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Identification of Insulin Resistance Biomarkers in Metabolic Syndrome Detected by UHPLC-ESI-QTOF-MS

Metabolic syndrome (MetS) is a disorder characterized by a group of factors that can increase the risk of chronic diseases, including cardiovascular diseases and type 2 diabetes mellitus (T2D). Metabolomics has provided new insight into disease diagnosis and biomarker identification. This cross-sect...

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Autores principales: Alsoud, Leen Oyoun, Soares, Nelson C., Al-Hroub, Hamza M., Mousa, Muath, Kasabri, Violet, Bulatova, Nailya, Suyagh, Maysa, Alzoubi, Karem H., El-Huneidi, Waseem, Abu-Irmaileh, Bashaer, Bustanji, Yasser, Semreen, Mohammad H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9227428/
https://www.ncbi.nlm.nih.gov/pubmed/35736441
http://dx.doi.org/10.3390/metabo12060508
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author Alsoud, Leen Oyoun
Soares, Nelson C.
Al-Hroub, Hamza M.
Mousa, Muath
Kasabri, Violet
Bulatova, Nailya
Suyagh, Maysa
Alzoubi, Karem H.
El-Huneidi, Waseem
Abu-Irmaileh, Bashaer
Bustanji, Yasser
Semreen, Mohammad H.
author_facet Alsoud, Leen Oyoun
Soares, Nelson C.
Al-Hroub, Hamza M.
Mousa, Muath
Kasabri, Violet
Bulatova, Nailya
Suyagh, Maysa
Alzoubi, Karem H.
El-Huneidi, Waseem
Abu-Irmaileh, Bashaer
Bustanji, Yasser
Semreen, Mohammad H.
author_sort Alsoud, Leen Oyoun
collection PubMed
description Metabolic syndrome (MetS) is a disorder characterized by a group of factors that can increase the risk of chronic diseases, including cardiovascular diseases and type 2 diabetes mellitus (T2D). Metabolomics has provided new insight into disease diagnosis and biomarker identification. This cross-sectional investigation used an untargeted metabolomics-based technique to uncover metabolomic alterations and their relationship to pathways in normoglycemic and prediabetic MetS participants to improve disease diagnosis. Plasma samples were collected from drug-naive prediabetic MetS patients (n = 26), normoglycemic MetS patients (n = 30), and healthy (normoglycemic lean) subjects (n = 30) who met the inclusion criteria for the study. The plasma samples were analyzed using highly sensitive ultra-high-performance liquid chromatography electrospray ionization quadrupole time-of-flight mass spectrometry (UHPLC-ESI-QTOF-MS). One-way ANOVA analysis revealed that 59 metabolites differed significantly among the three groups (p < 0.05). Glutamine, 5-hydroxy-L-tryptophan, L-sorbose, and hippurate were highly associated with MetS. However, 9-methyluric acid, sphinganine, and threonic acid were highly associated with prediabetes/MetS. Metabolic pathway analysis showed that arginine biosynthesis and glutathione metabolism were associated with MetS/prediabetes, while phenylalanine, D-glutamine and D-glutamate, and lysine degradation were highly impacted in MetS. The current study sheds light on the potential diagnostic value of some metabolites in metabolic syndrome and the role of their alteration on some of the metabolic pathways. More studies are needed in larger cohorts in order to verify the implication of the above metabolites on MetS and their diagnostic value.
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spelling pubmed-92274282022-06-25 Identification of Insulin Resistance Biomarkers in Metabolic Syndrome Detected by UHPLC-ESI-QTOF-MS Alsoud, Leen Oyoun Soares, Nelson C. Al-Hroub, Hamza M. Mousa, Muath Kasabri, Violet Bulatova, Nailya Suyagh, Maysa Alzoubi, Karem H. El-Huneidi, Waseem Abu-Irmaileh, Bashaer Bustanji, Yasser Semreen, Mohammad H. Metabolites Article Metabolic syndrome (MetS) is a disorder characterized by a group of factors that can increase the risk of chronic diseases, including cardiovascular diseases and type 2 diabetes mellitus (T2D). Metabolomics has provided new insight into disease diagnosis and biomarker identification. This cross-sectional investigation used an untargeted metabolomics-based technique to uncover metabolomic alterations and their relationship to pathways in normoglycemic and prediabetic MetS participants to improve disease diagnosis. Plasma samples were collected from drug-naive prediabetic MetS patients (n = 26), normoglycemic MetS patients (n = 30), and healthy (normoglycemic lean) subjects (n = 30) who met the inclusion criteria for the study. The plasma samples were analyzed using highly sensitive ultra-high-performance liquid chromatography electrospray ionization quadrupole time-of-flight mass spectrometry (UHPLC-ESI-QTOF-MS). One-way ANOVA analysis revealed that 59 metabolites differed significantly among the three groups (p < 0.05). Glutamine, 5-hydroxy-L-tryptophan, L-sorbose, and hippurate were highly associated with MetS. However, 9-methyluric acid, sphinganine, and threonic acid were highly associated with prediabetes/MetS. Metabolic pathway analysis showed that arginine biosynthesis and glutathione metabolism were associated with MetS/prediabetes, while phenylalanine, D-glutamine and D-glutamate, and lysine degradation were highly impacted in MetS. The current study sheds light on the potential diagnostic value of some metabolites in metabolic syndrome and the role of their alteration on some of the metabolic pathways. More studies are needed in larger cohorts in order to verify the implication of the above metabolites on MetS and their diagnostic value. MDPI 2022-06-01 /pmc/articles/PMC9227428/ /pubmed/35736441 http://dx.doi.org/10.3390/metabo12060508 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
Alsoud, Leen Oyoun
Soares, Nelson C.
Al-Hroub, Hamza M.
Mousa, Muath
Kasabri, Violet
Bulatova, Nailya
Suyagh, Maysa
Alzoubi, Karem H.
El-Huneidi, Waseem
Abu-Irmaileh, Bashaer
Bustanji, Yasser
Semreen, Mohammad H.
Identification of Insulin Resistance Biomarkers in Metabolic Syndrome Detected by UHPLC-ESI-QTOF-MS
title Identification of Insulin Resistance Biomarkers in Metabolic Syndrome Detected by UHPLC-ESI-QTOF-MS
title_full Identification of Insulin Resistance Biomarkers in Metabolic Syndrome Detected by UHPLC-ESI-QTOF-MS
title_fullStr Identification of Insulin Resistance Biomarkers in Metabolic Syndrome Detected by UHPLC-ESI-QTOF-MS
title_full_unstemmed Identification of Insulin Resistance Biomarkers in Metabolic Syndrome Detected by UHPLC-ESI-QTOF-MS
title_short Identification of Insulin Resistance Biomarkers in Metabolic Syndrome Detected by UHPLC-ESI-QTOF-MS
title_sort identification of insulin resistance biomarkers in metabolic syndrome detected by uhplc-esi-qtof-ms
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9227428/
https://www.ncbi.nlm.nih.gov/pubmed/35736441
http://dx.doi.org/10.3390/metabo12060508
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