Cargando…

Profiling Cellular Processes in Adipose Tissue during Weight Loss Using Time Series Gene Expression

Obesity is a global epidemic identified as a major risk factor for multiple chronic diseases and, consequently, diet-induced weight loss is used to counter obesity. The adipose tissue is the primary tissue affected in diet-induced weight loss, yet the underlying molecular mechanisms and changes are...

Descripción completa

Detalles Bibliográficos
Autores principales: Tareen, Samar H. K., Adriaens, Michiel E., Arts, Ilja C. W., de Kok, Theo M., Vink, Roel G., Roumans, Nadia J. T., van Baak, Marleen A., Mariman, Edwin C. M., Evelo, Chris T., Kutmon, Martina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6266822/
https://www.ncbi.nlm.nih.gov/pubmed/30380678
http://dx.doi.org/10.3390/genes9110525
_version_ 1783375927285121024
author Tareen, Samar H. K.
Adriaens, Michiel E.
Arts, Ilja C. W.
de Kok, Theo M.
Vink, Roel G.
Roumans, Nadia J. T.
van Baak, Marleen A.
Mariman, Edwin C. M.
Evelo, Chris T.
Kutmon, Martina
author_facet Tareen, Samar H. K.
Adriaens, Michiel E.
Arts, Ilja C. W.
de Kok, Theo M.
Vink, Roel G.
Roumans, Nadia J. T.
van Baak, Marleen A.
Mariman, Edwin C. M.
Evelo, Chris T.
Kutmon, Martina
author_sort Tareen, Samar H. K.
collection PubMed
description Obesity is a global epidemic identified as a major risk factor for multiple chronic diseases and, consequently, diet-induced weight loss is used to counter obesity. The adipose tissue is the primary tissue affected in diet-induced weight loss, yet the underlying molecular mechanisms and changes are not completely deciphered. In this study, we present a network biology analysis workflow which enables the profiling of the cellular processes affected by weight loss in the subcutaneous adipose tissue. Time series gene expression data from a dietary intervention dataset with two diets was analysed. Differentially expressed genes were used to generate co-expression networks using a method that capitalises on the repeat measurements in the data and finds correlations between gene expression changes over time. Using the network analysis tool Cytoscape, an overlap network of conserved components in the co-expression networks was constructed, clustered on topology to find densely correlated genes, and analysed using Gene Ontology enrichment analysis. We found five clusters involved in key metabolic processes, but also adipose tissue development and tissue remodelling processes were enriched. In conclusion, we present a flexible network biology workflow for finding important processes and relevant genes associated with weight loss, using a time series co-expression network approach that is robust towards the high inter-individual variation in humans.
format Online
Article
Text
id pubmed-6266822
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-62668222018-12-13 Profiling Cellular Processes in Adipose Tissue during Weight Loss Using Time Series Gene Expression Tareen, Samar H. K. Adriaens, Michiel E. Arts, Ilja C. W. de Kok, Theo M. Vink, Roel G. Roumans, Nadia J. T. van Baak, Marleen A. Mariman, Edwin C. M. Evelo, Chris T. Kutmon, Martina Genes (Basel) Article Obesity is a global epidemic identified as a major risk factor for multiple chronic diseases and, consequently, diet-induced weight loss is used to counter obesity. The adipose tissue is the primary tissue affected in diet-induced weight loss, yet the underlying molecular mechanisms and changes are not completely deciphered. In this study, we present a network biology analysis workflow which enables the profiling of the cellular processes affected by weight loss in the subcutaneous adipose tissue. Time series gene expression data from a dietary intervention dataset with two diets was analysed. Differentially expressed genes were used to generate co-expression networks using a method that capitalises on the repeat measurements in the data and finds correlations between gene expression changes over time. Using the network analysis tool Cytoscape, an overlap network of conserved components in the co-expression networks was constructed, clustered on topology to find densely correlated genes, and analysed using Gene Ontology enrichment analysis. We found five clusters involved in key metabolic processes, but also adipose tissue development and tissue remodelling processes were enriched. In conclusion, we present a flexible network biology workflow for finding important processes and relevant genes associated with weight loss, using a time series co-expression network approach that is robust towards the high inter-individual variation in humans. MDPI 2018-10-29 /pmc/articles/PMC6266822/ /pubmed/30380678 http://dx.doi.org/10.3390/genes9110525 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Tareen, Samar H. K.
Adriaens, Michiel E.
Arts, Ilja C. W.
de Kok, Theo M.
Vink, Roel G.
Roumans, Nadia J. T.
van Baak, Marleen A.
Mariman, Edwin C. M.
Evelo, Chris T.
Kutmon, Martina
Profiling Cellular Processes in Adipose Tissue during Weight Loss Using Time Series Gene Expression
title Profiling Cellular Processes in Adipose Tissue during Weight Loss Using Time Series Gene Expression
title_full Profiling Cellular Processes in Adipose Tissue during Weight Loss Using Time Series Gene Expression
title_fullStr Profiling Cellular Processes in Adipose Tissue during Weight Loss Using Time Series Gene Expression
title_full_unstemmed Profiling Cellular Processes in Adipose Tissue during Weight Loss Using Time Series Gene Expression
title_short Profiling Cellular Processes in Adipose Tissue during Weight Loss Using Time Series Gene Expression
title_sort profiling cellular processes in adipose tissue during weight loss using time series gene expression
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6266822/
https://www.ncbi.nlm.nih.gov/pubmed/30380678
http://dx.doi.org/10.3390/genes9110525
work_keys_str_mv AT tareensamarhk profilingcellularprocessesinadiposetissueduringweightlossusingtimeseriesgeneexpression
AT adriaensmichiele profilingcellularprocessesinadiposetissueduringweightlossusingtimeseriesgeneexpression
AT artsiljacw profilingcellularprocessesinadiposetissueduringweightlossusingtimeseriesgeneexpression
AT dekoktheom profilingcellularprocessesinadiposetissueduringweightlossusingtimeseriesgeneexpression
AT vinkroelg profilingcellularprocessesinadiposetissueduringweightlossusingtimeseriesgeneexpression
AT roumansnadiajt profilingcellularprocessesinadiposetissueduringweightlossusingtimeseriesgeneexpression
AT vanbaakmarleena profilingcellularprocessesinadiposetissueduringweightlossusingtimeseriesgeneexpression
AT marimanedwincm profilingcellularprocessesinadiposetissueduringweightlossusingtimeseriesgeneexpression
AT evelochrist profilingcellularprocessesinadiposetissueduringweightlossusingtimeseriesgeneexpression
AT kutmonmartina profilingcellularprocessesinadiposetissueduringweightlossusingtimeseriesgeneexpression