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Objective  Shear forces play a key role in the maintenance of vessel wall integrity. Current understanding regarding shear-dependent gene expression is mainly based on  in vitro  or  in vivo  observations with experimentally deranged shear, hence reflecting acute molecular events in relation to flow. Our objective was to combine computational fluid dynamic (CFD) simulations with global microarray analysis to study flow-dependent vessel wall biology in the aortic wall under physiological conditions.    Methods and Results  Male Wistar rats were used. Animal-specific wall shear stress (WSS) magnitude and vector direction were estimated using CFD based on aortic geometry and flow information acquired by magnetic resonance imaging. Two distinct flow pattern regions were identified in the normal rat aortic arch; the distal part of the lesser curvature being exposed to low WSS and a non-uniform vector direction, and a region along the greater curvature being subjected to markedly higher levels of WSS and a uniform vector direction. Microarray analysis identified numerous novel mechanosensitive genes, including  Trpc4  and  Fgf12 , and confirmed well-known ones, e.g. K lf2  and  Nrf2 . Gene ontology analysis revealed an over-representation of genes involved in transcriptional regulation. The most differentially expressed gene,  Hand2 , is a transcription factor previously shown to be involved in extracellular matrix remodeling. HAND2 protein was endothelial specific and showed higher expression in the regions exposed to low WSS with disturbed flow.    Conclusions  Microarray analysis validated the CFD-defined WSS regions in the rat aortic arch, and identified numerous novel shear-sensitive genes. Defining the functional importance of these genes in relation to atherosusceptibility may provide important insight into the understanding of vascular pathology.

Characterization of Shear-Sensitive Genes in the Normal Rat Aorta Identifies Hand2 as a Major Flow-Responsive Transcription Factor