- Email: [email protected]
Quantification of multiple elements in dried blood spot samples
CLB-09463; No. of pages: 7; 4C: Clinical Biochemistry xxx (2017) xxx–xxx
Contents lists available at ScienceDirect
Clinical Biochemistry journal homepage: www.elsevier.com/locate/clinbiochem
Quantification of multiple elements in dried blood spot samples Lise Pedersen a, Karen Andersen-Ranberg b,e, Mads Hollergaard c, Mads Nybo d,⁎ a
Department of Clinical Biochemistry, Holbæk Hospital, Holbæk, Denmark Danish Ageing Research Center (DARC), University of Southern Denmark (SDU), Odense, Denmark c Danish National Neonatal Screening Biobank, Statens Serum Institute (SSI), Copenhagen, Denmark d Department of Clinical Biochemistry and Pharmacology, Odense University Hospital, Odense, Denmark e SHARE (Survey of Health, Ageing and Retirement in Europe), Denmark b
a r t i c l e
i n f o
Article history: Received 21 October 2016 Received in revised form 19 January 2017 Accepted 19 January 2017 Available online xxxx Keywords: Dried blood spots Elements Hematocrit ICP-MS Method validation
a b s t r a c t Background: Dried blood spots (DBS) is a unique matrix that offers advantages compared to conventional blood collection making it increasingly popular in large population studies. We here describe development and validation of a method to determine multiple elements in DBS. Methods: Elements were extracted from punches and analyzed using inductively coupled plasma-mass spectrometry (ICP-MS). The method was evaluated with quality controls with defined element concentration and blood spiked with elements to assess accuracy and imprecision. DBS element concentrations were compared with concentrations in venous blood. Samples with different hematocrit were spotted onto filter paper to assess hematocrit effect. Results: The established method was precise and accurate for measurement of most elements in DBS. There was a significant but relatively weak correlation between measurement of the elements Mg, K, Fe, Cu, Zn, As and Se in DBS and venous whole blood. Hematocrit influenced the DBS element measurement, especially for K, Fe and Zn. Conclusion: Trace elements can be measured with high accuracy and low imprecision in DBS, but contribution of signal from the filter paper influences measurement of some elements present at low concentrations. Simultaneous measurement of K and Fe in DBS extracts may be used to estimate sample hematocrit. © 2017 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.
1. Introduction Dried blood spots (DBS) are spots of capillary blood from a finger prick dripped onto filter paper, dried and then used for laboratory testing. DBS are commonly used in newborn screening for inborn errors of metabolism and in therapeutic drug monitoring [1], but has become increasingly popular as a sample matrix for biomarkers in population studies as they are easy to obtain, easy to transport, and allows collection in the field with a high response rate. To this can be added that collection of DBS are quick, relatively painless, less invasive than venipuncture and requires minimal field storage capacity. However, the number of validated assays for quantifying biomarkers in DBS samples is still relatively low compared with traditional whole blood, serum or plasma matrices. Reasons for this is the variety of challenges associated with analysis of DBS, e.g. contamination risk, blood spot heterogeneity, hematocrit effect and analyte on-card stability [2,3]. The sample volume is small (5 drops of blood on each card, i.e. approximately 275–375 μL) compared to conventional venipuncture (typical 5 mL of whole blood), and in many population studies and biobanks of e.g. ⁎ Corresponding author at: Dept. of Clinical Biochemistry and Pharmacology, Odense University Hospital, Sdr. Boulevard 29, DK-5000 Odense, Denmark. E-mail address: [email protected] (M. Nybo).
neonatal blood spots collected at birth only one card is obtained per subject. Consequently, samples for analysis are often as small as 3– 6 mm punches making the available volume of blood as small as 2– 5 μL, which is a challenge in terms of obtaining a sufficient recovery and analyte signal. For some analytical techniques analytes can be quantified or detected directly from DBS punches. However, for the majority of routine analytes, pharmaceutical substances and elements (metals and non-metals) it is necessary to develop an extraction protocol that ensures good recovery rates, minimizes the background contamination from the filter paper and is suitable for the analyte of interest. The ideal procedure enables extraction of a maximum number of analytes from the same punch allowing the remainder of the card to be used for other purposes. Recent development in high-sensitive element analyzers like inductively coupled plasma mass spectrometry (ICP-MS) instruments provides simultaneous measurement of multiple elements at very low concentrations. However, to utilize the ICP-MS technology elements must be extracted from the filter paper, which introduces a dilution factor and a potential loss of sensitivity. Methods for quantification of elements in DBS by ICP-MS have previously been reported [4–7]. These methods all used one-half or a whole intact dried spot with a diameter of 8–13 mm corresponding to a starting blood volume of 20–40 μL blood, and the filter paper was weighed to estimate the amount of blood in each sample.
http://dx.doi.org/10.1016/j.clinbiochem.2017.01.010 0009-9120/© 2017 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.
Please cite this article as: L. Pedersen, et al., Quantification of multiple elements in dried blood spot samples, Clin Biochem (2017), http:// dx.doi.org/10.1016/j.clinbiochem.2017.01.010
2
L. Pedersen et al. / Clinical Biochemistry xxx (2017) xxx–xxx
Our objective was to develop a method for determination of multiple elements in DBS samples using the smallest possible sample amount with fast throughput and a quality comparable to whole blood and plasma methods. This paper describes the development and validation of a protocol for extraction of a range of elements from two 3.2 mm punches and subsequent quantification by ICP-MS using matrix-matched calibrators. 2. Materials and methods For comparative analysis element concentrations of Co, Cu, Zn, As, Se, Cd and Pb were compared in a set of 17 matched whole blood samples and capillary blood collected on DBS filter paper, while Na, K and Fe were compared in a set of plasma samples and capillary blood collected on DBS filter paper. Element levels were also compared in matched DBS, whole blood QC samples and samples spiked with elements in order to cover a broader concentration range. 2.1. Subjects and samples Dried blood spots and venous blood were collected from adult volunteers and approved by The Regional Ethical Committee in Southern Denmark. Capillary blood was obtained from the participant's finger using a microtainer contact-activated lancet (Becton Dickinson, New Jersey, USA), and drops of blood were collected on Whatman 903 protein saver cards (GE Healthcare, Little Chalfont, UK) to fill all five discs. Each card was dried overnight at room temperature and thereafter stored separately in a Zip-Lock® bag with a desiccant at − 20 °C for three months until analysis. Prior to analysis, DBS cards were thawed at room temperature and 3.2 mm punches were produced by a semi-automatic DBS puncher (Perkin Elmer, Waltham, MA, USA). Venous blood was collected by antecubital venipuncture in metalfree tubes containing EDTA (Vacutainer Royal Blue, Becton Dickinson) or Li-heparin (Vacutainer Green, Becton Dickinson). For collection of plasma, whole blood samples were centrifuged at 3600g for 10 min at 4 °C, and aliquots of whole blood and plasma were stored at − 20 °C for three months until analysis. For method validation, 75 μL venous EDTA whole blood or whole blood spiked with elemental standard solutions was applied with a precision pipette on the Whatman cards. Quality control (QC) cards were prepared applying 75 μL whole blood QC materials from Sero (Billingstad, Norway), UTAK (Valencia, CA, USA), QMEQAS (Centre de Toxicologie, Quebéc, Canada) and UK NEQAS (Trace elements program, UK NEQAS, Sheffield, UK), respectively, on DBS cards. 2.2. Preparation of DBS samples with different hematocrit Seven portions of whole blood with hematocrit values between 22.5 and 79.1% were prepared from a single batch of packed washed erythrocytes and a single batch of plasma as described in NBS01-A6 CLSI standard, Appendix C3. The hematocrit value in each portion was measured on a Sysmex XN10 before aliquots of 75 μL were spotted onto filter paper as described. Element concentrations were measured in three replicates from DBS extracts at each hematocrit level. 2.3. Reagents and utensils Nitric acid 65%, Triton™ X-100 and Tracecert multi-trace elemental and single trace element standards for ICP-MS analysis were purchased from Sigma-Aldrich (St. Louis, MO, USA). Seronorm™ Certified Reference Materials (CRMs) were obtained from Sero (Billingstad, Norway). UTAK whole blood and serum QC were obtained from UTAK (Valencia, CA, USA). CRM for toxic metals in bovine blood was obtained from NIST (Gaithersburg, Maryland, USA), while whole blood external quality control (EQC) samples containing a range of elements in human
