Imperial College London
Alternate

DrKrysiaBroda

Faculty of Engineering, Department of Computing

Honorary Senior Lecturer
 
 
 
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Contact

 

k.broda Website

 
 
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Location

 

Huxley BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Maimari:2016:10.1160/TH15-09-0704,
author = {Maimari, N and Pedrigi, RM and Russo, A and Broda, K and Krams, R},
doi = {10.1160/TH15-09-0704},
journal = {Thrombosis and Haemostasis},
pages = {474--483},
title = {Integration of flow studies for robust selection of mechanoresponsive genes},
url = {http://dx.doi.org/10.1160/TH15-09-0704},
volume = {115},
year = {2016}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Blood flow is an essential contributor to plaque growth, composition and initiation. It is sensed by endothelial cells, which react to blood flow by expressing > 1000 genes. The sheer number of genes implies that one needs genomic techniques to unravel their response in disease. Individual genomic studies have been performed but lack sufficient power to identify subtle changes in gene expression. In this study, we investigated whether a systematic meta-analysis of available microarray studies can improve their consistency. We identified 17 studies using microarrays, of which six were performed in vivo and 11 in vitro. The in vivo studies were disregarded due to the lack of the shear profile. Of the in vitro studies, a cross-platform integration of human studies (HUVECs in flow cells) showed high concordance (> 90 %). The human data set identified > 1600 genes to be shear responsive, more than any other study and in this gene set all known mechanosensitive genes and pathways were present. A detailed network analysis indicated a power distribution (e. g. the presence of hubs), without a hierarchical organisation. The average cluster coefficient was high and further analysis indicated an aggregation of 3 and 4 element motifs, indicating a high prevalence of feedback and feed forward loops, similar to prokaryotic cells. In conclusion, this initial study presented a novel method to integrate human-based mechanosensitive studies to increase its power. The robust network was large, contained all known mechanosensitive pathways and its structure revealed hubs, and a large aggregate of feedback and feed forward loops.
AU  - Maimari,N
AU  - Pedrigi,RM
AU  - Russo,A
AU  - Broda,K
AU  - Krams,R
DO  - 10.1160/TH15-09-0704
EP  - 483
PY  - 2016///
SN  - 0340-6245
SP  - 474
TI  - Integration of flow studies for robust selection of mechanoresponsive genes
T2  - Thrombosis and Haemostasis
UR  - http://dx.doi.org/10.1160/TH15-09-0704
UR  - http://hdl.handle.net/10044/1/33618
VL  - 115
ER  -
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