Posted on: 27 August 2024

Researchers from Trinity College Dublin's School of Medicine and the ADAPT Centre at the School of Computer Science and Statistics have made a significant breakthrough in vasculitis research, in collaboration with Lund University. Their findings, recently published in The Lancet Rheumatology, offer new insights into diagnosing and treating systemic vasculitis, a group of rare and complex autoimmune diseases.

This research is part of the EU-funded FAIRVASC project, which leverages advanced artificial intelligence (AI) and big data techniques to overcome key challenges in diagnosing and treating systemic vasculitis. FAIRVASC connects vasculitis patient registries across Europe, facilitating seamless data sharing and advanced analysis to enhance research and improve patient care.

The study focuses on antineutrophil cytoplasm antibody (ANCA)-associated vasculitis and introduces a novel approach to classifying this disease using a federated dataset ten times larger than those used in previous studies. The extensive dataset enabled more detailed analysis, revealing previously unidentified disease clusters. This new classification method offers more accurate predictions of outcomes, such as overall survival and kidney health, paving the way for personalised treatment strategies that could significantly improve patient care.

Professor Mark Little, Professor of Nephrology and Consultant Nephrologist at Trinity College Dublin, and Tallaght and Beaumont Hospitals, commented, "Our research shows that by leveraging advanced AI systems and broad datasets, we can uncover new patterns in this rare autoimmune disease, which impact the likelihood of adverse outcomes. This allows us to focus potentially toxic therapies on those most likely to benefit."

He emphasised that such progress was possible only through a multidisciplinary approach and the direct involvement of patients with lived experience of the condition. "This collaborative project has successfully brought together experts in medicine, computer science, and statistics," Professor Little added.

Professor Declan O'Sullivan, ADAPT Principal Investigator and Professor in Computer Science at Trinity, expressed his enthusiasm for the research, stating, "I am delighted to see that the research we focus on in our group, particularly Knowledge Graphs for data integration, is making an impact in advancing medical research, especially in federating patient registries for rare diseases."

The study highlights the transformative potential of AI in medical research, particularly in addressing the complexities of rare diseases, where it has previously been difficult to generate sufficiently large cohorts for meaningful research. By enabling more precise identification of disease patterns, AI has the potential to revolutionise how clinicians approach diagnosis and treatment, offering hope for better outcomes not only for vasculitis patients but also for those suffering from other rare and challenging diseases.

This research provides a blueprint for using advanced technologies to tackle similar challenges in the broader field of rare diseases, potentially leading to breakthroughs that could benefit countless patients worldwide.

The full journal article is available on the publisher's website.