biological matrices were obtained from CTQ (QMEQAS program, Centre de Toxicologie, Quebéc, Canada) or from UK NEQAS (Trace elements program, UK NEQAS, Sheffield, UK). XN Check hematology control blood was obtained from Sysmex (Kobe, Japan). Ultrapure water (N 18 MΩ cm) from a Milli-Q system (Millipore, Bedford, MA, USA) was used for preparation of all buffers and standards. Clear polystyrene 96-wells flat bottom plates (NUNC, catalogue 439,454) and 12 mL MiniSorp™ tubes (NUNC, catalogue 468,608) was obtained from Thermo Fisher (Waltham, MA, USA). Three different lots of Whatman 903 protein saver cards were included in the method validation: Lots 6833909W082, 6912111W111, and 7018515W141. 2.4. Contamination control All handling of samples were performed in a dedicated trace element-clean laboratory. DBS were handled with gloved hands under a laminar flow, except during punching with the semi-automatic puncher. All plastic materials in contact with DBS (tubes, plates, tips) were decontaminated with a 5% HNO3 (v/v) solution overnight and dried under a laminar flow prior to use. 2.5. Instrumentation and ICP-MS conditions Analysis of isotopes 23Na, 24Mg, 39K, 44Ca, 52Cr, 56Fe, 55Mn, 58Ni, 59Co, Cu, 64Zn, 75As 78Se,114Cd and 208Pb in dried blood extracts and whole blood was performed on a iCAP-Qc ICP-MS (Thermo Fisher, Winsford, UK) equipped with collision cell technology with kinetic energy discrimination (CCTED). A flow of helium with a purity of N 99.999% (Strandmøllen, Ejby, Denmark) was introduced into the collision cell. Sample introduction was performed with a PFA-ST microflow nebulizer combined with a quartz cyclonic spray chamber (Trace elemental scientific, Omaha, NE, USA) in all instances. For automation of the analyses the ICP-MS was equipped with a Cetac ASX-520 autosampler (Cetac Technologies, Omaha, NE, USA). Conditions were daily optimized to obtain the highest signal-to-background ratio for 7Li, 59Co, 115In, 137Ba and 238 U along with the ratio of 140Ce16O +/140Ce+ b 2% for a solution of 1 μg/L of each trace element (Thermo Scientific, Tune B solution). Sample data were acquired in counts per second with three replicate readings and a dwell time of 50 ms. To overcome potential polyatomic interferences (such as 35Cl17O on 52 Cr, 35 Cl40Ar on 75As and 40Ar40Ar on 80Se) three approaches were employed: 1) if possible, selection of interference-free isotopes for analysis; 2) use of collision cell technology; or 3) use of an equation to correct for interferences. Collision cell technology was applied to elements 23 Na, 24Mg, 39K, 44Ca, 52Cr, 56Fe, 59Co, and 78Se. For selenium the less abundant isotope 78Se was measured in order to avoid interference of the 40Ar2+ dimer from the argon plasma instead of the most abundant isotope of selenium (80Se). Mathematical correction was applied to measurement of 78Se by the equation: I(78Se)-0.03461 I(83Kr). To compensate for uptake variation and analytical drift on the ICP-MS 71Ga (collision cell mode) and 208Bi (without collision cell) were added as internal standard in all tubes prior to analysis. Data were analyzed using the Qtegra™ software (version 2.2.1465.24) from Thermo Scientific (Winsford, UK). The hematocrit value in whole blood samples were measured on a Sysmex XN10 (Sysmex, Kobe, Japan), while plasma concentrations of Na, Mg, K and Fe were measured on an Architect c8000 (Abbott Laboratories, Illinois, USA). 63
2.6. Calibration and standards In order to maximize comparability between calibrators and unknown samples calibrators were by elemental spiking of a pool of artificial control blood that were deposited with 75 μL on “calibration cards” to be punched and extracted in a manner similar to unknown samples. By treating calibrators and samples in the same manner it is possible to
Please cite this article as: L. Pedersen, et al., Quantification of multiple elements in dried blood spot samples, Clin Biochem (2017), http:// dx.doi.org/10.1016/j.clinbiochem.2017.01.010
L. Pedersen et al. / Clinical Biochemistry xxx (2017) xxx–xxx
avoid additional quantification steps like weighing of the filer paper in order to estimate the total blood volume or determination of a dilution factor between calibrators and DBS extracts. However, the amount of blood in the punches may depend on hematocrit since a fixed punch size is used, and the actual sample size can therefore differ at abnormally low and high hematocrit values [8, 9]. In addition, some compounds may show a chromatographic effect with a higher concentration in a center punch relative to a peripheral punch [10]. The influence of both hematocrit and within-spot variation was therefore included in the method validation. To obtain calibrators with a hematocrit value comparable to patient samples an artificial blood pool was made mixing the XN Check level 3 hematology control (with defined hematocrit value) with a whole blood trace element control (Seronorm™ L-3). Further addition of ICP-MS multi trace element standard solution 4 in increasing amounts were used to create a 5point calibration curve for the trace elements As, Se and Cd. Addition of single element standards in increasing amounts were used to create a 5-point calibration curve used for Mg, Ca, Cu, Zn and Pb. For a calibration point with element concentrations between reagent blank and the pool, a two-fold dilution was prepared with Milli-Q water. As element concentrations of Na, K and Fe in whole blood samples requires predilution to obtain levels comparable to DBS extracts, a calibration curve for Na, K and Fe was constructed by serial dilution of the artificial blood pool starting with a 5-fold and ending in a 100-fold dilution prior to application. Dilution of the artificial blood pool lowered the hematocrit value and caused the samples to spread differently compared to whole blood samples, which could cause non-commutability between calibrator and samples [11]. Traceability of each element level in each calibrator point were verified by parallel analysis against independent whole blood QC standards with elemental “target” values from NEQAS for Trace elements (Surrey, UK) and QMEQAS (CTQ, Quebec, Canada). For elements K and Fe the levels in the calibrators were verified with QC Autonorm™ Human Liquid L-1 and L-2 from SERO (Billingstad, Norway) and with samples from KS-Clinical Chemistry in serum “wet chemistry” from Ringversuche (Referenzinstitut für Bioanalytik, Bonn, Germany). Aliquots of each calibrator point were stored at −20 °C. All “calibration cards” were freshly prepared the day before analysis on Whatman cards by applying 75 μL of each calibrator point to each of the five discs, where-after cards were allowed to dry overnight in a laminar flow bench prior to use. In each analytical run all intensities were corrected by subtraction of the mean intensity from three method blanks (signal from blank filter paper extract).
3
limits of blank (LoB), detection (LoD) and quantification (LoQ), respectively, and the hematocrit effect. Validation furthermore included unique DBS parameters such as signal contribution from blank filter paper from different lots, hematocrit effect and within-spot variation. The LoB for each isotope was determined from measurement of reagent blank (ICP-MS running buffer) in several analytical runs. The method LoB and LoD was defined as meanblank filter paper + (1645 ∗ sdblank filter paper) and LoB + (1645 ∗ sdblank filter paper), respectively [9]. The LoQ was defined as ten times the standard deviation of the blank filter paper concentration [16]. Imprecision was determined using six replicates of each of three QC levels, which were extracted and run against a standard curve as described. This was repeated in three separate runs to determine intra- and inter-assay imprecision (% coefficient of variation (CV%)). As punches were taken within the same spot as well as between spots of the same QC sample, intra- and inter-assay imprecision encompasses within- and between-spot variation. For evaluation of accuracy (% bias) two different approaches were used: 1) Whole blood samples of CRM or samples from EQC programs with target values were spotted on filter paper as described. The blood was then extracted and measured on the ICP-MS in three runs. 2.9. Statistical analysis ANOVA, Mann Whitney U test, linear regression analysis and BlandAltman analysis were all performed using GraphPad Prism version 5.00 (GraphPad Software, San Diego, California, USA). 3. Results 3.1. Extraction procedure As shown in Fig. 1, the signal for elements Fe and Se was considerably better using the extraction buffer with the lowest acid concentration (0.5% HNO3), which was also seen by the red coloration of DBS extracts when the lowest acid concentration was used (not shown). Increasing extraction time or temperature did not optimize element signals (not shown), but two subsequent extraction steps with respectively 100 μL gave a better yield than a single extraction step with 200 μL for 2 h. ANOVA analysis revealed that the three extraction procedures differed for all elements (p b 0.05). Mann-Whitney U test comparing two extractions showed that extraction using buffer 2 gave significantly superior extraction result (p b 0.05) for all elements except
2.7. Extraction protocol for ICP-MS analysis All analyses were performed using two 3.2 mm (diameter) DBS filter paper discs punched out with a semi-automatic DBS puncher (Perkin Elmer 1296) and placed in a 96-well plate before extraction of elements and subsequent analysis. The optimal extraction protocol encompassed two extraction steps: Extraction step 1 was performed by adding 100 μL of extraction buffer to each well followed by shaking on an orbital shaker (Wallac Delfia Plate Shaker 1296-001) at 1350 rpm for 1 h. As liquid is absorbed into the dry filter paper it was only possible to transfer 75 μL extract from each well to clean 10 mL polyethylene tubes (MiniSorp, Nunc, Denmark) containing 1 mL ICP-MS running buffer. In extraction step 2, additionally 100 μL of extraction buffer was added to each well and shaking was performed for an hour on the orbital shaker. From step 2 75 μL of extract were transferred to the MiniSorp tubes. Prior to analysis MiniSorp tubes were centrifuged at 2000 g for 10 min to avoid unintentional transfer of paper debris or undigested material. 2.8. Method validation Validation of the method was carried out to determine performance, which comprised precision in series, accuracy, method comparison,
Fig. 1. Intensity of elements in DBS extracts. Extraction was performed using different extraction buffers: Buffer 1: 0.5% HNO3 (v/v)/0.1% (v/v) Triton X-100) (white bars). Buffer 2: 5% HNO3 (v/v)/0.1% (v/v) Triton X-100) (grey bars). Buffer 3: 65% HNO3 (v/v)/ 0.1% (v/v) Triton X-100) (black bars). Intensities obtained from extraction buffer 1 were set to 100%, while results obtained with extraction buffers 2 and 3 are presented relative to this. Bars indicate mean intensity and CV% of six independent extractions of the same sample corrected for method blank (extracts from blank filter paper).
