Researchers from Karolinska Institutet have used digital twins to improve their understanding of inflammatory diseases, potentially leading to new treatments.
The complex mechanisms behind inflammatory diseases like rheumatoid arthritis can differ in each patient, even if they have the same diagnosis. This means many drugs for inflammatory diseases have little or no effect on certain patients. Patients with diseases such as Crohn’s disease, ulcerative colitis and rheumatoid arthritis often find that they never feel completely healthy, despite being on medication.
Inflammatory diseases alter how thousands of genes interact with different organs and cell types. This pathological process can vary from patient to patient and even within the same patient. This makes it extremely difficult to diagnose and treat patients with such complex conditions.
What are digital twins?
A digital twin is a virtual model of a physical entity. They have been used in industries such as manufacturing since the early 2000s. However, digital twins in healthcare are a relatively new phenomenon. Digital twins of human beings can facilitate groundbreaking developments in precision medicine, clinical trials, and public health.
The Karolinska Institutet researchers believe that creating more personalised treatments through digital twins can help combat the challenges of treating inflammatory diseases. These models allow doctors to study each patient’s unique disease mechanism in great detail.
Using digital twins, the team found that the pathological differences in patients are caused by ‘off and on’ switch proteins in an individual’s molecular makeup. Some of these proteins can be targeted by certain drugs, such as TNF inhibitors. However, this treatment option is not suitable for everyone.
“Our analyses of patients who responded or didn’t respond to TNF therapy revealed different switch proteins in different individuals. Another important discovery was that the proteins did not switch off the diseases but were more like dimmer switches that raised or lowered the disease programmes,” said the study’s corresponding author Mikael Benson.
Predicting outcomes for inflammatory diseases
Digital modelling techniques can be adjusted for each patient’s individual circumstances by analysing gene activity from the patient’s blood and tissue cells. This can predict any physiological outcome that may occur as the condition changes. These include changes that can be induced by drug variations and their dosage. Analysing these outcomes allows researchers to explore new treatments for various diseases.
“The methods can be developed to tailor the right combination of drugs for ‘on’ proteins for individual patients. The programmes we describe will be made available to the research community so that more clinical studies can be done of patients with different immune diseases,” explained Dr Benson.
The researchers combined mouse models of rheumatoid arthritis and digital twins of humans with inflammatory diseases to draw their analysis.
“Even though 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. As far as I’m aware, this is the first time science has obtained such a broad picture of how many organs are affected by rheumatoid arthritis. This is partly due to the difficulty of physically sampling so many different organs,” concluded Dr Benson.
