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Metabolic signatures of insulin resistance in non-diabetic individuals

BACKGROUND: Insulin resistance (IR) evolved from excessive energy intake and poor energy expenditure, affecting the patient's quality of life. Amino acid and acylcarnitine metabolomic profiles have identified consistent patterns associated with metabolic disease and insulin sensitivity. Here, w...

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Autores principales: Arjmand, Babak, Ebrahimi Fana, Saeed, Ghasemi, Erfan, Kazemi, Ameneh, Ghodssi-Ghassemabadi, Robabeh, Dehghanbanadaki, Hojat, Najjar, Niloufar, Kakaii, Ardeshir, Forouzanfar, Katayoon, Nasli-Esfahani, Ensieh, Farzadfar, Farshad, Larijani, Bagher, Razi, Farideh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9404631/
https://www.ncbi.nlm.nih.gov/pubmed/36002887
http://dx.doi.org/10.1186/s12902-022-01130-3
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author Arjmand, Babak
Ebrahimi Fana, Saeed
Ghasemi, Erfan
Kazemi, Ameneh
Ghodssi-Ghassemabadi, Robabeh
Dehghanbanadaki, Hojat
Najjar, Niloufar
Kakaii, Ardeshir
Forouzanfar, Katayoon
Nasli-Esfahani, Ensieh
Farzadfar, Farshad
Larijani, Bagher
Razi, Farideh
author_facet Arjmand, Babak
Ebrahimi Fana, Saeed
Ghasemi, Erfan
Kazemi, Ameneh
Ghodssi-Ghassemabadi, Robabeh
Dehghanbanadaki, Hojat
Najjar, Niloufar
Kakaii, Ardeshir
Forouzanfar, Katayoon
Nasli-Esfahani, Ensieh
Farzadfar, Farshad
Larijani, Bagher
Razi, Farideh
author_sort Arjmand, Babak
collection PubMed
description BACKGROUND: Insulin resistance (IR) evolved from excessive energy intake and poor energy expenditure, affecting the patient's quality of life. Amino acid and acylcarnitine metabolomic profiles have identified consistent patterns associated with metabolic disease and insulin sensitivity. Here, we have measured a wide array of metabolites (30 acylcarnitines and 20 amino acids) with the MS/MS and investigated the association of metabolic profile with insulin resistance. METHODS: The study population (n = 403) was randomly chosen from non-diabetic participants of the Surveillance of Risk Factors of NCDs in Iran Study (STEPS 2016). STEPS 2016 is a population-based cross-sectional study conducted periodically on adults aged 18–75 years in 30 provinces of Iran. Participants were divided into two groups according to the optimal cut-off point determined by the Youden index of HOMA-IR for the diagnosis of metabolic syndrome. Associations were investigated using regression models adjusted for age, sex, and body mass index (BMI). RESULTS: People with high IR were significantly younger, and had higher education level, BMI, waist circumference, FPG, HbA1c, ALT, triglyceride, cholesterol, non-HDL cholesterol, uric acid, and a lower HDL-C level. We observed a strong positive association of serum BCAA (valine and leucine), AAA (tyrosine, tryptophan, and phenylalanine), alanine, and C0 (free carnitine) with IR (HOMA-IR); while C18:1 (oleoyl L-carnitine) was inversely correlated with IR. CONCLUSIONS: In the present study, we identified specific metabolites linked to HOMA-IR that improved IR prediction. In summary, our study adds more evidence that a particular metabolomic profile perturbation is associated with metabolic disease and reemphasizes the significance of understanding the biochemistry and physiology which lead to these associations. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12902-022-01130-3.
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spelling pubmed-94046312022-08-26 Metabolic signatures of insulin resistance in non-diabetic individuals Arjmand, Babak Ebrahimi Fana, Saeed Ghasemi, Erfan Kazemi, Ameneh Ghodssi-Ghassemabadi, Robabeh Dehghanbanadaki, Hojat Najjar, Niloufar Kakaii, Ardeshir Forouzanfar, Katayoon Nasli-Esfahani, Ensieh Farzadfar, Farshad Larijani, Bagher Razi, Farideh BMC Endocr Disord Research BACKGROUND: Insulin resistance (IR) evolved from excessive energy intake and poor energy expenditure, affecting the patient's quality of life. Amino acid and acylcarnitine metabolomic profiles have identified consistent patterns associated with metabolic disease and insulin sensitivity. Here, we have measured a wide array of metabolites (30 acylcarnitines and 20 amino acids) with the MS/MS and investigated the association of metabolic profile with insulin resistance. METHODS: The study population (n = 403) was randomly chosen from non-diabetic participants of the Surveillance of Risk Factors of NCDs in Iran Study (STEPS 2016). STEPS 2016 is a population-based cross-sectional study conducted periodically on adults aged 18–75 years in 30 provinces of Iran. Participants were divided into two groups according to the optimal cut-off point determined by the Youden index of HOMA-IR for the diagnosis of metabolic syndrome. Associations were investigated using regression models adjusted for age, sex, and body mass index (BMI). RESULTS: People with high IR were significantly younger, and had higher education level, BMI, waist circumference, FPG, HbA1c, ALT, triglyceride, cholesterol, non-HDL cholesterol, uric acid, and a lower HDL-C level. We observed a strong positive association of serum BCAA (valine and leucine), AAA (tyrosine, tryptophan, and phenylalanine), alanine, and C0 (free carnitine) with IR (HOMA-IR); while C18:1 (oleoyl L-carnitine) was inversely correlated with IR. CONCLUSIONS: In the present study, we identified specific metabolites linked to HOMA-IR that improved IR prediction. In summary, our study adds more evidence that a particular metabolomic profile perturbation is associated with metabolic disease and reemphasizes the significance of understanding the biochemistry and physiology which lead to these associations. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12902-022-01130-3. BioMed Central 2022-08-24 /pmc/articles/PMC9404631/ /pubmed/36002887 http://dx.doi.org/10.1186/s12902-022-01130-3 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Arjmand, Babak
Ebrahimi Fana, Saeed
Ghasemi, Erfan
Kazemi, Ameneh
Ghodssi-Ghassemabadi, Robabeh
Dehghanbanadaki, Hojat
Najjar, Niloufar
Kakaii, Ardeshir
Forouzanfar, Katayoon
Nasli-Esfahani, Ensieh
Farzadfar, Farshad
Larijani, Bagher
Razi, Farideh
Metabolic signatures of insulin resistance in non-diabetic individuals
title Metabolic signatures of insulin resistance in non-diabetic individuals
title_full Metabolic signatures of insulin resistance in non-diabetic individuals
title_fullStr Metabolic signatures of insulin resistance in non-diabetic individuals
title_full_unstemmed Metabolic signatures of insulin resistance in non-diabetic individuals
title_short Metabolic signatures of insulin resistance in non-diabetic individuals
title_sort metabolic signatures of insulin resistance in non-diabetic individuals
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9404631/
https://www.ncbi.nlm.nih.gov/pubmed/36002887
http://dx.doi.org/10.1186/s12902-022-01130-3
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