Please cite this article as: L. Pedersen, et al., Quantification of multiple elements in dried blood spot samples, Clin Biochem (2017), http:// dx.doi.org/10.1016/j.clinbiochem.2017.01.010
4
L. Pedersen et al. / Clinical Biochemistry xxx (2017) xxx–xxx
for Mn, As and Cd, where extraction with buffer 1 and 2 were equivalent (statistical non-significant), while extraction with buffer 1 were superior for Fe and Se (p b 0.001). Additionally, it proved more efficient to use two 3.2 mm discs pr. well than one 6.0 mm disc. 3.2. Method performance and calibration protocol The “on-paper” calibration curves provided a suitable linear response for most elements except for Cr, Mn, and Ni, probably due to very low analyte levels, relative high background signals and poor analytical recoveries. These elements were therefore excluded from further analysis. Standard curves for other elements were considered acceptable with r2 N 0.95. The imprecision (Table 1) was below 14% for all QC levels and all elements except at the lowest concentrations of Co and Pb, as they were lower than the limit of quantification (LoQ) defined as ten times the standard deviation of the blank filter paper concentration [12]. Results for accuracy and recovery are shown in Table 2. Spiking experiments with elements Na, K, Mg, Ca and Fe was not possible due to the natural high concentration of these elements in whole blood. 3.3. Signal contribution from blank filter paper and method limit of quantification The instrument limit of blank for each element, the method limit of blank and the LoD are shown in Table 3. Elements that showed the largest variability in blank filter paper were Fe, Pb, Cu, Ca and Cd with CV% in the range 44–162%. Mean element concentrations in blank filter paper in the range 2.5–20 mmol/L with the highest levels detected from Na, Mg, K, Ca and Fe. For calcium the mean contribution from the blank filter paper resulted in method LoD higher than the average clinical sample. 3.4. Comparison of element levels in DBS and whole blood Analysis of the concentrations in whole blood from volunteers, EQC samples and elemental spiked samples and matched DBS samples showed good correlations for most elements (Pearson's r2 = 0.90– 0.97). However, when the method comparison was performed using only the 17 matched samples from volunteers the correlations found were weak (Pearson's r2 = 0.19–0.72). Fig. 2 shows Bland-Altman comparisons of DBS Na, Mg, K, and Fe with plasma concentrations of Na, Mg, K and Fe. 3.5. Influence of hematocrit level on element concentration The variability across hematocrit levels determined by CV% was b15% for most elements; for elements K, Fe and Zn a higher hematocrit however resulted in higher element concentrations due to increased contribution of elements from erythrocytes with increasing hematocrit. As recently suggested [14] we examined the relationship between
Table 2 Accuracy of the DBS method based on analysis of EQC samples. Sample
Whole blood (EQC target)
DBS extract
Recovery (%)
Cu (μmol/L) TEQAS 2014:B19 TEQAS 2014:B20 QM-B-Q1404
21.0 21.2 22.0
25.7 22.9 21.5
122.0 108.3 97.8
Zn (μmol/L) TEQAS 2014:B19 TEQAS 2014:B20 QM-B-Q1404
6.5 9.2 81.1
7.4 10.4 95.7
113.7 112.5 118.0
Pb (μmol/L) NIST SRM L2 TEQAS13:B11 TEQAS14:B19 UTAK L2
1.22 1.18 0.33 1.96
1.48 1.31 0.37 1.86
121.5 111.3 111.6 95.1
Cd (nmol/L) TEQAS13:B02 TEQAS13:B11 UTAK L2
12.13 16.38 48.0
13.0 11.2 35.3
107.2 68.3 73.5
Se (μmol/L) TEQAS13:B04 TEQAS13:B11 UTAK L2
2.07 1.00 2.76
2.51 1.05 2.46
82.5 105.2 90.9
As (nmol/L) QM-B-Q1404 QM-B-Q1410
153 104
127.4 117.3
83.3 112.7
hematocrit, K and Fe, respectively, in a subset of samples, which gave the equation Hct (%) = (DBS-Fe (mmol/L) + 0.41) / 0.21. Applying this equation on another subset of samples achieved very good correlations between the theoretical and the measured hematocrit (Fig. 3a). Also, normalization of concentrations of K, Fe and Zn with the calculated hematocrit resulted in good correlations with Pearson's r2 = 0.90–0.97 (Fig. 3b). 4. Discussion We here present a method for extraction of elements Na, Mg, K, Fe, Co, Cu, Zn, As, Se, Cd and Pb from DBS and subsequently quantification by ICP-MS. The relatively small sample volume of two 3.2 mm punches per subject is a clear advantage in terms of optimal use of DBS material. For elements Na, Mg, K, Fe, Cu, Zn, Se good accuracy and acceptable imprecision data were obtained from the method validation. For elements Co, As, Cd and Pb the combined effect of background contamination and sample dilution makes the method unsuitable for toxicological screening. Comparison of element levels in whole blood and DBS extracts from capillary blood collected on filter paper showed a weak but significant linear relationship. There was no linear relationship between
Table 1 Method imprecision. Values are mean concentration ± SD (CV%). Intra-assay imprecision (n = 6)
Na (mmol/L) Mg (mmol/L) K (mmol/L) Fe (mmol/L) Co (nmol/L) Cu (μmol/L) Zn (μmol/L) As (nmol/L) Se (μmol/L) Cd (nmol/L) Pb (μmol/L)
Inter-assay imprecision (n = 18)
1
2
3
1
2
3
93 ± 5.6 (6.0) 0.79 ± 0.05 (6.3) 21.9 ± 1.2 (5.5) 16.8 ± 1.2 (7.1) 8.1 ± 2.4 (29.6) 22.9 ± 0.8 (3.4) 67.8 ± 3.9 (5.7) 59.1 ± 4.6 (7.8) 0.72 ± 9.7 (9.7) 19.5 ± 2.0 (10.3) 0.14 ± 0.03 (22.0)
87 ± 5.0 (5.7) 0.67 ± 0.03 (4.5) 18.7 ± 0.9 (4.6) 21.0 ± 0.9 (4.3) 17.2 ± 4.0 (23.2) 9.5 ± 0.5 (4.8) 80.9 ± (6.3) 111.8 ± 11.6 (10.4) 1.08 ± 0.07 (6.9) 83.0 ± 6.3 (7.6) 2.2 ± 0.08 (3.6)
128 ± 7.2 (5.6) 1.45 ± 0.1 (6.9) 39.6 ± 2.9 (7.3) 28.9 ± 1.1 (3.8) 122.9 ± 10.1 (8.2) 66.2 ± 3.4 (5.2) 301 ± 14.5 (4.8) 1366 ± 62.8 (4.6) 3.51 ± 0.4 (11.1) 106.2 ± 8.9 (8.4) 4.1 ± 0.1 (2.9)
96 ± 9.4 (9.8) 0.8 ± 0.07 (8.9) 27.0 ± 1.6 (5.8) 16.8 ± 1.4 (8.3) 7.9 ± 7.3 (93.0) 21.9 ± 1.9 (8.0) 68.6 ± 5.6 (8.1) 63.5 ± 8.6 (13.5) 0.76 ± 0.1 (13.2) 21.1 ± 2.7 (12.8) 0.12 ± 0.03 (24.0)
89 ± 8.3 (9.3) 0.75 ± 0.04 (5.4) 23.8 ± 1.9 (7.9) 19.6 ± 1.3 (6.6) 16.3 ± 4.8 (29.5) 9.9 ± 0.8 (8.0) 83.1 ± 8.2 (9.9) 117.3 ± 14.0 (11.9 1.0 ± 0.1 (14.0) 80.7 ± 10 (12.4) 2.1 ± 0.09 (4.2)
124 ± 10.4 (8.4) 1.47 ± 0.2 (12.9) 38.6 ± 3.1 (8.0) 28.3 ± 0.9 (5.0) 122.9 ± 13.4 (10.9) 66.6 ± 5.0 (7.7) 304.9 ± 21.3 (7.0) 1388 ± 80.5 (5.8) 3.39 ± 0.4 (12.9) 100.3 ± 13.4 (13.3) 4.1 ± 0.09 (2.2)
Please cite this article as: L. Pedersen, et al., Quantification of multiple elements in dried blood spot samples, Clin Biochem (2017), http:// dx.doi.org/10.1016/j.clinbiochem.2017.01.010
L. Pedersen et al. / Clinical Biochemistry xxx (2017) xxx–xxx
5
Table 3 Limit of blank, contribution of element signal from blank paper and method limit of blank, detection and quantification. Element
Meanreagent blank (n = 12)
SDreagent blank (n = 12)
LoBa
MeanDBSblank (n = 12)
SDDBSblank (n = 12)
Method LoBb
Method LoDc
Method LoQd
Samplese (n = 20)
Na (mmol/L) Mg (mmol/L) K (mmol/L) Ca (mmol/L) Fe (mmol/L) Co (nmol/L) Cu (μmol/L) Zn (μmol/L) As (nmol/L) Se (μmol/L) Cd (nmol/L) Pb (μmol/L)
0.056 0.057 0.0014 0.026 0.000058 0.75 0.0024 0.0013 0.3952 0.0008 0.0284 0.00026
1.15 0.0066 0.005 0.00014 0.000058 0.809 0.00167 0.00459 0.2499 0.00077 0.0269 0.00024
1.48 0.0679 0.0096 0.026 0.0001534 2.08 0.005173 0.008907 0.80649 0.002091 0.07285 0.0006616
20.0 0.40 0.41 0.69 0.008 4.14 0.30 2.29 19.5 0.17 2.5 0.05
1.7 0.03 0.046 0.38 0.013 1.40 0.25 0.24 3.6 0.04 1.1 0.04
22.8 0.45 0.49 1.32 0.029 6.40 0.71 2.68 25.4 0.24 4.31 0.12
25.6 0.50 0.56 1.94 0.051 8.70 1.12 3.08 31.4 0.30 6.12 0.18
37.0 0.70 10.87 4.49 0.14 18.2 2.80 4.69 55.5 0.57 13.5 0.45
134.6 1.0 25.7 b1.94 9.4 7.8 16.8 139.0 76.0 1.10 28.3 b0.18
a b c d e
LoB = meanreagent blank + 1.645(SDreagent blank), Ambruster and Pry, 2008 [13]. Method LoB = meanDBS blank + 1.645(SDDBS blank), Ambruster and Pry, 2008 [13]. Method LoD = LoBpaper + 1.645 (SDDBS blank), Ambruster and Pry, 2008 [13]. Method LoQ = meanDBS blank + 10(SDDBS blank), MacDougall et al., 1980 [12]. Mean concentration in DBS samples from test persons.
elements Na, Mg, K and Fe in plasma and the corresponding element concentration in DBS extracts from capillary blood collected on filter paper. Comparison of these elements in plasma and DBS extracts showed a concentration-dependent bias which most likely reflects that the DBS concentration is influenced by the erythrocyte concentration and hematocrit. Interestingly, measurement of K and Fe in DBS extracts seems capable to estimate sample hematocrit. We would like to address a few issues in this relation. To obtain good results, optimal extraction conditions are necessary. We evaluated the extraction conditions using 3.2 mm punches from DBS prepared with donor blood and blank unspotted paper. The results obtained from the DBS were corrected for those obtained from adjacent
blank filter paper punches. The efficiency of each extraction method was evaluated based on the conditions giving the highest signal after subtraction of intensity obtained from adjacent blank filter paper. Three different extraction buffers with increasing HNO3 concentration (0.5% HNO3 (v/v), 5% HNO3 (v/v) and 65% HNO3 (v/v)) + 0.1% Triton X-100 were tested, but for most elements the extraction efficiency were unaffected by buffer composition. We therefore believe that the extraction protocol suggested here gives the best quantification results. As samples are extracted and measured in a manner similar to the calibration standards, good comparability between unknown samples and standards are expected as long as the hematocrit in the calibration standards is close to the expected hematocrit of the samples. The
Fig. 2. Bland-Altman plots of plasma Na vs DBS Na; plasma Mg vs DBS Mg; plasma K vs DBS K; plasma Fe vs DBS Fe. Dotted lines indicate the average difference ± 1.96 standard deviation of the difference. Solid line accompanied by a dot-and-dash-line indicates regression line with 95% confidence intervals.
