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Baseline gene expression in subcutaneous adipose tissue predicts diet-induced weight loss in individuals with obesity

BACKGROUND: Weight loss effectively reduces cardiometabolic health risks among people with overweight and obesity, but inter-individual variability in weight loss maintenance is large. Here we studied whether baseline gene expression in subcutaneous adipose tissue predicts diet-induced weight loss s...

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Autores principales: Oghabian, Ali, van der Kolk, Birgitta W., Marttinen, Pekka, Valsesia, Armand, Langin, Dominique, Saris, W. H., Astrup, Arne, Blaak, Ellen E., Pietiläinen, Kirsi H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10042157/
https://www.ncbi.nlm.nih.gov/pubmed/36992941
http://dx.doi.org/10.7717/peerj.15100
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author Oghabian, Ali
van der Kolk, Birgitta W.
Marttinen, Pekka
Valsesia, Armand
Langin, Dominique
Saris, W. H.
Astrup, Arne
Blaak, Ellen E.
Pietiläinen, Kirsi H.
author_facet Oghabian, Ali
van der Kolk, Birgitta W.
Marttinen, Pekka
Valsesia, Armand
Langin, Dominique
Saris, W. H.
Astrup, Arne
Blaak, Ellen E.
Pietiläinen, Kirsi H.
author_sort Oghabian, Ali
collection PubMed
description BACKGROUND: Weight loss effectively reduces cardiometabolic health risks among people with overweight and obesity, but inter-individual variability in weight loss maintenance is large. Here we studied whether baseline gene expression in subcutaneous adipose tissue predicts diet-induced weight loss success. METHODS: Within the 8-month multicenter dietary intervention study DiOGenes, we classified a low weight-losers (low-WL) group and a high-WL group based on median weight loss percentage (9.9%) from 281 individuals. Using RNA sequencing, we identified the significantly differentially expressed genes between high-WL and low-WL at baseline and their enriched pathways. We used this information together with support vector machines with linear kernel to build classifier models that predict the weight loss classes. RESULTS: Prediction models based on a selection of genes that are associated with the discovered pathways ‘lipid metabolism’ (max AUC = 0.74, 95% CI [0.62–0.86]) and ‘response to virus’ (max AUC = 0.72, 95% CI [0.61–0.83]) predicted the weight-loss classes high-WL/low-WL significantly better than models based on randomly selected genes (P < 0.01). The performance of the models based on ‘response to virus’ genes is highly dependent on those genes that are also associated with lipid metabolism. Incorporation of baseline clinical factors into these models did not noticeably enhance the model performance in most of the runs. This study demonstrates that baseline adipose tissue gene expression data, together with supervised machine learning, facilitates the characterization of the determinants of successful weight loss.
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spelling pubmed-100421572023-03-28 Baseline gene expression in subcutaneous adipose tissue predicts diet-induced weight loss in individuals with obesity Oghabian, Ali van der Kolk, Birgitta W. Marttinen, Pekka Valsesia, Armand Langin, Dominique Saris, W. H. Astrup, Arne Blaak, Ellen E. Pietiläinen, Kirsi H. PeerJ Bioinformatics BACKGROUND: Weight loss effectively reduces cardiometabolic health risks among people with overweight and obesity, but inter-individual variability in weight loss maintenance is large. Here we studied whether baseline gene expression in subcutaneous adipose tissue predicts diet-induced weight loss success. METHODS: Within the 8-month multicenter dietary intervention study DiOGenes, we classified a low weight-losers (low-WL) group and a high-WL group based on median weight loss percentage (9.9%) from 281 individuals. Using RNA sequencing, we identified the significantly differentially expressed genes between high-WL and low-WL at baseline and their enriched pathways. We used this information together with support vector machines with linear kernel to build classifier models that predict the weight loss classes. RESULTS: Prediction models based on a selection of genes that are associated with the discovered pathways ‘lipid metabolism’ (max AUC = 0.74, 95% CI [0.62–0.86]) and ‘response to virus’ (max AUC = 0.72, 95% CI [0.61–0.83]) predicted the weight-loss classes high-WL/low-WL significantly better than models based on randomly selected genes (P < 0.01). The performance of the models based on ‘response to virus’ genes is highly dependent on those genes that are also associated with lipid metabolism. Incorporation of baseline clinical factors into these models did not noticeably enhance the model performance in most of the runs. This study demonstrates that baseline adipose tissue gene expression data, together with supervised machine learning, facilitates the characterization of the determinants of successful weight loss. PeerJ Inc. 2023-03-24 /pmc/articles/PMC10042157/ /pubmed/36992941 http://dx.doi.org/10.7717/peerj.15100 Text en © 2023 Oghabian et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Bioinformatics
Oghabian, Ali
van der Kolk, Birgitta W.
Marttinen, Pekka
Valsesia, Armand
Langin, Dominique
Saris, W. H.
Astrup, Arne
Blaak, Ellen E.
Pietiläinen, Kirsi H.
Baseline gene expression in subcutaneous adipose tissue predicts diet-induced weight loss in individuals with obesity
title Baseline gene expression in subcutaneous adipose tissue predicts diet-induced weight loss in individuals with obesity
title_full Baseline gene expression in subcutaneous adipose tissue predicts diet-induced weight loss in individuals with obesity
title_fullStr Baseline gene expression in subcutaneous adipose tissue predicts diet-induced weight loss in individuals with obesity
title_full_unstemmed Baseline gene expression in subcutaneous adipose tissue predicts diet-induced weight loss in individuals with obesity
title_short Baseline gene expression in subcutaneous adipose tissue predicts diet-induced weight loss in individuals with obesity
title_sort baseline gene expression in subcutaneous adipose tissue predicts diet-induced weight loss in individuals with obesity
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10042157/
https://www.ncbi.nlm.nih.gov/pubmed/36992941
http://dx.doi.org/10.7717/peerj.15100
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