Peripheral artery disease (PAD) results from an obstruction of blood flow in the peripheral arteries, most commonly the arteries that supply the legs. The blockage reduces the increases in perfusion that are required with activity causing leg pain and difficulty walking. In its most severe form PAD limits leg perfusion resulting in limb amputation. PAD affects approximately 8 to 12 million persons in United States, especially those over the age of 50 and its prevalence is now almost comparable to that of coronary artery disease. With the goal of trying to increase blood flow around blockages clinical trials using drugs and gene delivery aimed at stimulating vascular growth and remodeling (angiogenesis and arteriogenesis) have been performed for more than a decade but have not been successful. Current treatments and recommendations for PAD do not affect limb perfusion and there is a clear unmet medical need to identify novel targets and develop new treatments for PAD. The complexity of the known signaling pathways involved in PAD, including various growth factors and their crosstalks, suggests that high-throughput experimental data and their analysis using bioinformatics and systems biology methods could lead to a new level of understanding of the disease as well as novel and hereunto unanticipated potential targets. Such bioinformatics analyses have not been systematically performed for PAD. Thus, we will use bioinformatic approaches to analyze existing multiple large-scale high-throughput gene expression datasets from PAD patients and mouse models of PAD with the goal of identifying and systematizing important proteins and signaling pathways, discover connections between the proteins in the form of a PAD interactome, performing in silico drug repositioning studies to predict potential therapeutic targets, and validating them using previously accumulated human biopsy samples. A systematic analysis of molecules, pathways, protein-protein interactions, and drug targets will provide much needed guidance for prevention and treatment of PAD.
Peripheral artery disease (PAD) affects approximately 8 to 12 million persons in United States, especially those over the age of 50. Using bioinformatic approaches we will analyze large-scale high-throughput gene expression datasets from PAD patients and mouse models of PAD with the goal of identifying and systematizing important proteins and signaling pathways, discover connections between the proteins, perform computational drug repositioning studies to predict potential therapeutic targets, and validate them using previously accumulated human blood and muscle samples.
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