Authors: Daniel Jaeger, Huiyan Jing, Lawrence F. Brass, Manash S. Chatterjee, Matthew H. Flamm, Scott L. Diamond, Songtao Zhou, Talid Sinno, Thomas V. Colace
Publication Date: July 5, 2012
Citation: M. H. Flamm, T. Colace, M. S. Chatterjee, H. Jing, S. Zhou, D. Jaeger, L. F. Brass, T. Sinno, S. L. Diamond, Multiscale Prediction of Patient-Specific Platelet Function Under Flow, Blood 120 (2012) 190-198.
Abstract: During thrombotic or hemostatic episodes, platelets bind collagen and release ADP and thromboxane A(2), recruiting additional platelets to a growing deposit that distorts the flow field. Prediction of clotting function under hemodynamic conditions for a patient’s platelet phenotype remains a challenge. A platelet signaling phenotype was obtained for 3 healthy donors using pairwise agonist scanning, in which calcium dye-loaded platelets were exposed to pairwise combinations of ADP, U46619, and convulxin to activate the P2Y(1)/P2Y(12), TP, and GPVI receptors, respectively, with and without the prostacyclin receptor agonist iloprost. A neural network model was trained on each donor’s pairwise agonist scanning experiment and then embedded into a multiscale Monte Carlo simulation of donor-specific platelet deposition under flow. The simulations were compared directly with microfluidic experiments of whole blood flowing over collagen at 200 and 1000/s wall shear rate. The simulations predicted the ranked order of drug sensitivity for indomethacin, aspirin, MRS-2179 (a P2Y(1) inhibitor), and iloprost. Consistent with measurement and simulation, one donor displayed larger clots and another presented with indomethacin resistance (revealing a novel heterozygote TP-V241G mutation). In silico representations of a subject’s platelet phenotype allowed prediction of blood function under flow, essential for identifying patient-specific risks, drug responses, and novel genotypes.