Abstract
Background
Urine amino acid analysis is used for the assessment of various diseases. The aim of this study was to estimate the valid biological variation (BV) components (within- and between-subjects) required for the safe clinical application of free urine amino acids.
Methods
First morning void urine samples were taken from 12 healthy subjects (five females, seven males) once a week for 10 consecutive weeks, and amino acid analysis was performed using an Agilent 6470 triple quadrupole tandem mass spectrometer instrument. The obtained data were subjected to normality, outlier and variance homogeneity analyses prior to coefficient of variation (CV) analysis. Within- and between-subject BV values (CVI and CVG) of 39 amino acids were determined for all subjects. In addition, the index of individuality (II), reference change value (RCV), imprecision, bias and total error were estimated using BV data obtained from our study.
Results
The CVI values ranged from 8.9 (histidine) to 36.8% (trans-4-hydroxyprolin), while the CVG values ranged from 25.0 (1-methyl-L-histidine) to 63.3% (phenylalanine). The II value of most amino acids was less than 0.6 and ranged between 0.21 and 0.88. The imprecision, bias and total error ranged between 4.45 and 16.6, between 7.69 and 16.6, and between 18.4 and 43.2, respectively.
Conclusions
This study, designed according to a rigorous protocol, has the feature of being the first to give information about BV data of urine amino acids. We believe that the reference intervals have a limitation in the evaluation of consecutive results from an individual, so the use of RCV would be more appropriate.
Acknowledgments
We would like to thank all volunteers involved in the study and Gökçe Göksu (Jasem R&D Manager) for technical assistance.
Research funding: This study was funded by the Research Fund of the Van Yüzüncü Yıl University, Project number: TSA-2018-6777.
Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.
Competing interests: Authors state no conflict of interest.
Informed consent: Informed consent was obtained from all individuals included in this study.
Ethical approval: Ethical approval was obtained from the local Ethics Committee (degree no: 03-2017).
References
1. Kasper D, Fauci A, Hauser S, Longo D, Jameson JL, Loscalzo J. Inherited disorders of amino acid metabolism in adults, 19th ed. McGraw-Hill Education, 2015:427–84.Search in Google Scholar
2. Marshall WJ, Lapsley M, Day AP, Ayling RM. Clinical biochemistry metabolic and clinical aspects, 3rd ed. Toronto: Elsevier, 2014:168–79.Search in Google Scholar
3. Dunstan RH, Sparkes DL, Macdonald MM, De Jonge XJ, Dascombe BJ, Gottfries J, et al. Diverse characteristics of the urinary excretion of amino acids in humans and the use of amino acid supplementation to reduce fatigue and sub-health in adults. Nutr J 2017;16:19.10.1186/s12937-017-0240-ySearch in Google Scholar PubMed PubMed Central
4. Wasim M, Awan FR, Khan HN, Tawab A, Iqbal M, Ayesha H. Aminoacidopathies: prevalence, etiology, screening, and treatment options. Biochem Genet 2018;56:7–21.10.1007/s10528-017-9825-6Search in Google Scholar PubMed
5. Sandberg S, Fraser CG, Horvath AR, Jansen R, Jones G, Oosterhuis W, et al. Defining analytical performance specifications: Consensus Statement from the 1st Strategic Conference of the European Federation of Clinical Chemistry and Laboratory Medicine. Clin Chem Lab Med 2015;53:833–5.10.1515/cclm-2015-0067Search in Google Scholar PubMed
6. Ceriotti F, Fernandez-Calle P, Klee GG, Nordin G, Sandberg S, Streichert T, et al. Criteria for assigning laboratory measurands to models for analytical performance specifications defined in the 1st EFLM Strategic Conference. Clin Chem Lab Med 2017;55:189–94.10.1515/cclm-2017-0772Search in Google Scholar PubMed
7. Biological variation database, and quality specifications for imprecision, bias and total error (desirable and minimum). Available at: https://www.westgard.com/biodatabase-2014-update.htm. Accessed: 2014.Search in Google Scholar
8. EFLM. BV Data. Available at: https://biologicalvariation.eu/bv_specifications/measurand. Accessed: 2019.Search in Google Scholar
9. Carobene A, Strollo M, Jonker N, Barla G, Bartlett WA, Sandberg S, et al. Sample collections from healthy volunteers for biological variation estimates’ update: a new project undertaken by the Working Group on Biological Variation established by the European Federation of Clinical Chemistry and Laboratory Medicine. Clin Chem Lab Med 2016;54:1599–608.10.1515/cclm-2016-0035Search in Google Scholar PubMed
10. Bartlett WA, Braga F, Carobene A, Coskun A, Prusa R, Fernandez-Calle P, et al. A checklist for critical appraisal of studies of biological variation. Clin Chem Lab Med 2015;53:879–85.10.1515/cclm-2014-1127Search in Google Scholar PubMed
11. Fraser CG, Harris EK. Generation and application of data on biological variation in clinical chemistry. Crit Rev Clin Lab Sci 1989;27:409–37.10.3109/10408368909106595Search in Google Scholar PubMed
