FragClust and TestClust, two informatics tools for chemical structure hierarchical clustering analysis applied to lipidomics. The example of Alzheimer's disease.
Anal Bioanal Chem
; 408(9): 2215-26, 2016 Mar.
Article
en En
| MEDLINE
| ID: mdl-26753967
ABSTRACT
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 C100 (capric acid) and C240 (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.
Palabras clave
Texto completo:
1
Bases de datos:
MEDLINE
Asunto principal:
Enfermedad de Alzheimer
/
Lípidos
Tipo de estudio:
Observational_studies
Límite:
Aged
/
Aged80
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Humans
Idioma:
En
Revista:
Anal Bioanal Chem
Año:
2016
Tipo del documento:
Article
País de afiliación:
Italia