Bioinformatics Pilot Program Abstract: Alfonso Romero-Sandoval

Finding CD163 dependent pathways in diabetic macrophages using bioinformatics
Dr. E. Alfonso Romero-Sandoval (PI), Abigail Alvarado, Rachel Grosick, Department of Pharmaceutical and Administrative Science, Presbyterian College School of Pharmacy

Diabetes is a chronic disease that often results in complications such as diabetic neuropathy. 25 million people suffer from diabetes in the United States. Among adult diabetic patients, >60% develop peripheral diabetic neuropathy (PDN), and 15-25% of these patients suffer painful diabetic neuropathy. Peripheral diabetic neuropathy is the main cause of foot ulcers, which is the leading cause of foot amputations. We have uncovered that the incidence of PDN in patients from Laurence County, SC (Presbyterian College School of Pharmacy (PCSP) Wellness Center patients), which has a population made up primarily of low-income, rural patients, is at the higher end of the national average range. One of the manifestations of PDN is the loss of mechanical sensitivity, which is the major underlying mechanism for the formation of foot ulcers. The lack of proper wound healing in diabetic patients results in the progression of ulcer formation, and subsequent foot amputations in this patient population. This lack of proper wound healing results from a abnormal persistent pro-inflammatory phenotype in macrophages. Therefore, a better understanding on the mechanisms governing tissue repair and the resolution of inflammation could represent an opportunity to identify potential targets to promote efficient wound healing in diabetic patients. With current funding we have found that the induction of CD163 gene promotes a more efficient wound healing in an in vitro model using nanotechnology. Our ongoing experiments are focused on a total RNA sequencing and gene/pathway expression bioinformatics analysis of CD163 overexpressing cells (vs. control). We hypothesize that macrophages from diabetic patients are dysfunctional due to altered molecular pathways downstream CD163. We now propose to perform a whole-transcriptome analysis and differential expression/pathway determination using bioinformatics in macrophages from diabetic patients with and without neuropathy. This will allow us to do a cross analysis with our CD163 overexpressing cells using bioinformatics methodologies. We anticipate that this project will provide sufficient data to submit a competitive application for an R15 in October 2016.