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AI-powered gene discovery enables personalised psoriasis treatments, delivering targeted therapies and better patient outcomes, according to researchers at King’s College London
Recent research from King’s College London has used artificial intelligence‑enabled gene discovery to reveal new insights into psoriasis, paving the way for personalised treatment strategies. By combining machine learning with genetic analysis, scientists have identified key biological pathways that could result in more effective, targeted therapies for individuals living with this chronic skin condition.
Understanding psoriasis
Psoriasis is a common inflammatory skin disease that affects around 1 in 50 people in the UK. Severe psoriasis has a profound impact on quality of life and is often linked to several long-term health conditions.
The lack of understanding of psoriasis means current, high-cost treatment options often fail for no apparent reason, placing a heavy burden on the NHS.
AI and gene discovery in psoriasis
Researchers from King’s, Newcastle University, and Queen Mary University of London used advanced Machine Learning to identify several subtypes of the disease based on how someone’s genes impact psoriasis severity. This gives clinicians insight into why current treatments may fail, leading to more personalised treatments.
The team analysed over 700 blood samples from over 140 patients with moderate to severe psoriasis over an extended period. They were able to map how genes interfaced, both individually and in evolving networks, with other biological factors, such as BMI, to compare disease severity with common biological treatments.
They identified a nine-gene biomarker linked to psoriasis severity and specific genetic variants associated with more severe baseline disease. The researchers found a 14-gene signature associated with BMI in unaffected skin and with disease severity in affected skin with lesions.
Dr David Watson, Lecturer in Artificial Intelligence and joint first author of the study, said, “Diseases that present the same are often completely different. Breast cancer, for example, is not one, but a thousand different diseases all under the same label. To be able to develop targeted treatments, you need to understand how all these different diseases work, or risk ‘fat-fingered’ interventions like chemotherapy, which can have large side effects.
“Until now, we didn’t have that with psoriasis. But by using RNA sequencing and AI modelling, we can now categorise how genes affect the trajectory of psoriasis and group the disease into several sub-types as a prerequisite for better treatment – helping better deal with the most severe cases.”
Dr Watson said, “There are many immune-mediated inflammatory diseases, like rheumatoid arthritis and Crohn’s. And while they present differently, we know they are genetically linked – having one increases the risk of passing another to your kids.
“This is a complex world, and by figuring out how genes influence the path of one inflammatory disease, we hope to take this learning and apply it to a host of different diseases and see how they materialise in patients. If we can categorise the gene expression there too, we could potentially design personalised treatments for all these ailments which plague patients and cost our healthcare system millions.”