Please cite this article as: L. Pedersen, et al., Quantification of multiple elements in dried blood spot samples, Clin Biochem (2017), http:// dx.doi.org/10.1016/j.clinbiochem.2017.01.010
6
L. Pedersen et al. / Clinical Biochemistry xxx (2017) xxx–xxx
Fig. 3. A) (Top panels): regression analysis of measured potassium (K) and hematocrit and the corresponding regression analysis of the measured hematocrit and the calculated hematocrit (based on DBS measurements of K). B) (Bottom panels): regression analysis of measured iron (Fe) and hematocrit and the corresponding regression analysis of the measured hematocrit and the calculated hematocrit (based on DBS measurements of Fe).
hematocrit effect can be avoided by analyzing the entire DBS. This eliminates the variation from spreading and non-homogeneity [15]. However, unless a predefined volume of blood is spotted on the filter paper and the whole spot is analyzed, it is difficult to accurately quantify the original sample volume applied to the card. Application of accurate volumes of blood onto the DBS cards requires trained personal and a precision pipette and is not suitable when using for instance blood from heel pricks. However, whole blood hematocrit are directly proportional to blood viscosity and therefore affect the diffusion properties of blood spotted on filter paper [16]. A way to address this is to correct for the hematocrit value as previously suggested [14]. We also explored this using the fact that K and Fe concentrations measured in DBS extracts reflects the content in erythrocytes; since either RBC-K nor RBC-Fe are traditionally used in clinical evaluation, further studies are needed in order to evaluate the use DBS potassium and iron in a clinical context. But measurement of K or Fe in DBS by ICP-MS seems promising as a possible tool to calculate the hematocrit and could enable a correction of the hematocrit influence. However, further validation of the method using capillary blood is necessary in order assess the use of DBS-K or DBS-Fe from ICP-MS measurements to calculate sample hematocrit. For clinical purposes elements Na, Mg, K, and Fe are normally measured in the plasma phase. In the case of K and Fe the intracellular erythrocyte concentration is approximately 25–1000 times higher than in plasma [17]. As DBS sampling is based on drops of whole blood on filter paper and as the extraction procedure releases elements from erythrocytes, a much higher concentration of K and Fe is found in the DBS extracts compared to the corresponding plasma samples. The concentration of K and Fe in the DBS extracts is furthermore directly influenced by the sample hematocrit and therefore, a direct comparison between plasma and DBS concentrations cannot be made for these
two elements. DBS is a suitable matrix for establishing reference intervals for elements Na, Mg, K, Fe, Cu, Zn, and Se in DBS using ICP-MS. Reference ranges should however be established from hematocrit corrected values. Unfortunately, DBS seems to be an unsuitable matrix for establishing reference intervals using ICP-MS for elements Co, As, Cd and Pb (and calcium) due to high background signals from the filter paper. Our study has some strengths and limitations: Strengths include the small amount of DBS material per person required to obtain results for multiple elements enabling the rest of DBS to be used for other purposes. It is also an advantage that an estimate of sample hematocrit can be obtained in the same analytical run enabling correction of extreme hematocrit values or normalization of data. The study was limited to the use of Whatman 903 protein saver cards and Whatman Schleicher & Schuell 903, and different results may be obtained by using other types of DBS cards such as polyvinylidene difluoride (PVDF) membranes. Another limitation is the relative high sample volume required when using the 8–10 mL tubes required by the Cetac-ASX-520 autosampler and the simple peristaltic pump inlet system on the ICPMS. This causes a relative high dilution of the DBS extracts. Optimizing the method using an autosampler for microtiter plates racks with sample volumes as low as 500 μL could improve the sensitivity of the method. This method is limited by a relative high background signal from the filter paper for some elements. Using pre-cleaned for prospective sampling as suggested [7] may improve the method for heavy metals, but as the majority of DBS samples collected in biobanks are non-cleaned cards this method will only be suitable for future sample collection. In conclusion, we found good correlation between measurement in DBS and venous whole blood of the elements Mg, K, Fe, Cu, Zn, As and Se, while for Co, As, Cd and Pb the method was only precise and accurate
Please cite this article as: L. Pedersen, et al., Quantification of multiple elements in dried blood spot samples, Clin Biochem (2017), http:// dx.doi.org/10.1016/j.clinbiochem.2017.01.010
L. Pedersen et al. / Clinical Biochemistry xxx (2017) xxx–xxx
at toxic or elevated levels. Hematocrit however influenced the DBS element measurement, especially for K, Fe and Zn, but measurement of K and Fe in DBS extracts seems to enable sample hematocrit estimation. Appendix A. Supplementary data Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.clinbiochem.2017.01.010. References [1] R. Guthrie, A. Susi, A simple phenylalanine method for detecting phenylketonuria in large populations of newborn infants, Pediatrics 32 (1963) 338–343. [2] P.M. De Kesel, N. Sadones, S. Capiau, W.E. Lambert, C.P. Stove, Hemato-critical issues in quantitative analysis of dried blood spots: challenges and solutions, Bioanalysis 5 (2013) 2023–2041. [3] J. Henion, R.V. Oliveira, D.H. Chace, Microsample analyses via DBS: challenges and opportunities, Bioanalysis 5 (2013) 2547–2565. [4] W.E. Funk, J.K. McGee, A.F. Olshan, A.J. Ghio, Quantification of arsenic, lead, mercury and cadmium in newborn dried blood spots, Biomarkers 18 (2013) 174–177. [5] E.K. Langer, K.J. Johnson, M.M. Shafer, P. Gorski, J. Overdier, J. Musselman, J.A. Ross, Characterization of the elemental composition of newborn blood spots using sector-field inductively coupled plasma-mass spectrometry, J. Expo. Sci. Environ. Epidemiol. 21 (2011) 355–364. [6] V. Vacchina, V. Huin, S. Hulo, D. Cuny, F. Broly, G. Renom, J.M. Perini, Use of dried blood spots and inductively coupled plasma mass spectrometry for multi-element determination in blood, J. Trace Elem. Med. Biol. 28 (2014) 255–259.
7
[7] W.E. Funk, J.D. Pleil, D.J. Sauter, T.W. McDade, J.L. Holl, Use of dried blood spots for estimating children's exposures to heavy metals in epidemiological research, J. Environ. Anal. Toxicol. S7 (2015) 002. [8] P.M. Edelbroek, J. van der Heijden, L.M. Stolk, Dried blood spot methods in therapeutic drug monitoring: methods, assays, and pitfalls, Ther. Drug Monit. 31 (2009) 327–336. [9] J.V. Mei, J.R. Alexander, B.W. Adam, W.H. Hannon, Use of filter paper for the collection and analysis of human whole blood specimens, J. Nutr. 131 (2001) 1631S–1636S. [10] M. O'Mara, B. Hudson-Curtis, K. Olson, Y. Yueh, J. Dunn, N. Spooner, The effect of hematocrit and punch location on assay bias during quantitative bioanalysis of dried blood spot samples, Bioanalysis 3 (2011) 2335–2347. [11] H.W. Vesper, W.G. Miller, G.L. Myers, Reference materials and commutability, Clin. Biochem. Rev. 28 (2007) 139–147. [12] D. MacDougall, W.B. Crummett, F. Amore, G. Cox, D.G. Crosby, T. Abeku, et al., Guidelines for data acquisition and data quality evaluation in environmental chemistry, Anal. Chem. 52 (1980) 2242–2249. [13] D.A. Armbruster, T. Pry, Limit of blank, limit of detection and limit of quantitation, Clin. Biochem. Rev. 29 (Suppl. 1) (2008) S49–S52. [14] S. Capiau, V.V. Stove, W.E. Lambert, C.P. Stove, Prediction of the hematocrit of dried blood spots via potassium measurement on a routine clinical chemistry analyzer, Anal. Chem. 85 (2013) 404–410. [15] L. Fan, J.A. Lee, Managing the effect of hematocrit on DBS analysis in a regulated environment, Bioanalysis 4 (2012) 345–347. [16] A.R. Pries, D. Neuhaus, P. Gaehtgens, Blood viscosity in tube flow: dependence on diameter and hematocrit, Am. J. Phys. 263 (1992) H1770–H1778. [17] J.M. Harrington, D.J. Young, A.S. Essader, S.J. Sumner, K.E. Levine, Analysis of human serum and whole blood for mineral content by ICP-MS and ICP-OES: development of a mineralomics method, Biol. Trace Elem. Res. 160 (2014) 132–142.
