Flow dependent gene expression in the rat aorta under physiological conditions

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 portions of the entire aorta under physiological conditions. Methods and Results: Animal-specific WSS magnitude and vector direction were estimated using CFD based on aortic geometry and flow information acquired by MRI. Two distinct flow pattern regions were identified in the normal rat aorta; the distal part of the inner curvature being exposed to low WSS and a non-uniform vector direction, and a region along the outer curvature being subjected to markedly higher levels of WSS and a uniform vector direction. Microarray analysis identified numerous novel mechanosensitive genes, including Hand2, trpc4 and slain2, and confirmed well-known ones, such as klf2 and BMP4. Three genes were further validated for protein , including Hand2, which showed higher expression in the endothelium in regions exposed to disturbed flow. Gene ontology analysis revealed an over-representation of genes involved in transcriptional regulation. Microarray analysis of two distinct flow pattern regions were identified in the normal rat aorta. Tissue pieces from groups of five animals were pooled for each region giving total of 28 pools; 14 paired sample pools of high and low wall shear stress.