Background: Analysis of urinary organic acids (UOAs) by gas chromatography mass-spectrometry (GC-MS) is widely used in metabolomic studies. It is a complex test with many limitations and pitfalls yet there is limited evidence in the literature to support best practice. This study investigated the impact of drying down time and temperature on the recovery of 16 key analytes from solvent extracts.
View Article and Find Full Text PDFHereditary tyrosinemia type 1 (HT1) is a rare metabolic disease resulting in acute liver failure in early infancy, hypophosphataemic rickets, neurological crises, liver cirrhosis and risk of hepatocellular carcinoma later on in life. It is caused by the deficiency of the enzyme fumarylacetoacetate hydrolase which is involved in the terminal step of the catabolic pathway of tyrosine. Diagnosis is made through clinical suspicion supported by biochemical abnormalities that result from accumulation of upstream metabolites.
View Article and Find Full Text PDFMeasurement of plasma and dried blood spot (DBS) phenylalanine (Phe) is key to monitoring patients with phenylketonuria (PKU). The relationship between plasma and capillary DBS Phe concentrations has been investigated previously, however, differences in methodology, calibration approach and assumptions about the volume of blood in a DBS sub-punch has complicated this. Volumetric blood collection devices (VBCDs) provide an opportunity to re-evaluate this relationship.
View Article and Find Full Text PDFAn automated method for the measurement of blood tacrolimus on volumetric absorptive microsampling (VAMS) devices was developed. VAMS devices prepared by the automated method were compared with those prepared by the existing manual method (n = 284; mean concentration: 8.0 μg/l; range: 0.
View Article and Find Full Text PDFBackground: Measurement of dried blood spot (DBS) phenylalanine (Phe) is central to the monitoring of patients with phenylketonuria. However, the volume and hematocrit (Hct) of the blood applied to conventional DBS cards significantly affects analytical results. Volumetric blood collection devices are reported to be more accurate, precise and less prone to Hct effects.
View Article and Find Full Text PDFBackground: Plasma amino acid (PAA) profiles are used in routine clinical practice for the diagnosis and monitoring of inherited disorders of amino acid metabolism, organic acidemias, and urea cycle defects. Interpretation of PAA profiles is complex and requires substantial training and expertise to perform. Given previous demonstrations of the ability of machine learning (ML) algorithms to interpret complex clinical biochemistry data, we sought to determine if ML-derived classifiers could interpret PAA profiles with high predictive performance.
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