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Open AccessArticle

Troubleshooting in Large-Scale LC-ToF-MS Metabolomics Analysis: Solving Complex Issues in Big Cohorts

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CEMBIO, Centro de Excelencia en Metabolómica y Bioanálisis, Facultad de Farmacia, Universidad San Pablo CEU, 28668 Madrid, Spain
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IMMA, Instituto de Medicina Molecular Aplicada, Facultad de Medicina, Universidad San Pablo CEU, 28668 Madrid, Spain
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Laboratorio de Ensayos de Desarrollo Farmacéutico (LEDEFAR), Facultad de Estudios Superiores Cuautitlán, Universidad Nacional Autónoma de México, Estado de México CP.54714, Mexico
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Health and Biomedicine, Leitat Technological Center, 08028 Barcelona, Spain
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Analytical Unit, Health Research Institute Hospital La Fe, 46026 Valencia, Spain
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Departamento de Matemática Aplicada y Estadística, Universidad San Pablo CEU, 28668 Madrid, Spain
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Servicio de Alergia, “Hospital Universitario de Gran Canaria, Dr. Negrin”, 35010 Las Palmas de G.C., Spain
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Departamento de Ciencias Médicas Básicas, Facultad de Medicina, Universidad San Pablo CEU, 28668 Madrid, Spain
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Authors to whom correspondence should be addressed.
Metabolites 2019, 9(11), 247; https://doi.org/10.3390/metabo9110247
Received: 26 July 2019 / Revised: 11 October 2019 / Accepted: 21 October 2019 / Published: 24 October 2019
Metabolomics, understood as the science that manages the study of compounds from the metabolism, is an essential tool for deciphering metabolic changes in disease. The experiments rely on the use of high-throughput analytical techniques such as liquid chromatography coupled to mass spectrometry (LC-ToF MS). This hyphenation has brought positive aspects such as higher sensitivity, specificity and the extension of the metabolome coverage in a single run. The analysis of a high number of samples in a single batch is currently not always feasible due to technical and practical issues (i.e., a drop of the MS signal) which result in the MS stopping during the experiment obtaining more than a single sample batch. In this situation, careful data treatment is required to enable an accurate joint analysis of multi-batch data sets. This paper summarizes the analytical strategies in large-scale metabolomic experiments; special attention has been given to QC preparation troubleshooting and data treatment. Moreover, labeled internal standards analysis and their aim in data treatment, and data normalization procedures (intra- and inter-batch) are described. These concepts are exemplified using a cohort of 165 patients from a study in asthma. View Full-Text
Keywords: large-scale; metabolomics; LC-QToF-MS; normalization; asthma large-scale; metabolomics; LC-QToF-MS; normalization; asthma
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Rodríguez-Coira, J.; Delgado-Dolset, M.I.; Obeso, D.; Dolores-Hernández, M.; Quintás, G.; Angulo, S.; Barber, D.; Carrillo, T.; Escribese, M.M.; Villaseñor, A. Troubleshooting in Large-Scale LC-ToF-MS Metabolomics Analysis: Solving Complex Issues in Big Cohorts. Metabolites 2019, 9, 247.

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