Multiple reaction monitoring (MRM)-profiling with biomarker identification by LC-QTOF to characterize coronary artery disease
| Autor: | R. Graham Cooks, Shane E. Tichy, Christina R. Ferreira, Karen E. Yannell |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Adult
Male 0301 basic medicine Multivariate statistics Metabolite Coronary Artery Disease Mass spectrometry 01 natural sciences Biochemistry Article Analytical Chemistry Coronary artery disease Young Adult 03 medical and health sciences chemistry.chemical_compound Metabolomics Tandem Mass Spectrometry Electrochemistry medicine Humans Environmental Chemistry Biomarker discovery Spectroscopy Aged Aged 80 and over Chromatography Chemistry 010401 analytical chemistry Selected reaction monitoring Middle Aged medicine.disease 0104 chemical sciences Triple quadrupole mass spectrometer 030104 developmental biology Female Biomarkers Chromatography Liquid |
| Zdroj: | The Analyst. 143:5014-5022 |
| ISSN: | 1364-5528 0003-2654 |
| DOI: | 10.1039/c8an01017j |
| Popis: | Metabolite profiling by mass spectrometry (MS) is an area of interest for disease diagnostics, biomarker discovery, and therapeutic evaluation. A recently developed approach, multiple reaction monitoring (MRM)-profiling, searches for metabolites with precursor (Prec) and neutral loss (NL) scans in a representative sample and creates a list of ion transitions. These are then used in an MRM method for fast screening of individual samples and discrimination between healthy and diseased. A large variety of functional groups are considered and all signals discovered are recorded in the individual samples, making this a largely unsupervised method. MRM-profiling is described here and then demonstrated with data for over 900 human plasma coronary artery disease (CAD) samples. Representative pooled samples for each condition were interrogated using a library of over a hundred Prec and NL scans on a triple quadrupole MS. The data from the Prec and NL experiments were converted into ion transitions, initially some 1266 transitions. Each ion transition was examined in the individual samples on a time scale of milliseconds per transition, which allows for rapid screening of large sample sets ( |
| Databáze: | OpenAIRE |
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