Bioinformatic models can predict the individual pathological mechanisms of patients with inflammatory diseases such as rheumatoid arthritis. A study published in “Cell Reports Medicine” presents the results of a project, based on digital twins, which has allowed a deeper understanding of the “intermittent” proteins that control these diseases. Research carried out at the Karolinska Institutet (Sweden) may lead to more personalized drug therapies
It is known that most patients with inflammatory diseases such as rheumatoid arthritis, Crohn’s disease and ulcerative colitis do not feel completely healthy despite taking medication. This is a situation that causes suffering.
In an inflammatory disease, thousands of genes alter the way they interact in different organs and cell types. In addition, the pathological process varies from one patient to another with the same diagnosis, and even within the same patient at different times.
Today it is extremely difficult to diagnose and treat such complex and varied changes.
In this project that has been running for five years, researchers have been trying to solve this problem and tailor drugs to individual patients by building and processing data from their digital twins, that is, digital models of each unique mechanism of the patient’s disease.
Now the research group has found a possible solution: the changes can be organized into molecular programs. These molecular programs are regulated by a limited number of “switch” proteins.apaid and lit», some of which are known targets for drugs such as TNF inhibitors. But it is not a therapeutic option that helps everyone.
“Our analyzes of patients who did or did not respond to TNF therapy revealed different switch proteins in different individuals,” explains study author Mikael Benson. « Another important discovery was that proteins did not control disease, but were more like iswitches that increased or decreased disease programs.
Every physiological process can be described with mathematical equations. This advanced digital modeling technique can be tailored to a patient’s unique circumstances by analyzing the activity of each and every gene in thousands of individual blood and tissue cells. A digital twin can be used to calculate the physiological outcome if a condition changes, such as the dose of a drug.
In the current study, the researchers combined analyzes of a mouse model of rheumatoid arthritis and digital twins from human patients with various inflammatory diseases.
Thousands of genes changed their activity in different cell types in ten organs, including the skin, spleen, liver and lungs.
“Although only the joints were inflamed in mice, we found that thousands of genes changed their activity in different cell types in ten organs, including the skin, spleen, liver, and lungs,” Benson explains.
According to Benson, “this is the first time science has gotten such a comprehensive picture of how many organs are affected by rheumatoid arthritis. This is partly due to the difficulty of taking physical samples from so many different organs.”
Digital twins have revealed to researchers new opportunities for the effective treatment of serious diseases.
In Spain, projects such as Leukodomics try to design digital models to advance in the treatment of childhood leukemia.
“Methods can be developed to tailor the right protein-on drug combination for individual patients,” Benson adds. The programs we describe will be made available to the research community so that more clinical studies of patients with different immune diseases can be conducted.