12. Roraas T, Stove B, Petersen PH, Sandberg S. Biological variation: the effect of different distributions on estimated within-person variation and reference change values. Clin Chem 2016;62:725–36.10.1373/clinchem.2015.252296Search in Google Scholar PubMed
13. Snedecor GV, Cochran WG. Statistical methods, 8th ed. Iowa State University Press, 1989.Search in Google Scholar
14. Cochran WG. The distribution of the largest of a set of estimated variances as a fraction of their total. Ann Hum Genet 1941;11:47–52.10.1111/j.1469-1809.1941.tb02271.xSearch in Google Scholar
15. Shapiro SS, Wilk MB. An analysis of variance test for normality (complete samples). Biometrika 1965;52:591–611.10.1093/biomet/52.3-4.591Search in Google Scholar
16. Dixon WJ. Processing data for outliers. Biometrics 1953;9:74–89.10.2307/3001634Search in Google Scholar
17. Burdick RK, Graybill F. Confidence intervals on variance components, 1st ed. New York: Marcel Dekker, 1992.10.1201/9781482277142Search in Google Scholar
18. Fraser CG. Biological variation: from principles to practice. Washington, DC: AACC Press, 2001.Search in Google Scholar
19. Fraser CG, Petersen PH. Quality goals in external quality assessment are best based on biology. Scand J Clin Lab Invest Suppl 1993;212:8–9.10.1080/00365519309085446Search in Google Scholar
20. Fokkema MR, Herrmann Z, Muskiet FA, Moecks J. Reference change values for brain natriuretic peptides revisited. Clin Chem 2006;52:1602–3.10.1373/clinchem.2006.069369Search in Google Scholar
21. Bremer HJ. Disturbances of amino acid metabolism: clinical chemistry and diagnosis. Urban & Schwarzenberg, 1981.Search in Google Scholar
22. Parvy P, Bardet J, Rabier D, Kamoun P. A scheme for the interpretation of primary and secondary disturbances of plasma and urinary amino acid profiles. A possible way to an expert system. Clin Chim Acta 1995;235:1–10.10.1016/0009-8981(94)05992-9Search in Google Scholar
23. Gregory DM, Sovetts D, Clow CL, Scriver CR. Plasma free amino acid values in normal children and adolescents. Metabolism 1986;35:967–9.10.1016/0026-0495(86)90063-6Search in Google Scholar
24. Uaariyapanichkul J, Chomtho S, Suphapeetiporn K, Shotelersuk V, Punnahitananda S, Chinjarernpan P, et al. Age-related reference intervals for blood amino acids in Thai pediatric population measured by liquid chromatography tandem mass spectrometry. J Nutr Metab 2018;2018:5124035.10.1155/2018/5124035Search in Google Scholar PubMed PubMed Central
25. Haschke-Becher E, Kainz A, Bachmann C. Reference values of amino acids and of common clinical chemistry in plasma of healthy infants aged 1 and 4 months. J Inherit Metab Dis 2016;39:25–37.10.1007/s10545-015-9870-4Search in Google Scholar PubMed
26. Parvy PR, Bardet JI, Rabier DM, Kamoun PP. Age-related reference values for free amino acids in first morning urine specimens. Clin Chem 1988;34:2092–5.10.1093/clinchem/34.10.2092Search in Google Scholar
27. Corte Z, Venta R. Biological variation of free plasma amino acids in healthy individuals. Clin Chem Lab Med 2010;48:99–104.10.1515/CCLM.2010.008Search in Google Scholar PubMed
28. Schmidt JA, Rinaldi S, Scalbert A, Ferrari P, Achaintre D, GunterMJ, et al. Plasma concentrations and intakes of amino acids in male meat-eaters, fish-eaters, vegetarians and vegans: a cross-sectional analysis in the EPIC-Oxford cohort. Eur J Clin Nutr 2016;70:306–12.10.1038/ejcn.2015.144Search in Google Scholar PubMed PubMed Central
29. Fraser CG. Reference change values. Clin Chem Lab Med 2011;50:807–12.10.1515/cclm.2011.733Search in Google Scholar PubMed
30. Carobene A, Roraas T, Solvik UO, Sylte MS, Sandberg S, Guerra E, et al. Biological variation estimates obtained from 91 healthy study participants for 9 enzymes in serum. Clin Chem 2017;63:1141–50.10.1373/clinchem.2016.269811Search in Google Scholar PubMed
31. Coskun A, Carobene A, Kilercik M, Serteser M, Sandberg S, Aarsand AK, et al. Within-subject and between-subject biological variation estimates of 21 hematological parameters in 30 healthy subjects. Clin Chem Lab Med 2018;56:1309–18.10.1515/cclm-2017-1155Search in Google Scholar PubMed
32. Ahokoski O, Virtanen A, Kairisto V, Scheinin H, Huupponen R, Irjala K. Biological day-to-day variation and reference change limits of serum cortisol and aldosterone in healthy young men on unrestricted diets. Clin Chem 1999;45:1097–9.10.1093/clinchem/45.7.1097Search in Google Scholar
33. Talwar DK, Azharuddin MK, Williamson C, Teoh YP, McMillan DC, St J O’Reilly D. Biological variation of vitamins in blood of healthy individuals. Clin Chem 2005;51:2145–50.10.1373/clinchem.2005.056374Search in Google Scholar PubMed
Supplementary Material
The online version of this article offers supplementary material (https://doi.org/10.1515/cclm-2020-0249).
©2020 Walter de Gruyter GmbH, Berlin/Boston