Targeted metabolomic analysis of plasma samples for the diagnosis of inherited metabolic disorders
Jazyk angličtina Země Nizozemsko Médium print-electronic
Typ dokumentu časopisecké články, práce podpořená grantem
PubMed
22018716
DOI
10.1016/j.chroma.2011.09.074
PII: S0021-9673(11)01465-8
Knihovny.cz E-zdroje
- MeSH
- analýza hlavních komponent MeSH
- dítě MeSH
- dospělí MeSH
- lidé MeSH
- metabolom MeSH
- metabolomika metody MeSH
- mladiství MeSH
- předškolní dítě MeSH
- průtoková injekční analýza MeSH
- reprodukovatelnost výsledků MeSH
- shluková analýza MeSH
- tandemová hmotnostní spektrometrie MeSH
- vrozené poruchy metabolismu aminokyselin krev diagnóza MeSH
- Check Tag
- dítě MeSH
- dospělí MeSH
- lidé MeSH
- mladiství MeSH
- mužské pohlaví MeSH
- předškolní dítě MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Metabolomics has become an important tool in clinical research and diagnosis of human diseases. In this work we focused on the diagnosis of inherited metabolic disorders (IMDs) in plasma samples using a targeted metabolomic approach. The plasma samples were analyzed with the flow injection analysis method. All the experiments were performed on a QTRAP 5500 tandem mass spectrometer (AB SCIEX, U.S.A.) with electrospray ionization. The compounds were measured in a multiple reaction monitoring mode. We analyzed 50 control samples and 34 samples with defects in amino acid metabolism (phenylketonuria, maple syrup urine disease, tyrosinemia I, argininemia, homocystinuria, carbamoyl phosphate synthetase deficiency, ornithine transcarbamylase deficiency, nonketotic hyperglycinemia), organic acidurias (methylmalonic aciduria, propionic aciduria, glutaric aciduria I, 3-hydroxy-3-methylglutaric aciduria, isovaleric aciduria), and mitochondrial defects (medium-chain acyl-coenzyme A dehydrogenase deficiency, carnitine palmitoyltransferase II deficiency). The controls were distinguished from the patient samples by principal component analysis and hierarchical clustering. Approximately 80% of patients were clearly detected by absolute metabolite concentrations, the sum of variance for first two principle components was in the range of 44-55%. Other patient samples were assigned due to the characteristic ratio of metabolites (the sum of variance for first two principle components 77 and 83%). This study has revealed that targeted metabolomic tools with automated and unsupervised processing can be applied for the diagnosis of various IMDs.
Citace poskytuje Crossref.org
Cellwise outlier detection and biomarker identification in metabolomics based on pairwise log ratios