6533b862fe1ef96bd12c63d6
RESEARCH PRODUCT
FragClust and TestClust, two informatics tools for chemical structure hierarchical clustering analysis applied to lipidomics. The example of Alzheimer's disease
Roberto MonasteroOrnella PalesanoG.i. AltieriFrancesca Di GaudioSergio IndelicatoMassimiliano GrecoFrancesca FayerDavid BongiornoAngela AronicaMaurizio AvernaManuela FontanaAngelo B. CefalùSerena IndelicatoDavide Notosubject
0301 basic medicineHigh-resolution mass spectrometrySettore MED/09 - Medicina InternaChemical structureComputational biologyPlasma biomarkers01 natural sciencesTriglycerideBiochemistryHomogeneous clustersAnalytical ChemistryCeramide03 medical and health sciencesAlzheimer DiseaseTandem Mass SpectrometryHealth informatics toolsLipidomicsHumansStatistical analysisData miningChromatography High Pressure LiquidAgedAged 80 and overMolecular StructureChemistry010401 analytical chemistryLipids0104 chemical sciencesHierarchical clusteringPhospholipid030104 developmental biologyWorkflowBiochemistryCase-Control StudiesSettore MED/26 - Neurologiadescription
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.]
year | journal | country | edition | language |
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2016-01-11 |