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Development of a Novel Targeted Metabolomic LC-QqQ-MS Method in Allergic Inflammation
The transition from mild to severe allergic phenotypes is still poorly understood and there is an urgent need of incorporating new therapies, accompanied by personalized diagnosis approaches. This work presents the development of a novel targeted metabolomic methodology for the analysis of 36 metabo...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9319984/ https://www.ncbi.nlm.nih.gov/pubmed/35888716 http://dx.doi.org/10.3390/metabo12070592 |
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author | Obeso, David Contreras, Nuria Dolores-Hernández, Mariana Carrillo, Teresa Barbas, Coral Escribese, María M. Villaseñor, Alma Barber, Domingo |
author_facet | Obeso, David Contreras, Nuria Dolores-Hernández, Mariana Carrillo, Teresa Barbas, Coral Escribese, María M. Villaseñor, Alma Barber, Domingo |
author_sort | Obeso, David |
collection | PubMed |
description | The transition from mild to severe allergic phenotypes is still poorly understood and there is an urgent need of incorporating new therapies, accompanied by personalized diagnosis approaches. This work presents the development of a novel targeted metabolomic methodology for the analysis of 36 metabolites related to allergic inflammation, including mostly sphingolipids, lysophospholipids, amino acids, and those of energy metabolism previously identified in non-targeted studies. The methodology consisted of two complementary chromatography methods, HILIC and reversed-phase. These were developed using liquid chromatography, coupled to triple quadrupole mass spectrometry (LC-QqQ-MS) in dynamic multiple reaction monitoring (dMRM) acquisition mode and were validated using ICH guidelines. Serum samples from two clinical models of allergic asthma patients were used for method application, which were as follows: (1) corticosteroid-controlled (ICS, n = 6) versus uncontrolled (UC, n = 4) patients, and immunotherapy-controlled (IT, n = 23) versus biologicals-controlled (BIO, n = 12) patients. The results showed significant differences mainly in lysophospholipids using univariate analyses in both models. Multivariate analysis for model 1 was able to distinguish both groups, while for model 2, the results showed the correct classification of all BIO samples within their group. Thus, this methodology can be of great importance for further understanding the role of these metabolites in allergic diseases as potential biomarkers for disease severity and for predicting patient treatment response. |
format | Online Article Text |
id | pubmed-9319984 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-93199842022-07-27 Development of a Novel Targeted Metabolomic LC-QqQ-MS Method in Allergic Inflammation Obeso, David Contreras, Nuria Dolores-Hernández, Mariana Carrillo, Teresa Barbas, Coral Escribese, María M. Villaseñor, Alma Barber, Domingo Metabolites Article The transition from mild to severe allergic phenotypes is still poorly understood and there is an urgent need of incorporating new therapies, accompanied by personalized diagnosis approaches. This work presents the development of a novel targeted metabolomic methodology for the analysis of 36 metabolites related to allergic inflammation, including mostly sphingolipids, lysophospholipids, amino acids, and those of energy metabolism previously identified in non-targeted studies. The methodology consisted of two complementary chromatography methods, HILIC and reversed-phase. These were developed using liquid chromatography, coupled to triple quadrupole mass spectrometry (LC-QqQ-MS) in dynamic multiple reaction monitoring (dMRM) acquisition mode and were validated using ICH guidelines. Serum samples from two clinical models of allergic asthma patients were used for method application, which were as follows: (1) corticosteroid-controlled (ICS, n = 6) versus uncontrolled (UC, n = 4) patients, and immunotherapy-controlled (IT, n = 23) versus biologicals-controlled (BIO, n = 12) patients. The results showed significant differences mainly in lysophospholipids using univariate analyses in both models. Multivariate analysis for model 1 was able to distinguish both groups, while for model 2, the results showed the correct classification of all BIO samples within their group. Thus, this methodology can be of great importance for further understanding the role of these metabolites in allergic diseases as potential biomarkers for disease severity and for predicting patient treatment response. MDPI 2022-06-25 /pmc/articles/PMC9319984/ /pubmed/35888716 http://dx.doi.org/10.3390/metabo12070592 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Obeso, David Contreras, Nuria Dolores-Hernández, Mariana Carrillo, Teresa Barbas, Coral Escribese, María M. Villaseñor, Alma Barber, Domingo Development of a Novel Targeted Metabolomic LC-QqQ-MS Method in Allergic Inflammation |
title | Development of a Novel Targeted Metabolomic LC-QqQ-MS Method in Allergic Inflammation |
title_full | Development of a Novel Targeted Metabolomic LC-QqQ-MS Method in Allergic Inflammation |
title_fullStr | Development of a Novel Targeted Metabolomic LC-QqQ-MS Method in Allergic Inflammation |
title_full_unstemmed | Development of a Novel Targeted Metabolomic LC-QqQ-MS Method in Allergic Inflammation |
title_short | Development of a Novel Targeted Metabolomic LC-QqQ-MS Method in Allergic Inflammation |
title_sort | development of a novel targeted metabolomic lc-qqq-ms method in allergic inflammation |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9319984/ https://www.ncbi.nlm.nih.gov/pubmed/35888716 http://dx.doi.org/10.3390/metabo12070592 |
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