Metabolic profiling for the identification of Huntington biomarkers by on-line solid-phase extraction capillary electrophoresis mass spectrometry combined with advanced data analysis tools
In this work, an untargeted metabolomic approach based on sensitive analysis by on-line solid-phase extraction capillary electrophoresis mass spectrometry (SPE-CE-MS) in combination with multivariate data analysis is proposed as an efficient method for the identification of biomarkers of Huntington's disease (HD) progression in plasma. For this purpose, plasma samples from wild-type (wt) and HD (R6/1) mice of different ages (8, 12, and 30 weeks), were analyzed by C18-SPE-CE-MS in order to obtain the characteristic electrophoretic profiles of low molecular mass compounds. Then, multivariate curve resolution alternating least squares (MCR-ALS) was applied to the multiple full scan MS datasets. This strategy permitted the resolution of a large number of metabolites being characterized by their electrophoretic peaks and their corresponding mass spectra. A total number of 29 compounds were relevant to discriminate between wt and HD plasma samples, as well as to follow-up the HD progression. The intracellular signaling was found to be the most affected metabolic pathway in HD mice after 12 weeks of birth, when mice already showed motor coordination deficiencies and cognitive decline. This fact agreed with the atrophy and dysfunction of specific neurons, loss of several types of receptors, and changed expression of neurotransmitters. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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Format: | artículo biblioteca |
Language: | English |
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Wiley-VCH
2016-03-01
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Subjects: | Biomarkers, Huntington, Metabolomics, Multivariate data analysis, SPE-CE-MS, |
Online Access: | http://hdl.handle.net/10261/133965 http://dx.doi.org/10.13039/501100000780 |
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dig-idaea-es-10261-1339652022-08-17T11:00:23Z Metabolic profiling for the identification of Huntington biomarkers by on-line solid-phase extraction capillary electrophoresis mass spectrometry combined with advanced data analysis tools Pont, Laura Benavente, Fernando Jaumot, Joaquim Tauler, Romà Alberch, Jordi Ginés, Silvia Barbosa, José Sanz-Nebot, Victoria M. European Commission Biomarkers Huntington Metabolomics Multivariate data analysis SPE-CE-MS In this work, an untargeted metabolomic approach based on sensitive analysis by on-line solid-phase extraction capillary electrophoresis mass spectrometry (SPE-CE-MS) in combination with multivariate data analysis is proposed as an efficient method for the identification of biomarkers of Huntington's disease (HD) progression in plasma. For this purpose, plasma samples from wild-type (wt) and HD (R6/1) mice of different ages (8, 12, and 30 weeks), were analyzed by C18-SPE-CE-MS in order to obtain the characteristic electrophoretic profiles of low molecular mass compounds. Then, multivariate curve resolution alternating least squares (MCR-ALS) was applied to the multiple full scan MS datasets. This strategy permitted the resolution of a large number of metabolites being characterized by their electrophoretic peaks and their corresponding mass spectra. A total number of 29 compounds were relevant to discriminate between wt and HD plasma samples, as well as to follow-up the HD progression. The intracellular signaling was found to be the most affected metabolic pathway in HD mice after 12 weeks of birth, when mice already showed motor coordination deficiencies and cognitive decline. This fact agreed with the atrophy and dysfunction of specific neurons, loss of several types of receptors, and changed expression of neurotransmitters. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim. Laura Pont acknowledges the Spanish Ministry of Economy and Competitiveness for a FPI fellowship. This study was supported by a grant from the Spanish Ministry of Education and Science (CTQ2011-27130). Part of the study was supported by the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement n. 320737. We also thank Josep Maria Marimón for the blood sample collection. Peer reviewed 2016-06-23T08:52:04Z 2016-06-23T08:52:04Z 2016-03-01 artículo http://purl.org/coar/resource_type/c_6501 Electrophoresis 37(5-6): 795-808(2016) http://hdl.handle.net/10261/133965 10.1002/elps.201500378 http://dx.doi.org/10.13039/501100000780 en #PLACEHOLDER_PARENT_METADATA_VALUE# info:eu-repo/grantAgreement/EC/FP7/320737 Postprint http://dx.doi.org/10.1002/elps.201500378 Sí open Wiley-VCH |
