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Integration of whole-body [(18)F]FDG PET/MRI with non-targeted metabolomics can provide new insights on tissue-specific insulin resistance in type 2 diabetes

Alteration of various metabolites has been linked to type 2 diabetes (T2D) and insulin resistance. However, identifying significant associations between metabolites and tissue-specific phenotypes requires a multi-omics approach. In a cohort of 42 subjects with different levels of glucose tolerance (...

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Autores principales: Diamanti, Klev, Visvanathar, Robin, Pereira, Maria J., Cavalli, Marco, Pan, Gang, Kumar, Chanchal, Skrtic, Stanko, Risérus, Ulf, Eriksson, Jan W., Kullberg, Joel, Komorowski, Jan, Wadelius, Claes, Ahlström, Håkan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7239946/
https://www.ncbi.nlm.nih.gov/pubmed/32433479
http://dx.doi.org/10.1038/s41598-020-64524-0
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author Diamanti, Klev
Visvanathar, Robin
Pereira, Maria J.
Cavalli, Marco
Pan, Gang
Kumar, Chanchal
Skrtic, Stanko
Risérus, Ulf
Eriksson, Jan W.
Kullberg, Joel
Komorowski, Jan
Wadelius, Claes
Ahlström, Håkan
author_facet Diamanti, Klev
Visvanathar, Robin
Pereira, Maria J.
Cavalli, Marco
Pan, Gang
Kumar, Chanchal
Skrtic, Stanko
Risérus, Ulf
Eriksson, Jan W.
Kullberg, Joel
Komorowski, Jan
Wadelius, Claes
Ahlström, Håkan
author_sort Diamanti, Klev
collection PubMed
description Alteration of various metabolites has been linked to type 2 diabetes (T2D) and insulin resistance. However, identifying significant associations between metabolites and tissue-specific phenotypes requires a multi-omics approach. In a cohort of 42 subjects with different levels of glucose tolerance (normal, prediabetes and T2D) matched for age and body mass index, we calculated associations between parameters of whole-body positron emission tomography (PET)/magnetic resonance imaging (MRI) during hyperinsulinemic euglycemic clamp and non-targeted metabolomics profiling for subcutaneous adipose tissue (SAT) and plasma. Plasma metabolomics profiling revealed that hepatic fat content was positively associated with tyrosine, and negatively associated with lysoPC(P-16:0). Visceral adipose tissue (VAT) and SAT insulin sensitivity (K(i)), were positively associated with several lysophospholipids, while the opposite applied to branched-chain amino acids. The adipose tissue metabolomics revealed a positive association between non-esterified fatty acids and, VAT and liver K(i). Bile acids and carnitines in adipose tissue were inversely associated with VAT K(i). Furthermore, we detected several metabolites that were significantly higher in T2D than normal/prediabetes. In this study we present novel associations between several metabolites from SAT and plasma with the fat fraction, volume and insulin sensitivity of various tissues throughout the body, demonstrating the benefit of an integrative multi-omics approach.
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spelling pubmed-72399462020-05-29 Integration of whole-body [(18)F]FDG PET/MRI with non-targeted metabolomics can provide new insights on tissue-specific insulin resistance in type 2 diabetes Diamanti, Klev Visvanathar, Robin Pereira, Maria J. Cavalli, Marco Pan, Gang Kumar, Chanchal Skrtic, Stanko Risérus, Ulf Eriksson, Jan W. Kullberg, Joel Komorowski, Jan Wadelius, Claes Ahlström, Håkan Sci Rep Article Alteration of various metabolites has been linked to type 2 diabetes (T2D) and insulin resistance. However, identifying significant associations between metabolites and tissue-specific phenotypes requires a multi-omics approach. In a cohort of 42 subjects with different levels of glucose tolerance (normal, prediabetes and T2D) matched for age and body mass index, we calculated associations between parameters of whole-body positron emission tomography (PET)/magnetic resonance imaging (MRI) during hyperinsulinemic euglycemic clamp and non-targeted metabolomics profiling for subcutaneous adipose tissue (SAT) and plasma. Plasma metabolomics profiling revealed that hepatic fat content was positively associated with tyrosine, and negatively associated with lysoPC(P-16:0). Visceral adipose tissue (VAT) and SAT insulin sensitivity (K(i)), were positively associated with several lysophospholipids, while the opposite applied to branched-chain amino acids. The adipose tissue metabolomics revealed a positive association between non-esterified fatty acids and, VAT and liver K(i). Bile acids and carnitines in adipose tissue were inversely associated with VAT K(i). Furthermore, we detected several metabolites that were significantly higher in T2D than normal/prediabetes. In this study we present novel associations between several metabolites from SAT and plasma with the fat fraction, volume and insulin sensitivity of various tissues throughout the body, demonstrating the benefit of an integrative multi-omics approach. Nature Publishing Group UK 2020-05-20 /pmc/articles/PMC7239946/ /pubmed/32433479 http://dx.doi.org/10.1038/s41598-020-64524-0 Text en © The Author(s) 2020 Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Diamanti, Klev
Visvanathar, Robin
Pereira, Maria J.
Cavalli, Marco
Pan, Gang
Kumar, Chanchal
Skrtic, Stanko
Risérus, Ulf
Eriksson, Jan W.
Kullberg, Joel
Komorowski, Jan
Wadelius, Claes
Ahlström, Håkan
Integration of whole-body [(18)F]FDG PET/MRI with non-targeted metabolomics can provide new insights on tissue-specific insulin resistance in type 2 diabetes
title Integration of whole-body [(18)F]FDG PET/MRI with non-targeted metabolomics can provide new insights on tissue-specific insulin resistance in type 2 diabetes
title_full Integration of whole-body [(18)F]FDG PET/MRI with non-targeted metabolomics can provide new insights on tissue-specific insulin resistance in type 2 diabetes
title_fullStr Integration of whole-body [(18)F]FDG PET/MRI with non-targeted metabolomics can provide new insights on tissue-specific insulin resistance in type 2 diabetes
title_full_unstemmed Integration of whole-body [(18)F]FDG PET/MRI with non-targeted metabolomics can provide new insights on tissue-specific insulin resistance in type 2 diabetes
title_short Integration of whole-body [(18)F]FDG PET/MRI with non-targeted metabolomics can provide new insights on tissue-specific insulin resistance in type 2 diabetes
title_sort integration of whole-body [(18)f]fdg pet/mri with non-targeted metabolomics can provide new insights on tissue-specific insulin resistance in type 2 diabetes
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7239946/
https://www.ncbi.nlm.nih.gov/pubmed/32433479
http://dx.doi.org/10.1038/s41598-020-64524-0
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