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A novel approach for correction of crosstalk effects in pathway analysis and its application in osteoporosis research

Osteoporosis is a prevalent bone metabolic disease and peripheral blood monocytes represent a major systemic cell type for bone metabolism. To identify the key dysfunctional pathways in osteoporosis, we performed pathway analyses on microarray data of monocytes from subjects with extremely high/low...

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Autores principales: Zhou, Yu, Gao, Yunlong, Xu, Chao, Shen, Hui, Tian, Qing, Deng, Hong-Wen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5766601/
https://www.ncbi.nlm.nih.gov/pubmed/29330445
http://dx.doi.org/10.1038/s41598-018-19196-2
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author Zhou, Yu
Gao, Yunlong
Xu, Chao
Shen, Hui
Tian, Qing
Deng, Hong-Wen
author_facet Zhou, Yu
Gao, Yunlong
Xu, Chao
Shen, Hui
Tian, Qing
Deng, Hong-Wen
author_sort Zhou, Yu
collection PubMed
description Osteoporosis is a prevalent bone metabolic disease and peripheral blood monocytes represent a major systemic cell type for bone metabolism. To identify the key dysfunctional pathways in osteoporosis, we performed pathway analyses on microarray data of monocytes from subjects with extremely high/low hip bone mineral density. We first performed a traditional pathway analysis for which different pathways were treated as independent. However, genes overlap among pathways will lead to “crosstalk” phenomenon, which may lead to false positive/negative results. Therefore, we applied correction techniques including a novel approach that considers the correlation among genes to adjust the crosstalk effects in the analysis. In traditional analysis, 10 pathways were found to be significantly associated with BMD variation. After correction for crosstalk effects, three of them remained significant. Moreover, the MAPK signaling pathway, which has been shown to be important for osteoclastogenesis, became significant only after the correction for crosstalk effects. We also identified a new module mainly consisting of genes present in mitochondria to be significant. In summary, we describe a novel method to correct the crosstalk effect in pathway analysis and found five key independent pathways involved in BMD regulation, which may provide a better understanding of biological functional networks in osteoporosis.
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spelling pubmed-57666012018-01-25 A novel approach for correction of crosstalk effects in pathway analysis and its application in osteoporosis research Zhou, Yu Gao, Yunlong Xu, Chao Shen, Hui Tian, Qing Deng, Hong-Wen Sci Rep Article Osteoporosis is a prevalent bone metabolic disease and peripheral blood monocytes represent a major systemic cell type for bone metabolism. To identify the key dysfunctional pathways in osteoporosis, we performed pathway analyses on microarray data of monocytes from subjects with extremely high/low hip bone mineral density. We first performed a traditional pathway analysis for which different pathways were treated as independent. However, genes overlap among pathways will lead to “crosstalk” phenomenon, which may lead to false positive/negative results. Therefore, we applied correction techniques including a novel approach that considers the correlation among genes to adjust the crosstalk effects in the analysis. In traditional analysis, 10 pathways were found to be significantly associated with BMD variation. After correction for crosstalk effects, three of them remained significant. Moreover, the MAPK signaling pathway, which has been shown to be important for osteoclastogenesis, became significant only after the correction for crosstalk effects. We also identified a new module mainly consisting of genes present in mitochondria to be significant. In summary, we describe a novel method to correct the crosstalk effect in pathway analysis and found five key independent pathways involved in BMD regulation, which may provide a better understanding of biological functional networks in osteoporosis. Nature Publishing Group UK 2018-01-12 /pmc/articles/PMC5766601/ /pubmed/29330445 http://dx.doi.org/10.1038/s41598-018-19196-2 Text en © The Author(s) 2018 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
Zhou, Yu
Gao, Yunlong
Xu, Chao
Shen, Hui
Tian, Qing
Deng, Hong-Wen
A novel approach for correction of crosstalk effects in pathway analysis and its application in osteoporosis research
title A novel approach for correction of crosstalk effects in pathway analysis and its application in osteoporosis research
title_full A novel approach for correction of crosstalk effects in pathway analysis and its application in osteoporosis research
title_fullStr A novel approach for correction of crosstalk effects in pathway analysis and its application in osteoporosis research
title_full_unstemmed A novel approach for correction of crosstalk effects in pathway analysis and its application in osteoporosis research
title_short A novel approach for correction of crosstalk effects in pathway analysis and its application in osteoporosis research
title_sort novel approach for correction of crosstalk effects in pathway analysis and its application in osteoporosis research
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5766601/
https://www.ncbi.nlm.nih.gov/pubmed/29330445
http://dx.doi.org/10.1038/s41598-018-19196-2
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