Gene/Protein Disease Symptom Drug Enzyme Compound
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Query: EC:1.3.99.3 (acyl-CoA dehydrogenase)
 1,425 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

Development of acylcarnitine and amino acid profiling using tandem mass spectrometry, and its application for use with dried blood specimens collected on filter-paper cards, has introduced an innovative new technology for detecting inborn errors of fatty acid, organic acid, and amino acid metabolism. From November 1, 1992 through June 30, 1999 we screened more than 700,000 newborns in Pennsylvania, Ohio, North Carolina, and Louisiana. We have prospectively detected 163 inborn errors of metabolism. Eighty-six patients have amino acid metabolism errors. Among them are phenylketonuria, hyperphenylalaninemia, maple syrup urine disease, and several urea cycle disorders. Thirty-two have organic acid metabolism errors, including glutaric aciduria type 1; 3-methylcrotonyl coenzyme A (CoA) carboxylase deficiency, propionic acidemia, methylmalonic acidemia, and 3-hydroxy-3-methylglutaryl-CoA lyase deficiency; and 45 have fatty acid oxidation errors, including 36 with medium-chain acyl-CoA dehydrogenase deficiency. Details of the methodology are presented and the potential of this screening technology is discussed.
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PMID:Automated tandem mass spectrometry for mass newborn screening for disorders in fatty acid, organic acid, and amino acid metabolism. 1059 60

We have initiated clinical selective screening for inborn errors of metabolism in China by analysing amino acids and acylcarnitines in a dried blood filter-paper samples using tandem mass spectrometry. Samples from a total of 3070 children suspected of inborn errors of metabolism were collected through a study network which covered most provinces of China. The diagnoses were further confirmed through clinical symptoms, by gas chromatography-mass spectrometry and other biochemistry studies, and in a few cases by DNA analysis. In all, 212 cases were diagnosed (6.6%) including 92 (43.4%) with amino acids disorders (48 with phenylketonuria, 12 with ornithine carbamoyltransferase deficiency, 7 with tyrosinaemia type I, 9 with maple syrup urine disease, 5 with citrullinaemia type I, 8 with citrullinaemia type II, 2 with homocystinuria, and 1 with argininaemia); 107 (50.5%) with organic acid disorders (including 58 with methylmalonic acidaemia, 13 with propionic acidaemia, 6 with isovaleric acidaemia, 7 with glutaric acidaemia type I, 6 with 3-methylcrotonyl-CoA carboxylase deficiency, 2 with 3-hydroxy-3-methylglutaryl-CoA lyase deficiency, 10 with multiple carboxylase deficiency, and 5 with beta-ketothiolase deficiency); and 13 (6.1%) with fatty acid oxidation disorders (including 1 with carnitine palmitoyltransferase deficiency type I, 1 with carnitine palmitoyltransferase deficiency type II, 1 with short-chain acyl-CoA dehydrogenase deficiency, 5 with medium-chain acyl-CoA dehydrogenase deficiency, 3 with very long-chain acyl-CoA dehydrogenase deficiency, and 2 with multiple acyl-CoA dehydrogenase deficiency). It is suggested that tandem mass spectrometry is useful for selective screening of clinically suspected patients. The majority of diseases (94%) in this study were amino acid disorders and organic acid disorders. Fatty acid oxidation disorders are relatively rare in the Chinese, but medium-chain acyl-CoA dehydrogenase deficiency should be further investigated.
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PMID:Selective screening for inborn errors of metabolism on clinical patients using tandem mass spectrometry in China: a four-year report. 1734 12

The analysis of acylcarnitines (AC) in plasma/serum is established as a useful test for the biochemical diagnosis and the monitoring of treatment of organic acidurias and fatty acid oxidation defects. External quality assurance (EQA) for qualitative and quantitative AC is offered by ERNDIM and CDC in dried blood spots but not in plasma/serum samples. A pilot interlaboratory comparison between 14 European laboratories was performed over 3 years using serum/plasma samples from patients with an established diagnosis of an organic aciduria or fatty acid oxidation defect. Twenty-three different samples with a short clinical description were circulated. Participants were asked to specify the method used to analyze diagnostic AC, to give quantitative data for diagnostic AC with the corresponding reference values, possible diagnosis, and advice for further investigations.Although the reference and pathological concentrations of AC varied among laboratories, elevated marker AC for propionic acidemia, isovaleric acidemia, medium-chain acyl-CoA dehydrogenase, very long-chain acyl-CoA dehydrogenase, and multiple acyl-CoA dehydrogenase deficiencies were correctly identified by all participants allowing the diagnosis of these diseases. Conversely, the increased concentrations of dicarboxylic AC were not always identified, and therefore the correct diagnosis was not reach by some participants, as exemplified in cases of malonic aciduria and 3-hydroxy-3-methylglutaryl-CoA lyase deficiency. Misinterpretation occurred in those laboratories that used multiple-reaction monitoring acquisition mode, did not derivatize, or did not separate isomers. However, some of these laboratories suggested further analyses to clarify the diagnosis.This pilot experience highlights the importance of an EQA scheme for AC in plasma.
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PMID:Pilot Experience with an External Quality Assurance Scheme for Acylcarnitines in Plasma/Serum. 2689 93

Clinical metabolomics aims at finding statistically significant differences in metabolic statuses of patient and control groups with the intention of understanding pathobiochemical processes and identification of clinically useful biomarkers of particular diseases. After the raw measurements are integrated and pre-processed as intensities of chromatographic peaks, the differences between controls and patients are evaluated by both univariate and multivariate statistical methods. The traditional univariate approach relies on t-tests (or their nonparametric alternatives) and the results from multiple testing are misleadingly compared merely by p-values using the so-called volcano plot. This paper proposes a Bayesian counterpart to the widespread univariate analysis, taking into account the compositional character of a metabolome. Since each metabolome is a collection of some small-molecule metabolites in a biological material, the relative structure of metabolomic data, which is inherently contained in ratios between metabolites, is of the main interest. Therefore, a proper choice of logratio coordinates is an essential step for any statistical analysis of such data. In addition, a concept of b-values is introduced together with a Bayesian version of the volcano plot incorporating distance levels of the posterior highest density intervals from zero. The theoretical background of the contribution is illustrated using two data sets containing samples of patients suffering from 3-hydroxy-3-methylglutaryl-CoA lyase deficiency and medium-chain acyl-CoA dehydrogenase deficiency. To evaluate the stability of the proposed method as well as the benefits of the compositional approach, two simulations designed to mimic a loss of samples and a systematical measurement error, respectively, are added.
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PMID:Bayesian multiple hypotheses testing in compositional analysis of untargeted metabolomic data. 3191 Sep 69