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    Association of metabolomic and lipidomic approaches for plasma biomarkers discovery

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    <p>Metabolomics refers to the large scale detection and quantification of metabolites in a given biological condition. It is a multidisciplinary approach combining analytical chemistry, informatics and biostatistics. The comparison of metabolic profiles of biofluids from control and disease patients is currently used for biomarkers finding. However, these profiles obtained by liquid chromatography coupled to high resolution mass spectrometry (LC-HRMS) contain hundreds to thousands of features, most of them remaining unknown or at least not characterized in analytical systems, in particular in the field of biomarkers discovery. This makes necessary the use of robust data processing tools, i.e. peak detection and alignment algorithms and automatic annotation tools associated with public databases and an in-house metabolites (1200 metabolites to date) libraries.</p> <p>The challenge is as well to obtain comprehensive untargeted metabolic profiles of biofluids with metabolites displaying huge differences in physicochemical properties, from polar metabolites to apolar lipids. In this respect, we have developed an analytical pipeline involving 3 orthogonal LC-HRMS systems for the analysis of polar to moderately apolar molecules. Different chromatographic retention mechanisms, i.e. reversed phase, hydrophilic interaction liquid chromatography (HILIC) and PentaFluroPhenylPropyl (PFPP) are thus performed on the same sample.</p> <p>As a complementary approach, we have developed an analytical method for lipid profiling in plasma. This lipidomic method is based on dedicated sample preparation procedure, LC-HRMS conditions and data processing tools. When applied to human plasma samples, more than 900 unique lipid species, <em>i.e.</em> unique<em> m/z</em> – retention time signature, can be detected and identified, including glycerophospholipids, glycerolipids, shingolipids, free fatty acids and sterols and derivates.</p> <p>This methodology was applied to the comparison of 101 plasma samples of patients suffering from spinocerebellar ataxia (SCA1, 2, 3 and 7), obtained from Neuromics partners (WP4). The first results on their lipid profiles analyses will be presented.</p
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