FragClust and TestClust, two informatics tools for chemical structure hierarchical clustering analysis applied to lipidomics. The example of Alzheimer's disease

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 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.

Occult hypoperfusion and changes of systemic lipid levels after severe trauma: an analysis in a standardized porcine polytrauma model

“…These findings have led us to identify new lipid-based signalling molecules, reveal the underlying lipid-driven mechanisms responsible for pathophysiological conditions. Several potential lipid biomarkers for early diagnosis and prognosis of diseases have been reported, such as genetic disorders [ 20 ], obesity and diabetes [ 21 ], cardiovascular disease [ 22 ], cancer [ 23 ], Alzheimer’s disease [ 24 , 25 ], and neurodegenerative disease [ 21 , 26 ]. Tissue-specific lipid distribution revealed by these lipidomic techniques is also believed to contribute to analysis of the origin of lipid change after trauma [ 27 ].…”

Discovering lipid phenotypic changes of sepsis-induced lung injury using high-throughput lipidomic analysis

“…[7][8][9][10] The perturbations of lipid metabolism and signaling are implicated in the pathogenesis of the most common and devastating diseases. They also play a vital role in cardiovascular diseases, 11 inammation, 12 Alzheimer's disease, 13,14 and metabolic diseases. 15 Lipidomics is dened as "the full characterization of lipid molecules and their biological functions with respect to the expression of proteins involved in lipid metabolism and function, including gene regulation", which deals with the detection and identication of lipids, fatty acids and their derivatives.…”