Study findings could lead to new treatment options for patients with IBD in the future.
Scientists have created the first ever predictive model of inflammatory bowel disease (IBD) by modeling the exact biological networks involved in the immune component of the disease.
In a study published in Nature Genetics, investigators used various data from 3 different groups of patients at different stages of IBD. The data included gene expression, regulatory elements, DNA variations, and clinical information.
This in-depth computational analysis allowed investigators to model the precise biological networks and create a predictive model of IBD.
“These results demonstrate how much we stand to gain by organizing massive amounts of molecular and clinical data using advanced machine learning approaches that in turn can be queried to generate novel disease insights,” said senior author Eric Schadt. “Our predictive model serves as a repository of knowledge and understanding that facilitates learning more about the development and progression of IBD, including identifying master regulators of disease that can be explored as targets for treatment.”
Using tissue samples obtained from patients with IBD, the investigators could observe the effects of genes and regulatory elements on each other. Furthermore, it represented the entire network of immune activity.
Next, the scientists validated the top 12 genes predicted to change the network and provide new insight into the mechanisms that regulate IBD.
“This validated key driver set not only introduces new regulators of the processes central to IBD but also provides the integrated circuits of genetic, molecular, and clinical traits that can be directly queried to interrogate and refine the regulatory framework defining IBD,” the authors concluded.
Scott Snapper, MD, an expert in the research and treatment of IBD who was not involved in the study, added, “By creating multiscale predictive models of the immune component of IBD across different stages of disease, this work helps move us towards a more comprehensive understanding of the complex molecular network of this disease. I look forward to access this new knowledge base as highly informative to the collective efforts of the IBD research community to identify new targets and ultimately, novel treatments of IBD.”