Please cite this article as: L. Pedersen, et al., Quantification of multiple elements in dried blood spot samples, Clin Biochem (2017), http:// dx.doi.org/10.1016/j.clinbiochem.2017.01.010
Contents lists available at ScienceDirect
Clinical Biochemistry journal homepage: www.elsevier.com/locate/clinbiochem
Quantification of multiple elements in dried blood spot samples Lise Pedersen a, Karen Andersen-Ranberg b,e, Mads Hollergaard c, Mads Nybo d,⁎ a
Department of Clinical Biochemistry, Holbæk Hospital, Holbæk, Denmark Danish Ageing Research Center (DARC), University of Southern Denmark (SDU), Odense, Denmark c Danish National Neonatal Screening Biobank, Statens Serum Institute (SSI), Copenhagen, Denmark d Department of Clinical Biochemistry and Pharmacology, Odense University Hospital, Odense, Denmark e SHARE (Survey of Health, Ageing and Retirement in Europe), Denmark b
a r t i c l e
i n f o
Article history: Received 21 October 2016 Received in revised form 19 January 2017 Accepted 19 January 2017 Available online xxxx Keywords: Dried blood spots Elements Hematocrit ICP-MS Method validation
a b s t r a c t Background: Dried blood spots (DBS) is a unique matrix that offers advantages compared to conventional blood collection making it increasingly popular in large population studies. We here describe development and validation of a method to determine multiple elements in DBS. Methods: Elements were extracted from punches and analyzed using inductively coupled plasma-mass spectrometry (ICP-MS). The method was evaluated with quality controls with defined element concentration and blood spiked with elements to assess accuracy and imprecision. DBS element concentrations were compared with concentrations in venous blood. Samples with different hematocrit were spotted onto filter paper to assess hematocrit effect. Results: The established method was precise and accurate for measurement of most elements in DBS. There was a significant but relatively weak correlation between measurement of the elements Mg, K, Fe, Cu, Zn, As and Se in DBS and venous whole blood. Hematocrit influenced the DBS element measurement, especially for K, Fe and Zn. Conclusion: Trace elements can be measured with high accuracy and low imprecision in DBS, but contribution of signal from the filter paper influences measurement of some elements present at low concentrations. Simultaneous measurement of K and Fe in DBS extracts may be used to estimate sample hematocrit. © 2017 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.
1. Introduction Dried blood spots (DBS) are spots of capillary blood from a finger prick dripped onto filter paper, dried and then used for laboratory testing. DBS are commonly used in newborn screening for inborn errors of metabolism and in therapeutic drug monitoring [1], but has become increasingly popular as a sample matrix for biomarkers in population studies as they are easy to obtain, easy to transport, and allows collection in the field with a high response rate. To this can be added that collection of DBS are quick, relatively painless, less invasive than venipuncture and requires minimal field storage capacity. However, the number of validated assays for quantifying biomarkers in DBS samples is still relatively low compared with traditional whole blood, serum or plasma matrices. Reasons for this is the variety of challenges associated with analysis of DBS, e.g. contamination risk, blood spot heterogeneity, hematocrit effect and analyte on-card stability [2,3]. The sample volume is small (5 drops of blood on each card, i.e. approximately 275–375 μL) compared to conventional venipuncture (typical 5 mL of whole blood), and in many population studies and biobanks of e.g. ⁎ Corresponding author at: Dept. of Clinical Biochemistry and Pharmacology, Odense University Hospital, Sdr. Boulevard 29, DK-5000 Odense, Denmark. E-mail address: [email protected] (M. Nybo).
neonatal blood spots collected at birth only one card is obtained per subject. Consequently, samples for analysis are often as small as 3– 6 mm punches making the available volume of blood as small as 2– 5 μL, which is a challenge in terms of obtaining a sufficient recovery and analyte signal. For some analytical techniques analytes can be quantified or detected directly from DBS punches. However, for the majority of routine analytes, pharmaceutical substances and elements (metals and non-metals) it is necessary to develop an extraction protocol that ensures good recovery rates, minimizes the background contamination from the filter paper and is suitable for the analyte of interest. The ideal procedure enables extraction of a maximum number of analytes from the same punch allowing the remainder of the card to be used for other purposes. Recent development in high-sensitive element analyzers like inductively coupled plasma mass spectrometry (ICP-MS) instruments provides simultaneous measurement of multiple elements at very low concentrations. However, to utilize the ICP-MS technology elements must be extracted from the filter paper, which introduces a dilution factor and a potential loss of sensitivity. Methods for quantification of elements in DBS by ICP-MS have previously been reported [4–7]. These methods all used one-half or a whole intact dried spot with a diameter of 8–13 mm corresponding to a starting blood volume of 20–40 μL blood, and the filter paper was weighed to estimate the amount of blood in each sample.
http://dx.doi.org/10.1016/j.clinbiochem.2017.01.010 0009-9120/© 2017 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.
Please cite this article as: L. Pedersen, et al., Quantification of multiple elements in dried blood spot samples, Clin Biochem (2017), http:// dx.doi.org/10.1016/j.clinbiochem.2017.01.010
2
L. Pedersen et al. / Clinical Biochemistry xxx (2017) xxx–xxx
Our objective was to develop a method for determination of multiple elements in DBS samples using the smallest possible sample amount with fast throughput and a quality comparable to whole blood and plasma methods. This paper describes the development and validation of a protocol for extraction of a range of elements from two 3.2 mm punches and subsequent quantification by ICP-MS using matrix-matched calibrators. 2. Materials and methods For comparative analysis element concentrations of Co, Cu, Zn, As, Se, Cd and Pb were compared in a set of 17 matched whole blood samples and capillary blood collected on DBS filter paper, while Na, K and Fe were compared in a set of plasma samples and capillary blood collected on DBS filter paper. Element levels were also compared in matched DBS, whole blood QC samples and samples spiked with elements in order to cover a broader concentration range. 2.1. Subjects and samples Dried blood spots and venous blood were collected from adult volunteers and approved by The Regional Ethical Committee in Southern Denmark. Capillary blood was obtained from the participant's finger using a microtainer contact-activated lancet (Becton Dickinson, New Jersey, USA), and drops of blood were collected on Whatman 903 protein saver cards (GE Healthcare, Little Chalfont, UK) to fill all five discs. Each card was dried overnight at room temperature and thereafter stored separately in a Zip-Lock® bag with a desiccant at − 20 °C for three months until analysis. Prior to analysis, DBS cards were thawed at room temperature and 3.2 mm punches were produced by a semi-automatic DBS puncher (Perkin Elmer, Waltham, MA, USA). Venous blood was collected by antecubital venipuncture in metalfree tubes containing EDTA (Vacutainer Royal Blue, Becton Dickinson) or Li-heparin (Vacutainer Green, Becton Dickinson). For collection of plasma, whole blood samples were centrifuged at 3600g for 10 min at 4 °C, and aliquots of whole blood and plasma were stored at − 20 °C for three months until analysis. For method validation, 75 μL venous EDTA whole blood or whole blood spiked with elemental standard solutions was applied with a precision pipette on the Whatman cards. Quality control (QC) cards were prepared applying 75 μL whole blood QC materials from Sero (Billingstad, Norway), UTAK (Valencia, CA, USA), QMEQAS (Centre de Toxicologie, Quebéc, Canada) and UK NEQAS (Trace elements program, UK NEQAS, Sheffield, UK), respectively, on DBS cards. 2.2. Preparation of DBS samples with different hematocrit Seven portions of whole blood with hematocrit values between 22.5 and 79.1% were prepared from a single batch of packed washed erythrocytes and a single batch of plasma as described in NBS01-A6 CLSI standard, Appendix C3. The hematocrit value in each portion was measured on a Sysmex XN10 before aliquots of 75 μL were spotted onto filter paper as described. Element concentrations were measured in three replicates from DBS extracts at each hematocrit level. 2.3. Reagents and utensils Nitric acid 65%, Triton™ X-100 and Tracecert multi-trace elemental and single trace element standards for ICP-MS analysis were purchased from Sigma-Aldrich (St. Louis, MO, USA). Seronorm™ Certified Reference Materials (CRMs) were obtained from Sero (Billingstad, Norway). UTAK whole blood and serum QC were obtained from UTAK (Valencia, CA, USA). CRM for toxic metals in bovine blood was obtained from NIST (Gaithersburg, Maryland, USA), while whole blood external quality control (EQC) samples containing a range of elements in human
