Adipose tissue morphology, imaging and metabolomics predicting cardiometabolic risk and family history of type 2 diabetes in non-obese men

We evaluated the importance of body composition, amount of subcutaneous and visceral fat, liver and heart ectopic fat, adipose tissue distribution and cell size as predictors of cardio-metabolic risk in 53 non-obese male individuals. Known family history of type 2 diabetes was identified in 25 indiv...

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Autores principales: Rawshani, Aidin, Eliasson, Björn, Rawshani, Araz, Henninger, Josefin, Mardinoglu, Adil, Carlsson, Åsa, Sohlin, Maja, Ljungberg, Maria, Hammarstedt, Ann, Rosengren, Annika, Smith, Ulf
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
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Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7305301/
https://www.ncbi.nlm.nih.gov/pubmed/32561768
http://dx.doi.org/10.1038/s41598-020-66199-z
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author Rawshani, Aidin
Eliasson, Björn
Rawshani, Araz
Henninger, Josefin
Mardinoglu, Adil
Carlsson, Åsa
Sohlin, Maja
Ljungberg, Maria
Hammarstedt, Ann
Rosengren, Annika
Smith, Ulf
author_facet Rawshani, Aidin
Eliasson, Björn
Rawshani, Araz
Henninger, Josefin
Mardinoglu, Adil
Carlsson, Åsa
Sohlin, Maja
Ljungberg, Maria
Hammarstedt, Ann
Rosengren, Annika
Smith, Ulf
author_sort Rawshani, Aidin
collection PubMed
description We evaluated the importance of body composition, amount of subcutaneous and visceral fat, liver and heart ectopic fat, adipose tissue distribution and cell size as predictors of cardio-metabolic risk in 53 non-obese male individuals. Known family history of type 2 diabetes was identified in 25 individuals. The participants also underwent extensive phenotyping together with measuring different biomarkers and non-targeted serum metabolomics. We used ensemble learning and other machine learning approaches to identify predictors with considerable relative importance and their intricate interactions. Visceral fat and age were strong individual predictors of ectopic fat accumulation in liver and heart along with markers of lipid oxidation and reduced glucose tolerance. Subcutaneous adipose cell size was the strongest individual predictor of whole-body insulin sensitivity and also a marker of visceral and ectopic fat accumulation. The metabolite 3-MOB along with related branched-chain amino acids demonstrated strong predictability for family history of type 2 diabetes.
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spelling pubmed-73053012020-06-23 Adipose tissue morphology, imaging and metabolomics predicting cardiometabolic risk and family history of type 2 diabetes in non-obese men Rawshani, Aidin Eliasson, Björn Rawshani, Araz Henninger, Josefin Mardinoglu, Adil Carlsson, Åsa Sohlin, Maja Ljungberg, Maria Hammarstedt, Ann Rosengren, Annika Smith, Ulf Sci Rep Article We evaluated the importance of body composition, amount of subcutaneous and visceral fat, liver and heart ectopic fat, adipose tissue distribution and cell size as predictors of cardio-metabolic risk in 53 non-obese male individuals. Known family history of type 2 diabetes was identified in 25 individuals. The participants also underwent extensive phenotyping together with measuring different biomarkers and non-targeted serum metabolomics. We used ensemble learning and other machine learning approaches to identify predictors with considerable relative importance and their intricate interactions. Visceral fat and age were strong individual predictors of ectopic fat accumulation in liver and heart along with markers of lipid oxidation and reduced glucose tolerance. Subcutaneous adipose cell size was the strongest individual predictor of whole-body insulin sensitivity and also a marker of visceral and ectopic fat accumulation. The metabolite 3-MOB along with related branched-chain amino acids demonstrated strong predictability for family history of type 2 diabetes. Nature Publishing Group UK 2020-06-19 /pmc/articles/PMC7305301/ /pubmed/32561768 http://dx.doi.org/10.1038/s41598-020-66199-z 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
Rawshani, Aidin
Eliasson, Björn
Rawshani, Araz
Henninger, Josefin
Mardinoglu, Adil
Carlsson, Åsa
Sohlin, Maja
Ljungberg, Maria
Hammarstedt, Ann
Rosengren, Annika
Smith, Ulf
Adipose tissue morphology, imaging and metabolomics predicting cardiometabolic risk and family history of type 2 diabetes in non-obese men
title Adipose tissue morphology, imaging and metabolomics predicting cardiometabolic risk and family history of type 2 diabetes in non-obese men
title_full Adipose tissue morphology, imaging and metabolomics predicting cardiometabolic risk and family history of type 2 diabetes in non-obese men
title_fullStr Adipose tissue morphology, imaging and metabolomics predicting cardiometabolic risk and family history of type 2 diabetes in non-obese men
title_full_unstemmed Adipose tissue morphology, imaging and metabolomics predicting cardiometabolic risk and family history of type 2 diabetes in non-obese men
title_short Adipose tissue morphology, imaging and metabolomics predicting cardiometabolic risk and family history of type 2 diabetes in non-obese men
title_sort adipose tissue morphology, imaging and metabolomics predicting cardiometabolic risk and family history of type 2 diabetes in non-obese men
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7305301/
https://www.ncbi.nlm.nih.gov/pubmed/32561768
http://dx.doi.org/10.1038/s41598-020-66199-z
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