Gene Expression Analysis of Acute Kidney Injury in Kidney Transplants

Abstract

In the world of kidneys, transplants are an option for patients in chronic stages that can save their lives, simultaneously can cause lots of additional issues and one of the most common effects being Acute Kidney Injury (AKI). Due to how rarely kidneys are biopsied, we are not able to find out much about what exactly is causing AKI, specifically in relation to gene expressions. In this research, I have taken a dataset of 47 patients and their gene expressions: 28 with AKI, 8 who have had a complete nephrectomy, and 11 who are healthy patients. Using this data, I have trained a model using logistic regression that attempts to predict which patients are likely to have AKI depending on their gene expression levels. Using the model, I have been able to predict the top genes that are associated with having AKI and using a gene ontology analysis tool, I was able to find skeletal muscle terms that are associated with those genes.