMP ranged from −2.2% to 1.1% for SRM 1951b, 5 native serum samples, and 8 serum pools used in the interlaboratory comparison (Table 2). The mean %bias for the SRMs specifically was 0.6%. Our results for SRM 1951b agreed with the NIST target value for total glycerides; concentrations I and II were within the uncertainty limits reported on the NIST certificate of analysis (18).

View this table:
Table 2.

Interlaboratory comparison of ID-GC-MS for total glycerides in SRM 1951b; concentration I and II, 5 native serum samples, and 8 serum pools.

The equation derived from a weighted Deming regression of our ID-GC-MS RMP vs NIST's ID-GC-MS RMP measurements for 14 (highest value excluded) samples was: y = 0.99 (95% CI, 0.97–1.00) + 0.03 (95% CI, 0.01–0.05) (mmol/L), and Sy|x for the slope and intercept was 0.02 mmol/L. The 95% limits of agreement, determined by the Bland–Altman test, ranged from −1.3% (95% CI, −2.3 to −0.3%) to 2.8% (95% CI, 1.7%–3.7%) between the measurements (Fig. 3). The mean bias between the 2 methods was 0.7% (95% CI, 0.1–1.3%).

Fig. 3.
Fig. 3. Bland–Altman plot for test of agreement between CDC's ID-GC-MS RMP and the NIST primary RMP for SRM 1951b; concentrations I and II, 4 native serum samples and 8 serum pools for n = 14 samples.

UCI, upper CI; TG, total glycerides; LCI, lower CI.

For the IFCC–RELA lyophilized serum pools the %biases were calculated vs the group mean among reference laboratories performing ID-MS methods. The %bias from the group mean ranged from 0.01 to 0.03 mmol/L (Table 3). The expanded uncertainty (23) associated with total glyceride values obtained from quadruplicate measurements in 3 analytical runs ranged from 0.9% to 2.4%.

View this table:
Table 3.

Summary of results of total glyceride (TG) measurements in lyophilized serum samples from 2 cycles of the IFCC–RELA.

Discussion

The primary focus was to establish an ID-GC-MS RMP for total glycerides in serum at the CDC that could reliably guarantee the transfer of accuracy from a well-established accuracy base to routine or field methods in clinical laboratories. ID-GC-MS methods have been proven to be advantageous for total glycerides (measured as glycerol) in serum, and a few IDMS procedures are recognized and listed in the Joint Committee on Traceability in Laboratory Medicine database as higher-order RMPs (24). Our ID-GC-MS has similar performance characteristics to RMPs recognized by the Joint Committee on Traceability in Laboratory Medicine and can, therefore, be used to effectively standardize total glyceride measurements in the CDC LSP. We did not have the opportunity to compare this RMP to the former CA RMP before it was decommissioned. Furthermore, a true comparison would not be feasible because the ID-GC-MS RMP and the CA RMP do not measure the same species.

EVALUATION OF METHOD CHARACTERISTICS

Extraction and derivatization.

Extraction and derivatization of glycerol from the aqueous phase after hydrolyzing the net glycerides to glycerol and fatty acid is difficult because glycerol is readily miscible with water; this poses a major challenge for GC-MS quantitative methods. We considered adopting a few extraction processes described in the literature for serum glycerides (5, 10). The procedure reported by Ellerbe et al. (5) is a time-consuming, laborious procedure that incorporates 2 derivatization steps to produce a TMS derivative for GC-MS analysis. The procedures reported by Siekmann (10) and Bernert et al (9) are shorter processes and detect glycerol as heptafluorinated and TMS derivative, respectively, after hydrolysis. Although these methods shorten the analysis time, they require that the sample be completely free of moisture. Our ID-GC-MS RMP has similarities to these procedures except that it involves direct derivatization of glycerol to the stable triacetate derivative, which is readily extracted with ethyl acetate. Furthermore the derivatization process can proceed even in the presence of small amounts of water. An excess of pyridine was used because the reaction produces acetic acid as a byproduct, which can deteriorate the GC column, leading to peak broadening. Adequate washing of the ethyl acetate layer with sodium bicarbonate and water effectively removes traces of acetic acid from the sample. Sample extraction and derivatization are short processes that collectively result in a short total analysis time (4 h). This 1-step derivatization for ID-GC-MS analysis can allow high sample throughput.

Linearity.