biological matrices were obtained from CTQ (QMEQAS program, Centre de Toxicologie, Quebéc, Canada) or from UK NEQAS (Trace elements program, UK NEQAS, Sheffield, UK). XN Check hematology control blood was obtained from Sysmex (Kobe, Japan). Ultrapure water (N 18 MΩ cm) from a Milli-Q system (Millipore, Bedford, MA, USA) was used for preparation of all buffers and standards. Clear polystyrene 96-wells flat bottom plates (NUNC, catalogue 439,454) and 12 mL MiniSorp™ tubes (NUNC, catalogue 468,608) was obtained from Thermo Fisher (Waltham, MA, USA). Three different lots of Whatman 903 protein saver cards were included in the method validation: Lots 6833909W082, 6912111W111, and 7018515W141. 2.4. Contamination control All handling of samples were performed in a dedicated trace element-clean laboratory. DBS were handled with gloved hands under a laminar flow, except during punching with the semi-automatic puncher. All plastic materials in contact with DBS (tubes, plates, tips) were decontaminated with a 5% HNO3 (v/v) solution overnight and dried under a laminar flow prior to use. 2.5. Instrumentation and ICP-MS conditions Analysis of isotopes 23Na, 24Mg, 39K, 44Ca, 52Cr, 56Fe, 55Mn, 58Ni, 59Co, Cu, 64Zn, 75As 78Se,114Cd and 208Pb in dried blood extracts and whole blood was performed on a iCAP-Qc ICP-MS (Thermo Fisher, Winsford, UK) equipped with collision cell technology with kinetic energy discrimination (CCTED). A flow of helium with a purity of N 99.999% (Strandmøllen, Ejby, Denmark) was introduced into the collision cell. Sample introduction was performed with a PFA-ST microflow nebulizer combined with a quartz cyclonic spray chamber (Trace elemental scientific, Omaha, NE, USA) in all instances. For automation of the analyses the ICP-MS was equipped with a Cetac ASX-520 autosampler (Cetac Technologies, Omaha, NE, USA). Conditions were daily optimized to obtain the highest signal-to-background ratio for 7Li, 59Co, 115In, 137Ba and 238 U along with the ratio of 140Ce16O +/140Ce+ b 2% for a solution of 1 μg/L of each trace element (Thermo Scientific, Tune B solution). Sample data were acquired in counts per second with three replicate readings and a dwell time of 50 ms. To overcome potential polyatomic interferences (such as 35Cl17O on 52 Cr, 35 Cl40Ar on 75As and 40Ar40Ar on 80Se) three approaches were employed: 1) if possible, selection of interference-free isotopes for analysis; 2) use of collision cell technology; or 3) use of an equation to correct for interferences. Collision cell technology was applied to elements 23 Na, 24Mg, 39K, 44Ca, 52Cr, 56Fe, 59Co, and 78Se. For selenium the less abundant isotope 78Se was measured in order to avoid interference of the 40Ar2+ dimer from the argon plasma instead of the most abundant isotope of selenium (80Se). Mathematical correction was applied to measurement of 78Se by the equation: I(78Se)-0.03461 I(83Kr). To compensate for uptake variation and analytical drift on the ICP-MS 71Ga (collision cell mode) and 208Bi (without collision cell) were added as internal standard in all tubes prior to analysis. Data were analyzed using the Qtegra™ software (version 2.2.1465.24) from Thermo Scientific (Winsford, UK). The hematocrit value in whole blood samples were measured on a Sysmex XN10 (Sysmex, Kobe, Japan), while plasma concentrations of Na, Mg, K and Fe were measured on an Architect c8000 (Abbott Laboratories, Illinois, USA). 63
2.6. Calibration and standards In order to maximize comparability between calibrators and unknown samples calibrators were by elemental spiking of a pool of artificial control blood that were deposited with 75 μL on “calibration cards” to be punched and extracted in a manner similar to unknown samples. By treating calibrators and samples in the same manner it is possible to
Please cite this article as: L. Pedersen, et al., Quantification of multiple elements in dried blood spot samples, Clin Biochem (2017), http:// dx.doi.org/10.1016/j.clinbiochem.2017.01.010
L. Pedersen et al. / Clinical Biochemistry xxx (2017) xxx–xxx
avoid additional quantification steps like weighing of the filer paper in order to estimate the total blood volume or determination of a dilution factor between calibrators and DBS extracts. However, the amount of blood in the punches may depend on hematocrit since a fixed punch size is used, and the actual sample size can therefore differ at abnormally low and high hematocrit values [8, 9]. In addition, some compounds may show a chromatographic effect with a higher concentration in a center punch relative to a peripheral punch [10]. The influence of both hematocrit and within-spot variation was therefore included in the method validation. To obtain calibrators with a hematocrit value comparable to patient samples an artificial blood pool was made mixing the XN Check level 3 hematology control (with defined hematocrit value) with a whole blood trace element control (Seronorm™ L-3). Further addition of ICP-MS multi trace element standard solution 4 in increasing amounts were used to create a 5point calibration curve for the trace elements As, Se and Cd. Addition of single element standards in increasing amounts were used to create a 5-point calibration curve used for Mg, Ca, Cu, Zn and Pb. For a calibration point with element concentrations between reagent blank and the pool, a two-fold dilution was prepared with Milli-Q water. As element concentrations of Na, K and Fe in whole blood samples requires predilution to obtain levels comparable to DBS extracts, a calibration curve for Na, K and Fe was constructed by serial dilution of the artificial blood pool starting with a 5-fold and ending in a 100-fold dilution prior to application. Dilution of the artificial blood pool lowered the hematocrit value and caused the samples to spread differently compared to whole blood samples, which could cause non-commutability between calibrator and samples [11]. Traceability of each element level in each calibrator point were verified by parallel analysis against independent whole blood QC standards with elemental “target” values from NEQAS for Trace elements (Surrey, UK) and QMEQAS (CTQ, Quebec, Canada). For elements K and Fe the levels in the calibrators were verified with QC Autonorm™ Human Liquid L-1 and L-2 from SERO (Billingstad, Norway) and with samples from KS-Clinical Chemistry in serum “wet chemistry” from Ringversuche (Referenzinstitut für Bioanalytik, Bonn, Germany). Aliquots of each calibrator point were stored at −20 °C. All “calibration cards” were freshly prepared the day before analysis on Whatman cards by applying 75 μL of each calibrator point to each of the five discs, where-after cards were allowed to dry overnight in a laminar flow bench prior to use. In each analytical run all intensities were corrected by subtraction of the mean intensity from three method blanks (signal from blank filter paper extract).
3
limits of blank (LoB), detection (LoD) and quantification (LoQ), respectively, and the hematocrit effect. Validation furthermore included unique DBS parameters such as signal contribution from blank filter paper from different lots, hematocrit effect and within-spot variation. The LoB for each isotope was determined from measurement of reagent blank (ICP-MS running buffer) in several analytical runs. The method LoB and LoD was defined as meanblank filter paper + (1645 ∗ sdblank filter paper) and LoB + (1645 ∗ sdblank filter paper), respectively [9]. The LoQ was defined as ten times the standard deviation of the blank filter paper concentration [16]. Imprecision was determined using six replicates of each of three QC levels, which were extracted and run against a standard curve as described. This was repeated in three separate runs to determine intra- and inter-assay imprecision (% coefficient of variation (CV%)). As punches were taken within the same spot as well as between spots of the same QC sample, intra- and inter-assay imprecision encompasses within- and between-spot variation. For evaluation of accuracy (% bias) two different approaches were used: 1) Whole blood samples of CRM or samples from EQC programs with target values were spotted on filter paper as described. The blood was then extracted and measured on the ICP-MS in three runs. 2.9. Statistical analysis ANOVA, Mann Whitney U test, linear regression analysis and BlandAltman analysis were all performed using GraphPad Prism version 5.00 (GraphPad Software, San Diego, California, USA). 3. Results 3.1. Extraction procedure As shown in Fig. 1, the signal for elements Fe and Se was considerably better using the extraction buffer with the lowest acid concentration (0.5% HNO3), which was also seen by the red coloration of DBS extracts when the lowest acid concentration was used (not shown). Increasing extraction time or temperature did not optimize element signals (not shown), but two subsequent extraction steps with respectively 100 μL gave a better yield than a single extraction step with 200 μL for 2 h. ANOVA analysis revealed that the three extraction procedures differed for all elements (p b 0.05). Mann-Whitney U test comparing two extractions showed that extraction using buffer 2 gave significantly superior extraction result (p b 0.05) for all elements except
2.7. Extraction protocol for ICP-MS analysis All analyses were performed using two 3.2 mm (diameter) DBS filter paper discs punched out with a semi-automatic DBS puncher (Perkin Elmer 1296) and placed in a 96-well plate before extraction of elements and subsequent analysis. The optimal extraction protocol encompassed two extraction steps: Extraction step 1 was performed by adding 100 μL of extraction buffer to each well followed by shaking on an orbital shaker (Wallac Delfia Plate Shaker 1296-001) at 1350 rpm for 1 h. As liquid is absorbed into the dry filter paper it was only possible to transfer 75 μL extract from each well to clean 10 mL polyethylene tubes (MiniSorp, Nunc, Denmark) containing 1 mL ICP-MS running buffer. In extraction step 2, additionally 100 μL of extraction buffer was added to each well and shaking was performed for an hour on the orbital shaker. From step 2 75 μL of extract were transferred to the MiniSorp tubes. Prior to analysis MiniSorp tubes were centrifuged at 2000 g for 10 min to avoid unintentional transfer of paper debris or undigested material. 2.8. Method validation Validation of the method was carried out to determine performance, which comprised precision in series, accuracy, method comparison,
Fig. 1. Intensity of elements in DBS extracts. Extraction was performed using different extraction buffers: Buffer 1: 0.5% HNO3 (v/v)/0.1% (v/v) Triton X-100) (white bars). Buffer 2: 5% HNO3 (v/v)/0.1% (v/v) Triton X-100) (grey bars). Buffer 3: 65% HNO3 (v/v)/ 0.1% (v/v) Triton X-100) (black bars). Intensities obtained from extraction buffer 1 were set to 100%, while results obtained with extraction buffers 2 and 3 are presented relative to this. Bars indicate mean intensity and CV% of six independent extractions of the same sample corrected for method blank (extracts from blank filter paper).
