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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...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2023
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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. |
format | Online Article Text |
id | pubmed-10042157 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
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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