Selection of an appropriately labeled IS is essential to ensure a linear correlation for the response across the measurement range of calibrator concentrations used. It is essential for accurate calibration of the analytical system and permits ready interpretation of the instrument data. Other ID-MS procedures for total glycerides and glycerol that have been described in the literature use a variety of labeled analogs including [13C2]-glycerol (10, 25), [13C3]-tripalmitin (5, 25), and deuterated glycerol (26) as IS. In our procedure we used [13C3]-glycerol as the IS because it is commercially available, all carbons are isotopically labeled with 13C, and it coelutes with unlabeled glycerol from the capillary column. However, the quantification ion for the triacetate derivative of native glycerol (m/z 145) is prominent in the mass spectrum of the pure labeled [13C3]-glycerol triacetate derivative (Fig. 1), which may result from natural isotopic abundance or incomplete labeling of the IS. In contrast, the presence of the signal for the IS (m/z 147) originating from unlabeled glycerol was negligible. Despite an obvious spectral and retention time overlap with this labeled analog, as expected (27) the calibration curve of ion ratios vs calibrator concentrations was linear with a positive y intercept. The y intercept was consistent with the fraction of [13C3]-glycerol triacetate showing up as unlabeled glycerol triacetate calculated from repeat injection (n = 10) of the pure IS. Further confirmation of the suitability of [13C3]-glycerol as the IS was demonstrated by the correlation coefficient (r2) (range 0.9996–1.0). Additionally, the residuals from the regression analysis did not show any concentration-dependent variation for the range of calibrator concentrations used.

Imprecision and bias.

The results summarized in Tables 1 and 2 demonstrate that intraassay and interassay imprecision and accuracy of total glyceride measurements by this ID-GC-MS RMP met our target specifications for mean bias, slope, and correlation coefficient, which are consistent with expectations of RMPs. The intraassay and interassy variabilities were consistent and contributed equally to the overall variability of the RMP. The analytical system was stable throughout the analysis, which is reflected in the low intraassay, interassay, and total %CV for the assay. Furthermore, systematic influences on the variance, which could magnify the imprecision in the measurements, were minimized. As expected (28), dilution of the serum samples with Tris-HCl buffer solution prevented precipitate formation but did not adversely affect the imprecision. Indeed, the mean total %CVs for the samples were consistent with the long-term mean %CV of the QC materials and provided further assurance of the stability, low imprecision, and reliability of this RMP.

Our mean %bias criterion (≤ ±2% vs NIST) for the ID-GC-MS RMP was met. The Bland–Altman plot represented in Fig. 3 shows that the mean bias between this procedure and the NIST primary ID-GC-MS RMP was sufficiently small and provided the confidence that the method can be used to accurately value-assign reference values on QC materials in the LSP. In addition, the 95% limits of agreement bands at −1.4% and 2.8% are tightly positioned around the mean bias for the methods. These limits are well within the allowable bias of 5% to 10% at 2.49 and 0.994 mmol/L (220 and 88 mg/dL, respectively) used by the LSP to certify methods and laboratories performing total glyceride measurements. The low %bias suggests that our ID-GC-MS RMP is free of interferences that would amplify the difference between the 2 procedures. Furthermore, the results of the IFCC–RELA interlaboratory comparison among reference laboratories performing IDMS methods summarized in Table 3 provides further assurance that this ID-GC-MS RMP is acceptable for assigning target values in CDC's LSP.

In summary, for approximately 40 years the CDC has been an active partner in assuring the quality and comparability of serum triglyceride measurements in epidemiological and clinical studies. Implementing this ID-GC-MS RMP will continue to sustain lipid standardization initiatives and assure traceability of routine total glyceride measurements. The RMP described is fast and simple. The glycerol triacetate derivative is easily prepared even in the presence of water and it is readily detected by MS. This RMP exhibits acceptable selectivity and specificity for the analyte and it can be used to accurately quantify total glycerides in fresh-frozen and lyophilized serum samples.

Acknowledgments:

The authors thank Dr. Karen Phinney, Dr. Michael Welch, and Dr. Lorna Sniegoski at NIST for coordinating the comparison study with the NIST primary RMP.

Footnotes

  • ↵3 Nonstandard abbreviations:

    CVD,
    cardiovascular disease;
    RMP,
    reference measurement procedure;
    LSP,
    Lipid Standardization Program, CA, chromotopic acid;
    ID-GC-MS,
    isotope dilution–GC-MS;
    MS,
    mass spectrometry;
    TMS,
    trimethylsilyl;
    SRM,
    standard reference material;
    IFCC–RELA,
    External Quality Assessment Scheme for Reference Laboratories in Laboratory Medicine;
    MSD,
    mass selective detector;
    LOD,
    limit of detection.

  • Author Contributions: All authors confirmed they have contributed to the intellectual content of this paper and have met the following 3 requirements: (a) significant contributions to the conception and design, acquisition of data, or analysis and interpretation of data; (b) drafting or revising the article for intellectual content; and (c) final approval of the published article.

  • Authors' Disclosures or Potential Conflicts of Interest: Upon manuscript submission, all authors completed the Disclosures of Potential Conflict of Interest form. Potential conflicts of interest:

  • Employment or Leadership: None declared.

  • Consultant or Advisory Role: None declared.

  • Stock Ownership: None declared.

  • Honoraria: None declared.

  • Research Funding: Interagency Agreement with the National Heart Lung and Blood Institute and funding from the Division for Heart and Stroke Prevention, National Center for Chronic Disease Prevention and Health Promotion, CDC.

  • Expert Testimony: None declared.

  • Role of Sponsor: The funding organizations played no role in the design of study, choice of enrolled patients, review and interpretation of data, or preparation or approval of manuscript.

  • Received for publication October 4, 2011.
  • Accepted for publication December 12, 2011.

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