Please cite this article as: L. Pedersen, et al., Quantification of multiple elements in dried blood spot samples, Clin Biochem (2017), http:// dx.doi.org/10.1016/j.clinbiochem.2017.01.010
4
L. Pedersen et al. / Clinical Biochemistry xxx (2017) xxx–xxx
for Mn, As and Cd, where extraction with buffer 1 and 2 were equivalent (statistical non-significant), while extraction with buffer 1 were superior for Fe and Se (p b 0.001). Additionally, it proved more efficient to use two 3.2 mm discs pr. well than one 6.0 mm disc. 3.2. Method performance and calibration protocol The “on-paper” calibration curves provided a suitable linear response for most elements except for Cr, Mn, and Ni, probably due to very low analyte levels, relative high background signals and poor analytical recoveries. These elements were therefore excluded from further analysis. Standard curves for other elements were considered acceptable with r2 N 0.95. The imprecision (Table 1) was below 14% for all QC levels and all elements except at the lowest concentrations of Co and Pb, as they were lower than the limit of quantification (LoQ) defined as ten times the standard deviation of the blank filter paper concentration [12]. Results for accuracy and recovery are shown in Table 2. Spiking experiments with elements Na, K, Mg, Ca and Fe was not possible due to the natural high concentration of these elements in whole blood. 3.3. Signal contribution from blank filter paper and method limit of quantification The instrument limit of blank for each element, the method limit of blank and the LoD are shown in Table 3. Elements that showed the largest variability in blank filter paper were Fe, Pb, Cu, Ca and Cd with CV% in the range 44–162%. Mean element concentrations in blank filter paper in the range 2.5–20 mmol/L with the highest levels detected from Na, Mg, K, Ca and Fe. For calcium the mean contribution from the blank filter paper resulted in method LoD higher than the average clinical sample. 3.4. Comparison of element levels in DBS and whole blood Analysis of the concentrations in whole blood from volunteers, EQC samples and elemental spiked samples and matched DBS samples showed good correlations for most elements (Pearson's r2 = 0.90– 0.97). However, when the method comparison was performed using only the 17 matched samples from volunteers the correlations found were weak (Pearson's r2 = 0.19–0.72). Fig. 2 shows Bland-Altman comparisons of DBS Na, Mg, K, and Fe with plasma concentrations of Na, Mg, K and Fe. 3.5. Influence of hematocrit level on element concentration The variability across hematocrit levels determined by CV% was b15% for most elements; for elements K, Fe and Zn a higher hematocrit however resulted in higher element concentrations due to increased contribution of elements from erythrocytes with increasing hematocrit. As recently suggested [14] we examined the relationship between
Table 2 Accuracy of the DBS method based on analysis of EQC samples. Sample
Whole blood (EQC target)
DBS extract
Recovery (%)
Cu (μmol/L) TEQAS 2014:B19 TEQAS 2014:B20 QM-B-Q1404
21.0 21.2 22.0
25.7 22.9 21.5
122.0 108.3 97.8
Zn (μmol/L) TEQAS 2014:B19 TEQAS 2014:B20 QM-B-Q1404
6.5 9.2 81.1
7.4 10.4 95.7
113.7 112.5 118.0
Pb (μmol/L) NIST SRM L2 TEQAS13:B11 TEQAS14:B19 UTAK L2
1.22 1.18 0.33 1.96
1.48 1.31 0.37 1.86
121.5 111.3 111.6 95.1
Cd (nmol/L) TEQAS13:B02 TEQAS13:B11 UTAK L2
12.13 16.38 48.0
13.0 11.2 35.3
107.2 68.3 73.5
Se (μmol/L) TEQAS13:B04 TEQAS13:B11 UTAK L2
2.07 1.00 2.76
2.51 1.05 2.46
82.5 105.2 90.9
As (nmol/L) QM-B-Q1404 QM-B-Q1410
153 104
127.4 117.3
83.3 112.7
hematocrit, K and Fe, respectively, in a subset of samples, which gave the equation Hct (%) = (DBS-Fe (mmol/L) + 0.41) / 0.21. Applying this equation on another subset of samples achieved very good correlations between the theoretical and the measured hematocrit (Fig. 3a). Also, normalization of concentrations of K, Fe and Zn with the calculated hematocrit resulted in good correlations with Pearson's r2 = 0.90–0.97 (Fig. 3b). 4. Discussion We here present a method for extraction of elements Na, Mg, K, Fe, Co, Cu, Zn, As, Se, Cd and Pb from DBS and subsequently quantification by ICP-MS. The relatively small sample volume of two 3.2 mm punches per subject is a clear advantage in terms of optimal use of DBS material. For elements Na, Mg, K, Fe, Cu, Zn, Se good accuracy and acceptable imprecision data were obtained from the method validation. For elements Co, As, Cd and Pb the combined effect of background contamination and sample dilution makes the method unsuitable for toxicological screening. Comparison of element levels in whole blood and DBS extracts from capillary blood collected on filter paper showed a weak but significant linear relationship. There was no linear relationship between
Table 1 Method imprecision. Values are mean concentration ± SD (CV%). Intra-assay imprecision (n = 6)
Na (mmol/L) Mg (mmol/L) K (mmol/L) Fe (mmol/L) Co (nmol/L) Cu (μmol/L) Zn (μmol/L) As (nmol/L) Se (μmol/L) Cd (nmol/L) Pb (μmol/L)
Inter-assay imprecision (n = 18)
1
2
3
1
2
3
93 ± 5.6 (6.0) 0.79 ± 0.05 (6.3) 21.9 ± 1.2 (5.5) 16.8 ± 1.2 (7.1) 8.1 ± 2.4 (29.6) 22.9 ± 0.8 (3.4) 67.8 ± 3.9 (5.7) 59.1 ± 4.6 (7.8) 0.72 ± 9.7 (9.7) 19.5 ± 2.0 (10.3) 0.14 ± 0.03 (22.0)
87 ± 5.0 (5.7) 0.67 ± 0.03 (4.5) 18.7 ± 0.9 (4.6) 21.0 ± 0.9 (4.3) 17.2 ± 4.0 (23.2) 9.5 ± 0.5 (4.8) 80.9 ± (6.3) 111.8 ± 11.6 (10.4) 1.08 ± 0.07 (6.9) 83.0 ± 6.3 (7.6) 2.2 ± 0.08 (3.6)
128 ± 7.2 (5.6) 1.45 ± 0.1 (6.9) 39.6 ± 2.9 (7.3) 28.9 ± 1.1 (3.8) 122.9 ± 10.1 (8.2) 66.2 ± 3.4 (5.2) 301 ± 14.5 (4.8) 1366 ± 62.8 (4.6) 3.51 ± 0.4 (11.1) 106.2 ± 8.9 (8.4) 4.1 ± 0.1 (2.9)
96 ± 9.4 (9.8) 0.8 ± 0.07 (8.9) 27.0 ± 1.6 (5.8) 16.8 ± 1.4 (8.3) 7.9 ± 7.3 (93.0) 21.9 ± 1.9 (8.0) 68.6 ± 5.6 (8.1) 63.5 ± 8.6 (13.5) 0.76 ± 0.1 (13.2) 21.1 ± 2.7 (12.8) 0.12 ± 0.03 (24.0)
89 ± 8.3 (9.3) 0.75 ± 0.04 (5.4) 23.8 ± 1.9 (7.9) 19.6 ± 1.3 (6.6) 16.3 ± 4.8 (29.5) 9.9 ± 0.8 (8.0) 83.1 ± 8.2 (9.9) 117.3 ± 14.0 (11.9 1.0 ± 0.1 (14.0) 80.7 ± 10 (12.4) 2.1 ± 0.09 (4.2)
124 ± 10.4 (8.4) 1.47 ± 0.2 (12.9) 38.6 ± 3.1 (8.0) 28.3 ± 0.9 (5.0) 122.9 ± 13.4 (10.9) 66.6 ± 5.0 (7.7) 304.9 ± 21.3 (7.0) 1388 ± 80.5 (5.8) 3.39 ± 0.4 (12.9) 100.3 ± 13.4 (13.3) 4.1 ± 0.09 (2.2)
Please cite this article as: L. Pedersen, et al., Quantification of multiple elements in dried blood spot samples, Clin Biochem (2017), http:// dx.doi.org/10.1016/j.clinbiochem.2017.01.010
L. Pedersen et al. / Clinical Biochemistry xxx (2017) xxx–xxx
5
Table 3 Limit of blank, contribution of element signal from blank paper and method limit of blank, detection and quantification. Element
Meanreagent blank (n = 12)
SDreagent blank (n = 12)
LoBa
MeanDBSblank (n = 12)
SDDBSblank (n = 12)
Method LoBb
Method LoDc
Method LoQd
Samplese (n = 20)
Na (mmol/L) Mg (mmol/L) K (mmol/L) Ca (mmol/L) Fe (mmol/L) Co (nmol/L) Cu (μmol/L) Zn (μmol/L) As (nmol/L) Se (μmol/L) Cd (nmol/L) Pb (μmol/L)
0.056 0.057 0.0014 0.026 0.000058 0.75 0.0024 0.0013 0.3952 0.0008 0.0284 0.00026
1.15 0.0066 0.005 0.00014 0.000058 0.809 0.00167 0.00459 0.2499 0.00077 0.0269 0.00024
1.48 0.0679 0.0096 0.026 0.0001534 2.08 0.005173 0.008907 0.80649 0.002091 0.07285 0.0006616
20.0 0.40 0.41 0.69 0.008 4.14 0.30 2.29 19.5 0.17 2.5 0.05
1.7 0.03 0.046 0.38 0.013 1.40 0.25 0.24 3.6 0.04 1.1 0.04
22.8 0.45 0.49 1.32 0.029 6.40 0.71 2.68 25.4 0.24 4.31 0.12
25.6 0.50 0.56 1.94 0.051 8.70 1.12 3.08 31.4 0.30 6.12 0.18
37.0 0.70 10.87 4.49 0.14 18.2 2.80 4.69 55.5 0.57 13.5 0.45
134.6 1.0 25.7 b1.94 9.4 7.8 16.8 139.0 76.0 1.10 28.3 b0.18
a b c d e
LoB = meanreagent blank + 1.645(SDreagent blank), Ambruster and Pry, 2008 [13]. Method LoB = meanDBS blank + 1.645(SDDBS blank), Ambruster and Pry, 2008 [13]. Method LoD = LoBpaper + 1.645 (SDDBS blank), Ambruster and Pry, 2008 [13]. Method LoQ = meanDBS blank + 10(SDDBS blank), MacDougall et al., 1980 [12]. Mean concentration in DBS samples from test persons.
elements Na, Mg, K and Fe in plasma and the corresponding element concentration in DBS extracts from capillary blood collected on filter paper. Comparison of these elements in plasma and DBS extracts showed a concentration-dependent bias which most likely reflects that the DBS concentration is influenced by the erythrocyte concentration and hematocrit. Interestingly, measurement of K and Fe in DBS extracts seems capable to estimate sample hematocrit. We would like to address a few issues in this relation. To obtain good results, optimal extraction conditions are necessary. We evaluated the extraction conditions using 3.2 mm punches from DBS prepared with donor blood and blank unspotted paper. The results obtained from the DBS were corrected for those obtained from adjacent
blank filter paper punches. The efficiency of each extraction method was evaluated based on the conditions giving the highest signal after subtraction of intensity obtained from adjacent blank filter paper. Three different extraction buffers with increasing HNO3 concentration (0.5% HNO3 (v/v), 5% HNO3 (v/v) and 65% HNO3 (v/v)) + 0.1% Triton X-100 were tested, but for most elements the extraction efficiency were unaffected by buffer composition. We therefore believe that the extraction protocol suggested here gives the best quantification results. As samples are extracted and measured in a manner similar to the calibration standards, good comparability between unknown samples and standards are expected as long as the hematocrit in the calibration standards is close to the expected hematocrit of the samples. The
Fig. 2. Bland-Altman plots of plasma Na vs DBS Na; plasma Mg vs DBS Mg; plasma K vs DBS K; plasma Fe vs DBS Fe. Dotted lines indicate the average difference ± 1.96 standard deviation of the difference. Solid line accompanied by a dot-and-dash-line indicates regression line with 95% confidence intervals.
