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Deciphering the Relationship between Obesity and Various Diseases from a Network Perspective

The number of obesity cases is rapidly increasing in developed and developing countries, thereby causing significant health problems worldwide. The pathologic factors of obesity at the molecular level are not fully characterized, although the imbalance between energy intake and consumption is widely...

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Autores principales: Chen, Lei, Zhang, Yu-Hang, Li, JiaRui, Wang, ShaoPeng, Zhang, YunHua, Huang, Tao, Cai, Yu-Dong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5748710/
https://www.ncbi.nlm.nih.gov/pubmed/29258237
http://dx.doi.org/10.3390/genes8120392
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author Chen, Lei
Zhang, Yu-Hang
Li, JiaRui
Wang, ShaoPeng
Zhang, YunHua
Huang, Tao
Cai, Yu-Dong
author_facet Chen, Lei
Zhang, Yu-Hang
Li, JiaRui
Wang, ShaoPeng
Zhang, YunHua
Huang, Tao
Cai, Yu-Dong
author_sort Chen, Lei
collection PubMed
description The number of obesity cases is rapidly increasing in developed and developing countries, thereby causing significant health problems worldwide. The pathologic factors of obesity at the molecular level are not fully characterized, although the imbalance between energy intake and consumption is widely recognized as the main reason for fat accumulation. Previous studies reported that obesity can be caused by the dysfunction of genes associated with other diseases, such as myocardial infarction, hence providing new insights into dissecting the pathogenesis of obesity by investigating its associations with other diseases. In this study, we investigated the relationship between obesity and diseases from Online Mendelian Inheritance in Man (OMIM) databases on the protein–protein interaction (PPI) network. The obesity genes and genes of one OMIM disease were mapped onto the network, and the interaction scores between the two gene sets were investigated on the basis of the PPI of individual gene pairs, thereby inferring the relationship between obesity and this disease. Results suggested that diseases related to nutrition and endocrine are the top two diseases that are closely associated with obesity. This finding is consistent with our general knowledge and indicates the reliability of our obtained results. Moreover, we inferred that diseases related to psychiatric factors and bone may also be highly related to obesity because the two diseases followed the diseases related to nutrition and endocrine according to our results. Numerous obesity–disease associations were identified in the literature to confirm the relationships between obesity and the aforementioned four diseases. These new results may help understand the underlying molecular mechanisms of obesity–disease co-occurrence and provide useful insights for disease prevention and intervention.
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spelling pubmed-57487102018-01-07 Deciphering the Relationship between Obesity and Various Diseases from a Network Perspective Chen, Lei Zhang, Yu-Hang Li, JiaRui Wang, ShaoPeng Zhang, YunHua Huang, Tao Cai, Yu-Dong Genes (Basel) Article The number of obesity cases is rapidly increasing in developed and developing countries, thereby causing significant health problems worldwide. The pathologic factors of obesity at the molecular level are not fully characterized, although the imbalance between energy intake and consumption is widely recognized as the main reason for fat accumulation. Previous studies reported that obesity can be caused by the dysfunction of genes associated with other diseases, such as myocardial infarction, hence providing new insights into dissecting the pathogenesis of obesity by investigating its associations with other diseases. In this study, we investigated the relationship between obesity and diseases from Online Mendelian Inheritance in Man (OMIM) databases on the protein–protein interaction (PPI) network. The obesity genes and genes of one OMIM disease were mapped onto the network, and the interaction scores between the two gene sets were investigated on the basis of the PPI of individual gene pairs, thereby inferring the relationship between obesity and this disease. Results suggested that diseases related to nutrition and endocrine are the top two diseases that are closely associated with obesity. This finding is consistent with our general knowledge and indicates the reliability of our obtained results. Moreover, we inferred that diseases related to psychiatric factors and bone may also be highly related to obesity because the two diseases followed the diseases related to nutrition and endocrine according to our results. Numerous obesity–disease associations were identified in the literature to confirm the relationships between obesity and the aforementioned four diseases. These new results may help understand the underlying molecular mechanisms of obesity–disease co-occurrence and provide useful insights for disease prevention and intervention. MDPI 2017-12-18 /pmc/articles/PMC5748710/ /pubmed/29258237 http://dx.doi.org/10.3390/genes8120392 Text en © 2017 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
Chen, Lei
Zhang, Yu-Hang
Li, JiaRui
Wang, ShaoPeng
Zhang, YunHua
Huang, Tao
Cai, Yu-Dong
Deciphering the Relationship between Obesity and Various Diseases from a Network Perspective
title Deciphering the Relationship between Obesity and Various Diseases from a Network Perspective
title_full Deciphering the Relationship between Obesity and Various Diseases from a Network Perspective
title_fullStr Deciphering the Relationship between Obesity and Various Diseases from a Network Perspective
title_full_unstemmed Deciphering the Relationship between Obesity and Various Diseases from a Network Perspective
title_short Deciphering the Relationship between Obesity and Various Diseases from a Network Perspective
title_sort deciphering the relationship between obesity and various diseases from a network perspective
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5748710/
https://www.ncbi.nlm.nih.gov/pubmed/29258237
http://dx.doi.org/10.3390/genes8120392
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