Wide metabolite coverage LC-MS/MS assay for the diagnosis of inherited metabolic disorders in urine

OBJECTIVE

The laboratory diagnosis of inherited metabolic disorders (IMD) has undergone significant development in recent decades, mainly due to the use of mass spectrometry, which allows rapid multicomponent analysis of a wide range of metabolites. Combined with advanced software tools, the diagnosis becomes more efficient as a benefit for both physicians and patients.

METHODS

A hydrophilic interaction liquid chromatography coupled with tandem mass spectrometry assay for determination of urinary purines, pyrimidines, N-acylglycines, N-acetylated amino acids, sugars, sugar alcohols and other diagnostically important biomarkers was developed and validated. Evaluation of the results consisting of utilisation of robust scaling and advanced visualization tools is simple and even suitable for urgent requirements.

RESULTS

The developed method, covering 65 biomarkers, provides a comprehensive diagnostic platform for 51 IMD. For most analytes, linearity with R2 > 0.99, intra and inter-day accuracy between 80 and 120 % and precision lower than 20 % were achieved. Diagnostic workflow was evaluated on 47 patients and External Quality Assurance samples involving a total of 24 different IMD. Over seven years, more than 2300 urine samples from patients suspected for IMD have been routinely analysed.

CONCLUSIONS

This method offers the advantage of a broad coverage of intermediate metabolites of interest and therefore may be a potential alternative and simplification for clinical laboratories that use multiple methods for screening these markers.

Parallel Metabolomics and Lipidomics of a PSMA/GCPII Deficient Mouse Model Reveal Alteration of NAAG Levels and Brain Lipid Composition

Glutamate carboxypeptidase II (GCPII, also known as PSMA or FOLH1) is responsible for the cleavage of N-acetyl-aspartyl-glutamate (NAAG) to N-acetyl-aspartate and glutamate in the central nervous system and facilitates the intestinal absorption of folate by processing dietary folyl-poly-γ-glutamate in the small intestine. The physiological function of GCPII in other organs like kidneys is still not known. GCPII inhibitors are neuroprotective in various conditions (e.g., ischemic brain injury) in vivo; however, their utilization as potential drug candidates has not been investigated in regard to not yet known GCPII activities. To explore the GCPII role and possible side effects of GCPII inhibitors, we performed parallel metabolomic and lipidomic analysis of the cerebrospinal fluid (CSF), urine, plasma, and brain tissue of mice with varying degrees of GCPII deficiency (fully deficient in Folh1, -/-; one allele deficient in Folh1, +/-; and wild type, +/+). Multivariate analysis of metabolites showed no significant differences between wild-type and GCPII-deficient mice (except for NAAG), although changes were observed between the sex and age. NAAG levels were statistically significantly increased in the CSF, urine, and plasma of GCPII-deficient mice. However, no difference in NAAG concentrations was found in the whole brain lysate likely because GCPII, as an extracellular enzyme, can affect only extracellular and not intracellular NAAG concentrations. Regarding the lipidome, the most pronounced genotype-linked changes were found in the brain tissue. In brains of GCPII-deficient mice, we observed statistically significant enrichment in phosphatidylcholine-based lipids and reduction of sphingolipids and phosphatidylethanolamine plasmalogens. We hypothesize that the alteration of the NAA-NAAG axis by absent GCPII activity affected myelin composition. In summary, the absence of GCPII and thus similarly its inhibition do not have detrimental effects on metabolism, with just minor changes in the brain lipidome.

Clinical lipidomics in the era of the big data

Lipidomics as a branch of metabolomics provides unique information on the complex lipid profile in biological materials. In clinically focused studies, hundreds of lipids together with available clinical information proved to be an effective tool in the discovery of biomarkers and understanding of pathobiochemistry. However, despite the introduction of lipidomics nearly twenty years ago, only dozens of big data studies using clinical lipidomics have been published to date. In this review, we discuss the lipidomics workflow, statistical tools, and the challenges of standartisation. The consequent summary divided into major clinical areas of cardiovascular disease, cancer, diabetes mellitus, neurodegenerative and liver diseases is demonstrating the importance of clinical lipidomics. In these publications, the potential of lipidomics for prediction, diagnosis or finding new targets for the treatment of selected diseases can be seen. The first of these results have already been implemented in clinical practice in the field of cardiovascular diseases, while in other areas we can expect the application of the results summarized in this review in the near future.

Dynamics of acylcarnitines, hypoglycin A, méthylènecyclopropylglycine and their metabolites in a Kladruber stallion with atypical myopathy

Equine atypical myopathy (AM also referred to as multiple acyl-CoA dehydrogenases deficiency [MADD]) is thought to be caused by toxins metabolized from hypoglycin A (HGA) and méthylènecyclopropylglycine (MCPrG). HGA is contained in the seeds and seedlings of the sycamore tree (Acer pseudoplatanus); MCPrG has so far only been confirmed in seeds. Among other things, these substances can disrupt the fatty acids β-oxidation pathway with the subsequent accumulation of certain acylcarnitines. The tentative diagnosis is based on anamnesis and clinical signs and can be verified by the detection of elevated creatine kinase activity, specific profile of acylcarnitines and the presence of HGA, MCPrG conjugates and/or their metabolites in peripheral blood and/or urine. Dry blood spots were collected for 15 days from a 3.5-year-old stallion which had been affected by AM and, as a control group, from twelve healthy horses. Two mass spectrometry methods were used for the analysis of 31 acylcarnitines, carnitine, HGA, MCPrG and their metabolites. HGA and six increased acylcarnitines were detected in the patient’s blood throughout the monitoring period. Nine acylcarnitines were strongly correlated with HGA. Multivariate statistical analysis showed a clear separation of samples from the AM horse, where the metabolic profile tended to normalization in the later days after intoxication. Due to the longer persistence in the blood, the detection of HGA and elevated acylcarnitines profile appear to be an appropriate tool to confirm the diagnosis of AM, compared to metabolic products of HGA and MCPrG even in advanced cases.

Lipidomic and metabolomic analysis reveals changes in biochemical pathways for non-small cell lung cancer tissues

Lung cancer represents one of the leading worldwide causes of cancer death, but the pathobiochemistry of this disease is still not fully understood. Here we characterize the lipidomic and metabolomic profiles of the tumor and surrounding normal tissues for 23 patients with non-small cell lung cancer. In total, 500 molecular species were identified and quantified by a combination of the lipidomic shotgun tandem mass spectrometry (MS/MS) analysis and the targeted metabolomic approach using liquid chromatography (LC) - MS/MS. The statistical evaluation includes multivariate and univariate methods with the emphasis on paired statistical approaches. Our research revealed significant changes in several biochemical pathways related to the central carbon metabolism, acylcarnitines, dipeptides as well as the disruption in the lipid metabolism observed mainly for glycerophospholipids, sphingolipids, and cholesteryl esters.