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Development of Certified Reference Material for Amino Acids in Dried Blood Spots and Accuracy Assessment of Disc Sampling

Authors
Woo, SangjiRosli, NordianaChoi, SeohyunKwon, Ha-JeongYoon, Young AhnAhn, SunhyunLee, Ji YounHong, Seon-PyoJeong, Ji-Seon
Issue Date
Jul-2022
Publisher
American Chemical Society
Citation
Analytical Chemistry, v.94, no.28, pp 10127 - 10134
Pages
8
Journal Title
Analytical Chemistry
Volume
94
Number
28
Start Page
10127
End Page
10134
URI
https://scholarworks.bwise.kr/sch/handle/2021.sw.sch/21267
DOI
10.1021/acs.analchem.2c01349
ISSN
0003-2700
1520-6882
Abstract
To achieve the measurement reliability of amino acids used as diagnostic markers in clinical fields, establishing a reference measurement system is required, in which certified reference materials (CRMs) are an essential step in the hierarchy of measurement traceability. This study describes the development of dried blood spot (DBS) CRMs for amino acid analysis with complete measurement traceability to the International System of Units (SI). Six essential amino acids-proline, valine, isoleucine, leucine, phenylalanine, and tyrosine-were analyzed using isotope-dilution liquid chromatography-mass spectrometry (ID-MS). For minimizing measurement bias and uncertainty overestimation, whole spots with 50 mu L of whole blood were adopted in the certification. The between-spot homogeneities by whole spot sampling were lower than 2.1%. The relative expanded uncertainties of the six amino acids in the developed DBS CRMs were lower than 5.7% at 95% confidence. The certified values are traceable to SI through both gravimetric preparation and the primary method in certification, ID-MS. Comparison among DBS testing laboratories revealed discrepancies between the whole spot and disc sampling methods. The actual sampling volume was accurately estimated by weighing, which revealed the possibility of underestimation in routine DBS testing. The candidate CRMs can support the standardization of DBS testing for amino acids through the qualification and validation of many kinds of measurement procedures to compensate the measurement bias caused by matrix-specific sampling error.
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