Two Indiana University researchers are developing new ways of detecting the root of kidney disease causes using artificial intelligence data sequencing, thanks to a nearly $1.2 million grant from the National Institutes of Health.
Juexin Wang, assistant professor of bioinformatics in the Luddy School of Informatics, Computing and Engineering at IUPUI, and Dr. Michael Eadon, associate professor of medicine in the IU School of Medicine, will use novel AI data-sequencing technology to see what happens in the kidneys on a single-cell level, offering important insight into why kidney disease develops.
Juexin Wang. Photo courtesy of Juexin Wang The researchers first hope to develop a deep-learning framework with detailed heterogenous kidney spatial transcriptomics, which is data that takes a picture of where different genes are active in specific locations within tissues or organs. They will apply the new methods to publicly available kidney spatial transcriptomic data with the hopes of finding useful molecular signatures in kidney injuries.
According to the Centers for Disease Control and Prevention, one in seven adults in the United States suffer from chronic kidney disease.
"We're trying to find the differences between a healthy kidney and a patient with kidney disease, but we first need to understand the pathology of the disease using a new AI method scrutinizing new spatial transcriptomics data, which is cell information on the molecular level," Wang said. "We will then try to predict the severity of the kidney disease and identify if there are some key mechanisms that trigger the disease."
The researchers are working with Qin Ma from The Ohio State University. Ultimately, they hope to generate a community for analyzing, sharing and disseminating spatial transcriptomics for physicians and bioinformaticians in kidney research.
According to Wang, the biggest challenge for analyzing the kidney is heterogeneity. The kidney is made up of over a million nephrons - the microscopic structural unit of the organ - with more than 100 different types of tightly compacted cells. The researchers are developing ways to identify the overlapping cells in order to conduct further research of the disease.
"This research gives insight on how cells work together to build and maintain organs and systems, which is key to understanding how and why kidney disease develops," Wang said. "Other scientists can further their own research on kidney disease with our data, and physicians can use it in their practices."
