Abstract

1. The Effects of Osteoarthritis on the Genes of Mice 1Jasmine George, 1Dr. Gregory Goins, 1Adrian Ambrose, 1Gregory Harper, 1Jasmine Silas 2Dr. Jacquelyn Fetrow, 2Amy Olex 1 North Carolina Agricultural and Technical State University Department of Biology, Greensboro, NC, 2 Wake Forest University Department of Computer Science and Medical School Abstract Osteoarthritis is a degenerative disease that attacks the joints, bones and tendons causing the affected individual to be unable to carry out normal mobile skills. This experiment, conducted at Wake Forest University and North Carolina A&T State University investigated the impact of osteoarthritic genes in mice through Genetic Modeling and the study of microarray technology. The experiment’s data was translated through the Mouse 430 2.0 Array. The osteoarthritic genes were injected into the knees of mice and translated into a microarray chip. The Affymetrix IDs were converted into Entrez IDs and set in Cytoscape. Cytoscape was instrumental in mapping the old and young mice’s progression in the disease. The genes that were given were separated into three different categories; time zero, SHAM, and DMM, under subcategories which varied by the ages of the mice. It was observed early in the experiment that the genes that were not affected as shown in the microarray results were more common in the younger mice than in the older mice. Methods The data was sent from the Wake Forest University team and put through Cytoscape, and calculated into various values that corresponded to different factors such as elapsed time and mouse age. The data was normalized using SVN, and calculated into 3 different SLR values (expt - ctrl): (Time zero vs Sham,Time zero vs. DMM, and Sham vs. DMM). The results needed were expected to be significantly regulated and consistent genes shown in the clustering of gene expression profiles. Conclusion In conclusion, there was seen a correlation to the progression of Osteoarthritis to the age of the mice (since, OA is closely associated with age). When the results from the initial experiment came back, the younger mice appeared to have more up regulation (i.e. more genes are expressed; the older the mouse the less likely the genes will respond, making it difficult to treat.) This proved that the progression of the disease was common in age. (Fig.3) Although this is an ongoing process (several difficulties were encountered) , through microarray analysis, and the modeling of genes in Cytoscape, a correlation between the age of the mice , the progression of the disease, and which gene networks the disease attacks (glycolysis/glucogenisis, insulin signaling and starch sucrose metabolism, just to name a few) can be seen. Data Fig.1. This figure shows two clusters from the younger mice at the 8 wk period of the experiment. The graph shows the genes that were turned on (depicted in yellow and blue) at the time the mouse was injected and the genes that did not respond (depicted in black). Introduction What is Osteoarthritis? Osteoarthritis is a degenerative disease that attacks the joints, bones and tendons causing the affected individual to be unable to carry out normal mobile skills. Since Osteoarthritis is diagnosed in the later stages, and in people in later ages, little help can be given to the patient, causing adverse effects such as pain, stiffness, and locking of the joints. Some of the causes include diabetes, obesity, and it can be hereditary. The goal of this experiment was to identify the key differences in gene expression elucidate the mechanisms by which age contributes to the development and progression of OA. Fig.2. This figure shows two clusters from the older mice at the 8 wk period of the experiment. The graph shows the genes that were turned on (depicted in yellow and blue) at the time the mouse was injected and the genes that did not respond (depicted in black). Fig.3. Results from the JAM analysis (ran 10 times on different points of interests, or seeds) shows that more significant genes were expressed in younger mice than older mice. The following shows the seed “Network Union 0,6,7: ECM-Receptor Interaction” ACKNOWLEDGEMENTS: BLEND is an Undergraduate BioMath (UBM) Project sponsored by NSF Grant No. 1029426