Cargando…
Identification of network-based biomarkers of cardioembolic stroke using a systems biology approach with time series data
BACKGROUND: Molecular signaling of angiogenesis begins within hours after initiation of a stroke and the following regulation of endothelial integrity mediated by growth factor receptors and vascular growth factors. Recent studies further provided insights into the coordinated patterns of post-strok...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4674888/ https://www.ncbi.nlm.nih.gov/pubmed/26679092 http://dx.doi.org/10.1186/1752-0509-9-S6-S4 |
_version_ | 1782404967888322560 |
---|---|
author | Wong, Yung-Hao Wu, Chia-Chou Lai, Hsien-Yong Jheng, Bo-Ren Weng, Hsing-Yu Chang, Tzu-Hao Chen, Bor-Sen |
author_facet | Wong, Yung-Hao Wu, Chia-Chou Lai, Hsien-Yong Jheng, Bo-Ren Weng, Hsing-Yu Chang, Tzu-Hao Chen, Bor-Sen |
author_sort | Wong, Yung-Hao |
collection | PubMed |
description | BACKGROUND: Molecular signaling of angiogenesis begins within hours after initiation of a stroke and the following regulation of endothelial integrity mediated by growth factor receptors and vascular growth factors. Recent studies further provided insights into the coordinated patterns of post-stroke gene expressions and the relationships between neurodegenerative diseases and neural function recovery processes after a stroke. RESULTS: Differential protein-protein interaction networks (PPINs) were constructed at 3 post-stroke time points, and proteins with a significant stroke relevance value (SRV) were discovered. Genes, including UBC, CUL3, APP, NEDD8, JUP, and SIRT7, showed high associations with time after a stroke, and Ingenuity Pathway Analysis results showed that these post-stroke time series-associated genes were related to molecular and cellular functions of cell death, cell survival, the cell cycle, cellular development, cellular movement, and cell-to-cell signaling and interactions. These biomarkers may be helpful for the early detection, diagnosis, and prognosis of ischemic stroke. CONCLUSIONS: This is our first attempt to use our theory of a systems biology framework on strokes. We focused on 3 key post-stroke time points. We identified the network and corresponding network biomarkers for the 3 time points, further studies are needed to experimentally confirm the findings and compare them with the causes of ischemic stroke. Our findings showed that stroke-associated biomarker genes at different time points were significantly involved in cell cycle processing, including G(2)-M, G(1)-S and meiosis, which contributes to the current understanding of the etiology of stroke. We hope this work helps scientists reveal more hidden cellular mechanisms of stroke etiology and repair processes. |
format | Online Article Text |
id | pubmed-4674888 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-46748882015-12-15 Identification of network-based biomarkers of cardioembolic stroke using a systems biology approach with time series data Wong, Yung-Hao Wu, Chia-Chou Lai, Hsien-Yong Jheng, Bo-Ren Weng, Hsing-Yu Chang, Tzu-Hao Chen, Bor-Sen BMC Syst Biol Research BACKGROUND: Molecular signaling of angiogenesis begins within hours after initiation of a stroke and the following regulation of endothelial integrity mediated by growth factor receptors and vascular growth factors. Recent studies further provided insights into the coordinated patterns of post-stroke gene expressions and the relationships between neurodegenerative diseases and neural function recovery processes after a stroke. RESULTS: Differential protein-protein interaction networks (PPINs) were constructed at 3 post-stroke time points, and proteins with a significant stroke relevance value (SRV) were discovered. Genes, including UBC, CUL3, APP, NEDD8, JUP, and SIRT7, showed high associations with time after a stroke, and Ingenuity Pathway Analysis results showed that these post-stroke time series-associated genes were related to molecular and cellular functions of cell death, cell survival, the cell cycle, cellular development, cellular movement, and cell-to-cell signaling and interactions. These biomarkers may be helpful for the early detection, diagnosis, and prognosis of ischemic stroke. CONCLUSIONS: This is our first attempt to use our theory of a systems biology framework on strokes. We focused on 3 key post-stroke time points. We identified the network and corresponding network biomarkers for the 3 time points, further studies are needed to experimentally confirm the findings and compare them with the causes of ischemic stroke. Our findings showed that stroke-associated biomarker genes at different time points were significantly involved in cell cycle processing, including G(2)-M, G(1)-S and meiosis, which contributes to the current understanding of the etiology of stroke. We hope this work helps scientists reveal more hidden cellular mechanisms of stroke etiology and repair processes. BioMed Central 2015-12-09 /pmc/articles/PMC4674888/ /pubmed/26679092 http://dx.doi.org/10.1186/1752-0509-9-S6-S4 Text en Copyright © 2015 Wong et al. http://creativecommons.org/licenses/by/4.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Wong, Yung-Hao Wu, Chia-Chou Lai, Hsien-Yong Jheng, Bo-Ren Weng, Hsing-Yu Chang, Tzu-Hao Chen, Bor-Sen Identification of network-based biomarkers of cardioembolic stroke using a systems biology approach with time series data |
title | Identification of network-based biomarkers of cardioembolic stroke using a systems biology approach with time series data |
title_full | Identification of network-based biomarkers of cardioembolic stroke using a systems biology approach with time series data |
title_fullStr | Identification of network-based biomarkers of cardioembolic stroke using a systems biology approach with time series data |
title_full_unstemmed | Identification of network-based biomarkers of cardioembolic stroke using a systems biology approach with time series data |
title_short | Identification of network-based biomarkers of cardioembolic stroke using a systems biology approach with time series data |
title_sort | identification of network-based biomarkers of cardioembolic stroke using a systems biology approach with time series data |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4674888/ https://www.ncbi.nlm.nih.gov/pubmed/26679092 http://dx.doi.org/10.1186/1752-0509-9-S6-S4 |
work_keys_str_mv | AT wongyunghao identificationofnetworkbasedbiomarkersofcardioembolicstrokeusingasystemsbiologyapproachwithtimeseriesdata AT wuchiachou identificationofnetworkbasedbiomarkersofcardioembolicstrokeusingasystemsbiologyapproachwithtimeseriesdata AT laihsienyong identificationofnetworkbasedbiomarkersofcardioembolicstrokeusingasystemsbiologyapproachwithtimeseriesdata AT jhengboren identificationofnetworkbasedbiomarkersofcardioembolicstrokeusingasystemsbiologyapproachwithtimeseriesdata AT wenghsingyu identificationofnetworkbasedbiomarkersofcardioembolicstrokeusingasystemsbiologyapproachwithtimeseriesdata AT changtzuhao identificationofnetworkbasedbiomarkersofcardioembolicstrokeusingasystemsbiologyapproachwithtimeseriesdata AT chenborsen identificationofnetworkbasedbiomarkersofcardioembolicstrokeusingasystemsbiologyapproachwithtimeseriesdata |