Please cite this article as: L. Pedersen, et al., Quantification of multiple elements in dried blood spot samples, Clin Biochem (2017), http:// dx.doi.org/10.1016/j.clinbiochem.2017.01.010
6
L. Pedersen et al. / Clinical Biochemistry xxx (2017) xxx–xxx
Fig. 3. A) (Top panels): regression analysis of measured potassium (K) and hematocrit and the corresponding regression analysis of the measured hematocrit and the calculated hematocrit (based on DBS measurements of K). B) (Bottom panels): regression analysis of measured iron (Fe) and hematocrit and the corresponding regression analysis of the measured hematocrit and the calculated hematocrit (based on DBS measurements of Fe).
hematocrit effect can be avoided by analyzing the entire DBS. This eliminates the variation from spreading and non-homogeneity [15]. However, unless a predefined volume of blood is spotted on the filter paper and the whole spot is analyzed, it is difficult to accurately quantify the original sample volume applied to the card. Application of accurate volumes of blood onto the DBS cards requires trained personal and a precision pipette and is not suitable when using for instance blood from heel pricks. However, whole blood hematocrit are directly proportional to blood viscosity and therefore affect the diffusion properties of blood spotted on filter paper [16]. A way to address this is to correct for the hematocrit value as previously suggested [14]. We also explored this using the fact that K and Fe concentrations measured in DBS extracts reflects the content in erythrocytes; since either RBC-K nor RBC-Fe are traditionally used in clinical evaluation, further studies are needed in order to evaluate the use DBS potassium and iron in a clinical context. But measurement of K or Fe in DBS by ICP-MS seems promising as a possible tool to calculate the hematocrit and could enable a correction of the hematocrit influence. However, further validation of the method using capillary blood is necessary in order assess the use of DBS-K or DBS-Fe from ICP-MS measurements to calculate sample hematocrit. For clinical purposes elements Na, Mg, K, and Fe are normally measured in the plasma phase. In the case of K and Fe the intracellular erythrocyte concentration is approximately 25–1000 times higher than in plasma [17]. As DBS sampling is based on drops of whole blood on filter paper and as the extraction procedure releases elements from erythrocytes, a much higher concentration of K and Fe is found in the DBS extracts compared to the corresponding plasma samples. The concentration of K and Fe in the DBS extracts is furthermore directly influenced by the sample hematocrit and therefore, a direct comparison between plasma and DBS concentrations cannot be made for these
two elements. DBS is a suitable matrix for establishing reference intervals for elements Na, Mg, K, Fe, Cu, Zn, and Se in DBS using ICP-MS. Reference ranges should however be established from hematocrit corrected values. Unfortunately, DBS seems to be an unsuitable matrix for establishing reference intervals using ICP-MS for elements Co, As, Cd and Pb (and calcium) due to high background signals from the filter paper. Our study has some strengths and limitations: Strengths include the small amount of DBS material per person required to obtain results for multiple elements enabling the rest of DBS to be used for other purposes. It is also an advantage that an estimate of sample hematocrit can be obtained in the same analytical run enabling correction of extreme hematocrit values or normalization of data. The study was limited to the use of Whatman 903 protein saver cards and Whatman Schleicher & Schuell 903, and different results may be obtained by using other types of DBS cards such as polyvinylidene difluoride (PVDF) membranes. Another limitation is the relative high sample volume required when using the 8–10 mL tubes required by the Cetac-ASX-520 autosampler and the simple peristaltic pump inlet system on the ICPMS. This causes a relative high dilution of the DBS extracts. Optimizing the method using an autosampler for microtiter plates racks with sample volumes as low as 500 μL could improve the sensitivity of the method. This method is limited by a relative high background signal from the filter paper for some elements. Using pre-cleaned for prospective sampling as suggested [7] may improve the method for heavy metals, but as the majority of DBS samples collected in biobanks are non-cleaned cards this method will only be suitable for future sample collection. In conclusion, we found good correlation between measurement in DBS and venous whole blood of the elements Mg, K, Fe, Cu, Zn, As and Se, while for Co, As, Cd and Pb the method was only precise and accurate
Please cite this article as: L. Pedersen, et al., Quantification of multiple elements in dried blood spot samples, Clin Biochem (2017), http:// dx.doi.org/10.1016/j.clinbiochem.2017.01.010
L. Pedersen et al. / Clinical Biochemistry xxx (2017) xxx–xxx
at toxic or elevated levels. Hematocrit however influenced the DBS element measurement, especially for K, Fe and Zn, but measurement of K and Fe in DBS extracts seems to enable sample hematocrit estimation. Appendix A. Supplementary data Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.clinbiochem.2017.01.010. References [1] R. Guthrie, A. Susi, A simple phenylalanine method for detecting phenylketonuria in large populations of newborn infants, Pediatrics 32 (1963) 338–343. [2] P.M. De Kesel, N. Sadones, S. Capiau, W.E. Lambert, C.P. Stove, Hemato-critical issues in quantitative analysis of dried blood spots: challenges and solutions, Bioanalysis 5 (2013) 2023–2041. [3] J. Henion, R.V. Oliveira, D.H. Chace, Microsample analyses via DBS: challenges and opportunities, Bioanalysis 5 (2013) 2547–2565. [4] W.E. Funk, J.K. McGee, A.F. Olshan, A.J. Ghio, Quantification of arsenic, lead, mercury and cadmium in newborn dried blood spots, Biomarkers 18 (2013) 174–177. [5] E.K. Langer, K.J. Johnson, M.M. Shafer, P. Gorski, J. Overdier, J. Musselman, J.A. Ross, Characterization of the elemental composition of newborn blood spots using sector-field inductively coupled plasma-mass spectrometry, J. Expo. Sci. Environ. Epidemiol. 21 (2011) 355–364. [6] V. Vacchina, V. Huin, S. Hulo, D. Cuny, F. Broly, G. Renom, J.M. Perini, Use of dried blood spots and inductively coupled plasma mass spectrometry for multi-element determination in blood, J. Trace Elem. Med. Biol. 28 (2014) 255–259.
7
[7] W.E. Funk, J.D. Pleil, D.J. Sauter, T.W. McDade, J.L. Holl, Use of dried blood spots for estimating children's exposures to heavy metals in epidemiological research, J. Environ. Anal. Toxicol. S7 (2015) 002. [8] P.M. Edelbroek, J. van der Heijden, L.M. Stolk, Dried blood spot methods in therapeutic drug monitoring: methods, assays, and pitfalls, Ther. Drug Monit. 31 (2009) 327–336. [9] J.V. Mei, J.R. Alexander, B.W. Adam, W.H. Hannon, Use of filter paper for the collection and analysis of human whole blood specimens, J. Nutr. 131 (2001) 1631S–1636S. [10] M. O'Mara, B. Hudson-Curtis, K. Olson, Y. Yueh, J. Dunn, N. Spooner, The effect of hematocrit and punch location on assay bias during quantitative bioanalysis of dried blood spot samples, Bioanalysis 3 (2011) 2335–2347. [11] H.W. Vesper, W.G. Miller, G.L. Myers, Reference materials and commutability, Clin. Biochem. Rev. 28 (2007) 139–147. [12] D. MacDougall, W.B. Crummett, F. Amore, G. Cox, D.G. Crosby, T. Abeku, et al., Guidelines for data acquisition and data quality evaluation in environmental chemistry, Anal. Chem. 52 (1980) 2242–2249. [13] D.A. Armbruster, T. Pry, Limit of blank, limit of detection and limit of quantitation, Clin. Biochem. Rev. 29 (Suppl. 1) (2008) S49–S52. [14] S. Capiau, V.V. Stove, W.E. Lambert, C.P. Stove, Prediction of the hematocrit of dried blood spots via potassium measurement on a routine clinical chemistry analyzer, Anal. Chem. 85 (2013) 404–410. [15] L. Fan, J.A. Lee, Managing the effect of hematocrit on DBS analysis in a regulated environment, Bioanalysis 4 (2012) 345–347. [16] A.R. Pries, D. Neuhaus, P. Gaehtgens, Blood viscosity in tube flow: dependence on diameter and hematocrit, Am. J. Phys. 263 (1992) H1770–H1778. [17] J.M. Harrington, D.J. Young, A.S. Essader, S.J. Sumner, K.E. Levine, Analysis of human serum and whole blood for mineral content by ICP-MS and ICP-OES: development of a mineralomics method, Biol. Trace Elem. Res. 160 (2014) 132–142.
Please cite this article as: L. Pedersen, et al., Quantification of multiple elements in dried blood spot samples, Clin Biochem (2017), http:// dx.doi.org/10.1016/j.clinbiochem.2017.01.010