It is becoming increasingly clear that early-life exposures may be etiologically relevant to disease later in life (Waterland and Michels, 2007
). Electrolyte and trace metal disturbances are known to be involved in the pathogenesis of many diseases with some evidence suggesting that prenatal exposure to lead and lithium is associated with an increased risk of adverse outcomes in the offspring (Bellinger, 2005
; Giles and Bannigan, 2006
; Seiler et al., 1994
). Therefore, an important aspect of conducting studies that aim to determine relationships between diseases and prenatal exposures is the development of assays to measure analytes in samples collected around the time of birth. Although venous blood samples would be the preferred sample for measuring neonatal exposures, these samples are not routinely available retrospectively. Since NBSs are collected on most newborns and retained by some states that also permit their use in research (Olshan, 2007
), our objective was to develop an assay to measure elements in NBS samples using SF-ICP-MS.
Previous studies have simultaneously measured up to 37 elements in whole blood, plasma, urine, or hair by ICP-MS (Barbany E, 1997
; Goulle et al., 2005
; Heitland and Koster, 2006a
; Heitland and Koster, 2006b
; Muniz et al., 2001
). To our knowledge, this is the first study that has attempted to measure a large panel of elements in NBS. Using our optimized extraction protocol that we developed specifically for this application, coupled with SF-ICP-MS analysis, we were able to quantify 11 clinically relevant elements (Ca, Cs, Cu, Fe, K, Mg, Na, P, Rb, S, Zn) in the majority of NBS samples after accounting for measurement uncertainties. In addition, some elements (Li, Cd, Cs, Cr, Ni, Mo, and Pb) were detected at high levels in a minority of NBSs indicating that the assay may be useful for determining infants who have been exposed to supraphysiologic levels of trace elements while in utero.
We are aware of only two other studies that have used ICP-MS for element detection in dried blood spots (Chaudhuri et al., 2008
; Cizdziel, 2007
), only one of which measured elements using an extraction-based protocol (Chaudhuri et al., 2008
). In the first study, the authors reported successful measurement of lead and mercury but not cadmium (Chaudhuri et al., 2008
). In the second study, that introduced sample material into the ICP-MS by laser ablation, Pb, Ca, V, Fe, Cu, and Zn were measured in dried blood samples (Cizdziel, 2007
). This technique has the advantage over solution-based ICP-MS of measuring elements in solid matrices and thus requires no extraction/digestion procedures. However, limitations of this method include filter-blank and sample heterogeneity issues, matrix effects, and calibration challenges that limit quantitative analysis, particularly for multi-element applications (Pisonero J, 2009
Our assay was optimized to measure elements in a half blood spot, allowing the remainder to be used for other analyses (e.g. genotyping, measurement of other analytes, etc). Element measurement in a half spot (in contrast to a single punch) should theoretically improve assay reproducibility that can be influenced by sample location on the filter paper and hematocrit level (Carter, 1978
; Holub et al., 2006
; O'Broin, 1993
; Mei et al., 2001
) that has been shown to be variable among infants (Bizzarro et al., 2004
; Kayiran et al., 2003
). CVs of <10% were obtained between half spots from the same NBS for most elements in the majority of NBS indicating that the assay is highly reproducible.
Our results indicated some significant limitations to using NBSs as the source material for blood element quantification. Chief among these is adequate control of extraneous non-blood element. Our study and a similar study (Chaudhuri et al., 2008
) found significant differences in element levels between NBS card lots for cadmium and lead. Both studies and one additional study (Cizdziel, 2007
) noted the presence of high outliers for lead in some of the samples of blank filter paper that were tested. Thus, stochastic contamination of the NBS from field processing as well as filter paper lot variation in background element levels could have a substantial impact on the ability to quantify selected elements in NBS. For other elements (e.g. K, Fe, Na, P, Rb, and Zn), the filter paper contributed very little to the total element amount, and therefore quantification would not be substantially impacted by lot variation in filter paper element
Contamination of NBS samples from environmental sources (e.g. handling, heel sweat), however, could still be an issue, but the magnitude of this factor remains unclear. Whether the generally higher element levels observed in the “blank” region of spotted paper in comparison to that in unspotted cards was the result of environmental contamination, filter heterogeneity, or “bleed” from the blood spot is uncertain. Bleed from the spot could be due to diffusion of plasma or serum past the designated spot area. Although we did not visually observe any contamination, our data indicate that this may have occurred. For example, very low levels of Fe were measured in the “blank” spot sampled adjacent to the blood spot relative to the blood spot, as expected, because Fe resides mainly in red blood cells that would not be expected to diffuse to any large degree outside the spot area. In contrast, Na, which also had very low levels in blank unspotted filter paper relative to the blood spot, and is predominantly found in the extracellular compartment of blood, had a markedly lower corrected median concentration when corrected for element using correction method B (36% lower), but not correction method A (4% lower), which suggests some plasma migration. Further research is needed to address whether a sample of filter paper that is further away from the blood sample has lower background element than one adjacent to the spot, and might provide an ideal correction that better reflects extraneous non-blood element sources.
Another limitation to fully quantitative element measurement in NBSs is with regard to the volume of blood spotted on NBS cards. We assumed in our background element correction calculations (as described in the supplementary material
) an 80 µl spotted blood volume based on experiments that showed this blood volume completely filled the inscribed NBS circle without saturating it (data not shown). A similar volume assumption has been made by others (Chaudhuri et al., 2008
). This assumption may be problematic if blood is improperly spotted. However, several recent studies have suggested that spotted blood volume variation may not be a large concern in properly spotted samples
(see GE Healthcare, 2009
for links to images of valid NBS specimens). In a study of phenylalanine measurement in NBS, concentrations varied by only 11% between punches from NBSs spotted with either 35 or 100 µl of blood (Adam et al., 2000
). Other recent studies have suggested no difference in the concentrations of small molecules measured in same sized punches from filter paper spotted with different blood volumes (Li and Tse, 2010
). In practice, researchers may want to include an additional volume uncertainty component in their calculation of NBS element concentrations, especially if improperly spotted cards are used in their study.
A further suggestion for improvement in measurement precision caused by spotted blood volume variation is the “use of a ratio element such as magnesium or calcium, which has a narrower range in cord blood, to normalize other element values” (Olshan, 2007
). However, our data indicate that Mg and Ca may be inappropriate for normalization purposes due to both their high level and variability in blank filter paper samples. Other elements, such as potassium, which was found at low levels in unspotted filter paper relative to NBS, could be explored as a candidate to normalize for volume differences. The ability to quantify a number of elements that might prove useful in normalizing elemental values in the NBS is a notable feature of the method described here. Although we could not address this question with our data, this is an important area for further research.