Qualitative urinary organic acid analysis: 10 years of quality assurance

Chromatomass-Spectrometric Method for the Quantitative Determination of Amino- and Carboxylic Acids in Biological Samples

A highly sensitive method for the qualitative and quantitative determination of amino- and carboxylic acids, as well as a number of urea and methionine cycle metabolites in the studied solutions, is presented. Derivatives (esterification) were obtained for amino acids by their reaction in a solution of 3 N of hydrochloric acid in n-butanol for 15 min at 65 °C and for carboxylic acids by their reaction with phenol in ethyl acetate with 3 N of hydrochloric acid for 20 min at 65 °C. Experimental work on the determination of individual metabolites was carried out using the HPLC-MS/MS method and included the creation of a library of spectra of the analyzed compounds and their quantitative determination. Multiplex methods have been developed for the quantitative analysis of the desired metabolites in a wide range of concentrations of 3-4 orders of magnitude. The approach to the analysis of metabolites was developed based on the method of the dynamic monitoring of multiple reactions of the formation of fragments for a mass analyzer with a triple quadrupole (QQQ). The effective chromatographic separation of endogenous metabolites was carried out within 13 min. The calibration curves of the analyzed compounds were stable throughout the concentration range and had the potential to fit below empirical levels. The developed methods and obtained experimental data are of interest for a wide range of biomedical studies, as well as for monitoring the content of endogenous metabolites in biological samples under various pathological conditions. The sensitivity limit of the methods for amino acids was about 4.8 nM and about 0.5 μM for carboxylic acids. Up to 19 amino- and up to 12 carboxy acids and about 10 related metabolites can be tested in a single sample.

The role of ERNDIM diagnostic proficiency schemes in improving the quality of diagnostic testing for inherited metabolic diseases

External quality assurance (EQA) is crucial to monitor and improve the quality of biochemical genetic testing. ERNDIM (www.erndim.org), established in 1994, aims at reliable and standardized procedures for diagnosis, treatment and monitoring of inherited metabolic disease (IMD) by providing EQA schemes and educational activities. Currently, ERNDIM provides 16 different EQA schemes including quantitative schemes for various metabolite groups, and interpretive schemes such as diagnostic proficiency testing (DPT). DPT schemes focus on the ability of laboratories to correctly identify and interpret abnormalities in authentic urine samples across a wide range of IMDs. In the DPT schemes, six samples each year are distributed together with clinical information. Laboratories choose and perform the tests needed to reach a diagnosis. Data were collected on 345 samples, distributed to up to 105 laboratories worldwide. Diagnostic proficiency (the % of total points possible for all participating laboratories within a scheme for analysis and interpretation) ranged widely: amino acid disorders (n = 20), range 33%-100%, mean 84%; organic acid disorders (n = 35), range 14%-100%, mean 84%; lysosomal storage disorders (n = 13), range 20%-97%, mean 73%; purine/pyrimidine disorders (n = 9), range 37%-100%, mean 70%; miscellaneous disorders (n = 8), range 17%-100%, mean 65%; no IMD, range 65%-95%, mean 85%. When a sample with the same disorder was distributed in a subsequent survey, performance improved in 75 cases with no improvement seen in 32, suggesting overall improvement of performance. ERNDIM diagnostic proficiency testing is a valuable activity which can help to assess laboratory performance, identify methodological/technical challenges, be informative during quality audits and contribute to a better clinical appreciation of diagnostic uncertainty.

Laboratory practice of organic acid analysis based on gas chromatography–mass spectrometry in China

Objectives

The aim of this study is to investigate the status of laboratory practice of organic acid (OA) analysis using gas chromatography–mass spectrometry in China.

Methods

A survey, investigating details of laboratory practice of OA analysis, was issued on the website of the National Center for Clinical Laboratories of China. Nationwide external quality assessment participating laboratories of OA assay were informed to participate in this survey.

Results

A total of 36 laboratories completed this survey. Most laboratories started OA analysis during 2016–2020. Most (100%) labs reported semi-quantitative results, in which 79.4% of labs adopted the form of the ratio of peak area of OA and quantitative internal standard. Rare labs reported quantitative results. Few labs released reports in three days, most in 5–7 days. The source of control materials varied, 64.5% of labs adapted self-made materials. A total of 43.8% of laboratories directly used reference intervals (RIs) from published literature, 43.8% of laboratories established RIs themselves, but 21.2% of laboratories reported they didn’t verify RIs.

Conclusions

Appropriate supervision for the organic acid assay is needed in the aspect of the turnaround time of reporting results, the establishment validation and verification of reference ranges, and the quantification of results.

Fast and accurate quantitative organic acid analysis with LC-QTOF/MS facilitates screening of patients for inborn errors of metabolism

Since organic acid analysis in urine with gaschromatography-mass spectrometry (GC-MS) is a time-consuming technique, we developed a new liquid chromatography-quadrupole time-of-flight mass spectrometry (LC-QTOF/MS) method to replace the classical analysis for diagnosis of inborn errors of metabolism (IEM). Sample preparation is simple and experimental time short. Targeted mass extraction and automatic calculation of z-scores generated profiles characteristic for the IEMs in our panel consisting of 71 biomarkers for defects in amino acids, neurotransmitters, fatty acids, purine, and pyrimidine metabolism as well as other disorders. In addition, four medication-related metabolites were included in the panel. The method was validated to meet Dutch NEN-EN-ISO 15189 standards. Cross validation of 24 organic acids from 28 urine samples of the ERNDIM scheme showed superiority of the UPLC-QTOF/MS method over the GC-MS method. We applied our method to 99 patient urine samples with 32 different IEMs, and 88 control samples. All IEMs were unambiguously established/diagnosed using this new QTOF method by evaluation of the panel of 71 biomarkers. In conclusion, we present a LC-QTOF/MS method for fast and accurate quantitative organic acid analysis which facilitates screening of patients for IEMs. Extension of the panel of metabolites is easy which makes this application a promising technique in metabolic diagnostics/laboratories.