FragClust and TestClust, two informatics tools for chemical structure hierarchical clustering analysis applied to lipidomics. The example of Alzheimer's disease
Autor: | Roberto Monastero, Ornella Palesano, G.I. Altieri, Francesca Di Gaudio, Sergio Indelicato, Massimiliano Greco, Francesca Fayer, David Bongiorno, Angela Aronica, Maurizio Averna, Manuela Fontana, Angelo B. Cefalù, Serena Indelicato, Davide Noto |
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Přispěvatelé: | Di Gaudio, F., Indelicato, S., Monastero, R., Altieri, G., Fayer, F., Palesano, O., Fontana, M., Cefalù, A., Greco, M., Bongiorno, D., Aronica, A., Noto, D., Averna, M. |
Jazyk: | angličtina |
Rok vydání: | 2016 |
Předmět: |
0301 basic medicine
High-resolution mass spectrometry Settore MED/09 - Medicina Interna Chemical structure Computational biology Plasma biomarkers 01 natural sciences Triglyceride Biochemistry Homogeneous clusters Analytical Chemistry Ceramide 03 medical and health sciences Alzheimer Disease Tandem Mass Spectrometry Health informatics tools Lipidomics Humans Statistical analysis Data mining Chromatography High Pressure Liquid Aged Aged 80 and over Molecular Structure Chemistry 010401 analytical chemistry Lipids 0104 chemical sciences Hierarchical clustering Phospholipid 030104 developmental biology Workflow Case-Control Studies Settore MED/26 - Neurologia |
Popis: | Lipidomic analysis is able to measure simultaneously thousands of compounds belonging to a few lipid classes. In each lipid class, compounds differ only by the acyl radical, ranging between C10:0 (capric acid) and C24:0 (lignoceric acid). Although some metabolites have a peculiar pathological role, more often compounds belonging to a single lipid class exert the same biological effect. Here, we present a lipidomics workflow that extracts the tandem mass spectrometry data from individual files and uses them to group compounds into structurally homogeneous clusters by chemical structure hierarchical clustering analysis (CHCA). The case-to-control peak area ratios of the metabolites are then analyzed within clusters. We created two freely available applications to assist the workflow: FragClust to generate the tables to be subjected to CHCA, and TestClust to perform statistical analysis on clustered data. We used the lipidomics data from the plasma of Alzheimer's disease (AD) patients in comparison with healthy controls to test the workflow. To date, the search for plasma biomarkers in AD has not provided reliable results. This article shows that the workflow is helpful to understand the behavior of whole lipid classes in plasma of AD patients. [Figure not available: see fulltext.] |
Databáze: | OpenAIRE |
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