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Biomarkers Huntington Metabolomics Multivariate data analysis SPE-CE-MS Biomarkers Huntington Metabolomics Multivariate data analysis SPE-CE-MS |
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Biomarkers Huntington Metabolomics Multivariate data analysis SPE-CE-MS Biomarkers Huntington Metabolomics Multivariate data analysis SPE-CE-MS Pont, Laura Benavente, Fernando Jaumot, Joaquim Tauler, Romà Alberch, Jordi Ginés, Silvia Barbosa, José Sanz-Nebot, Victoria M. Metabolic profiling for the identification of Huntington biomarkers by on-line solid-phase extraction capillary electrophoresis mass spectrometry combined with advanced data analysis tools |
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In this work, an untargeted metabolomic approach based on sensitive analysis by on-line solid-phase extraction capillary electrophoresis mass spectrometry (SPE-CE-MS) in combination with multivariate data analysis is proposed as an efficient method for the identification of biomarkers of Huntington's disease (HD) progression in plasma. For this purpose, plasma samples from wild-type (wt) and HD (R6/1) mice of different ages (8, 12, and 30 weeks), were analyzed by C18-SPE-CE-MS in order to obtain the characteristic electrophoretic profiles of low molecular mass compounds. Then, multivariate curve resolution alternating least squares (MCR-ALS) was applied to the multiple full scan MS datasets. This strategy permitted the resolution of a large number of metabolites being characterized by their electrophoretic peaks and their corresponding mass spectra. A total number of 29 compounds were relevant to discriminate between wt and HD plasma samples, as well as to follow-up the HD progression. The intracellular signaling was found to be the most affected metabolic pathway in HD mice after 12 weeks of birth, when mice already showed motor coordination deficiencies and cognitive decline. This fact agreed with the atrophy and dysfunction of specific neurons, loss of several types of receptors, and changed expression of neurotransmitters. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim. |
author2 |
European Commission |
author_facet |
European Commission Pont, Laura Benavente, Fernando Jaumot, Joaquim Tauler, Romà Alberch, Jordi Ginés, Silvia Barbosa, José Sanz-Nebot, Victoria M. |
format |
artículo |
topic_facet |
Biomarkers Huntington Metabolomics Multivariate data analysis SPE-CE-MS |
author |
Pont, Laura Benavente, Fernando Jaumot, Joaquim Tauler, Romà Alberch, Jordi Ginés, Silvia Barbosa, José Sanz-Nebot, Victoria M. |
author_sort |
Pont, Laura |
title |
Metabolic profiling for the identification of Huntington biomarkers by on-line solid-phase extraction capillary electrophoresis mass spectrometry combined with advanced data analysis tools |
title_short |
Metabolic profiling for the identification of Huntington biomarkers by on-line solid-phase extraction capillary electrophoresis mass spectrometry combined with advanced data analysis tools |
title_full |
Metabolic profiling for the identification of Huntington biomarkers by on-line solid-phase extraction capillary electrophoresis mass spectrometry combined with advanced data analysis tools |
title_fullStr |
Metabolic profiling for the identification of Huntington biomarkers by on-line solid-phase extraction capillary electrophoresis mass spectrometry combined with advanced data analysis tools |
title_full_unstemmed |
Metabolic profiling for the identification of Huntington biomarkers by on-line solid-phase extraction capillary electrophoresis mass spectrometry combined with advanced data analysis tools |
title_sort |
metabolic profiling for the identification of huntington biomarkers by on-line solid-phase extraction capillary electrophoresis mass spectrometry combined with advanced data analysis tools |
publisher |
Wiley-VCH |
publishDate |
2016-03-01 |
url |
http://hdl.handle.net/10261/133965 http://dx.doi.org/10.13039/501100000780 |
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