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Integrative network analysis reveals biological pathways associated with Williams syndrome
BACKGROUND: Williams syndrome (WS) is a neurodevelopmental disorder that has been attributed to heterozygous deletions in chromosome 7q11.23 and exhibits a variety of physical, cognitive, and behavioral features. However, the genetic basis of this phenotypic variability is unclear. In this study, we...
Autores principales: | , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7379192/ https://www.ncbi.nlm.nih.gov/pubmed/30362171 http://dx.doi.org/10.1111/jcpp.12999 |
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author | Kimura, Ryo Swarup, Vivek Tomiwa, Kiyotaka Gandal, Michael J. Parikshak, Neelroop N. Funabiki, Yasuko Nakata, Masatoshi Awaya, Tomonari Kato, Takeo Iida, Kei Okazaki, Shin Matsushima, Kanae Kato, Toshihiro Murai, Toshiya Heike, Toshio Geschwind, Daniel H. Hagiwara, Masatoshi |
author_facet | Kimura, Ryo Swarup, Vivek Tomiwa, Kiyotaka Gandal, Michael J. Parikshak, Neelroop N. Funabiki, Yasuko Nakata, Masatoshi Awaya, Tomonari Kato, Takeo Iida, Kei Okazaki, Shin Matsushima, Kanae Kato, Toshihiro Murai, Toshiya Heike, Toshio Geschwind, Daniel H. Hagiwara, Masatoshi |
author_sort | Kimura, Ryo |
collection | PubMed |
description | BACKGROUND: Williams syndrome (WS) is a neurodevelopmental disorder that has been attributed to heterozygous deletions in chromosome 7q11.23 and exhibits a variety of physical, cognitive, and behavioral features. However, the genetic basis of this phenotypic variability is unclear. In this study, we identified genetic clues underlying these complex phenotypes. METHODS: Neurobehavioral function was assessed in WS patients and healthy controls. Total RNA was extracted from peripheral blood and subjected to microarray analysis, RNA‐sequencing, and qRT‐PCR. Weighted gene co‐expression network analysis was performed to identify specific alterations related to intermediate disease phenotypes. To functionally interpret each WS‐related module, gene ontology and disease‐related gene enrichment were examined. We also investigated the micro (mi)RNA expression profiles and miRNA co‐expression networks to better explain the regulation of the transcriptome in WS. RESULTS: Our analysis identified four significant co‐expression modules related to intermediate WS phenotypes. Notably, the three upregulated WS‐related modules were composed exclusively of genes located outside the 7q11.23 region. They were significantly enriched in genes related to B‐cell activation, RNA processing, and RNA transport. BCL11A, which is known for its association with speech disorders and intellectual disabilities, was identified as one of the hub genes in the top WS‐related module. Finally, these key upregulated mRNA co‐expression modules appear to be inversely correlated with a specific downregulated WS‐related miRNA co‐expression module. CONCLUSIONS: Dysregulation of the mRNA/miRNA network involving genes outside of the 7q11.23 region is likely related to the complex phenotypes observed in WS patients. |
format | Online Article Text |
id | pubmed-7379192 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-73791922020-07-24 Integrative network analysis reveals biological pathways associated with Williams syndrome Kimura, Ryo Swarup, Vivek Tomiwa, Kiyotaka Gandal, Michael J. Parikshak, Neelroop N. Funabiki, Yasuko Nakata, Masatoshi Awaya, Tomonari Kato, Takeo Iida, Kei Okazaki, Shin Matsushima, Kanae Kato, Toshihiro Murai, Toshiya Heike, Toshio Geschwind, Daniel H. Hagiwara, Masatoshi J Child Psychol Psychiatry Original Articles BACKGROUND: Williams syndrome (WS) is a neurodevelopmental disorder that has been attributed to heterozygous deletions in chromosome 7q11.23 and exhibits a variety of physical, cognitive, and behavioral features. However, the genetic basis of this phenotypic variability is unclear. In this study, we identified genetic clues underlying these complex phenotypes. METHODS: Neurobehavioral function was assessed in WS patients and healthy controls. Total RNA was extracted from peripheral blood and subjected to microarray analysis, RNA‐sequencing, and qRT‐PCR. Weighted gene co‐expression network analysis was performed to identify specific alterations related to intermediate disease phenotypes. To functionally interpret each WS‐related module, gene ontology and disease‐related gene enrichment were examined. We also investigated the micro (mi)RNA expression profiles and miRNA co‐expression networks to better explain the regulation of the transcriptome in WS. RESULTS: Our analysis identified four significant co‐expression modules related to intermediate WS phenotypes. Notably, the three upregulated WS‐related modules were composed exclusively of genes located outside the 7q11.23 region. They were significantly enriched in genes related to B‐cell activation, RNA processing, and RNA transport. BCL11A, which is known for its association with speech disorders and intellectual disabilities, was identified as one of the hub genes in the top WS‐related module. Finally, these key upregulated mRNA co‐expression modules appear to be inversely correlated with a specific downregulated WS‐related miRNA co‐expression module. CONCLUSIONS: Dysregulation of the mRNA/miRNA network involving genes outside of the 7q11.23 region is likely related to the complex phenotypes observed in WS patients. John Wiley and Sons Inc. 2018-10-25 2019-05 /pmc/articles/PMC7379192/ /pubmed/30362171 http://dx.doi.org/10.1111/jcpp.12999 Text en © 2018 The Authors. Journal of Child Psychology and Psychiatry published by John Wiley & Sons Ltd on behalf of Association for Child and Adolescent Mental Health. This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. |
spellingShingle | Original Articles Kimura, Ryo Swarup, Vivek Tomiwa, Kiyotaka Gandal, Michael J. Parikshak, Neelroop N. Funabiki, Yasuko Nakata, Masatoshi Awaya, Tomonari Kato, Takeo Iida, Kei Okazaki, Shin Matsushima, Kanae Kato, Toshihiro Murai, Toshiya Heike, Toshio Geschwind, Daniel H. Hagiwara, Masatoshi Integrative network analysis reveals biological pathways associated with Williams syndrome |
title | Integrative network analysis reveals biological pathways associated with Williams syndrome |
title_full | Integrative network analysis reveals biological pathways associated with Williams syndrome |
title_fullStr | Integrative network analysis reveals biological pathways associated with Williams syndrome |
title_full_unstemmed | Integrative network analysis reveals biological pathways associated with Williams syndrome |
title_short | Integrative network analysis reveals biological pathways associated with Williams syndrome |
title_sort | integrative network analysis reveals biological pathways associated with williams syndrome |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7379192/ https://www.ncbi.nlm.nih.gov/pubmed/30362171 http://dx.doi.org/10.1111/jcpp.12999 |
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