Leveraging Artificial Intelligence in the Diagnosis and Treatment of Congenital Disorders of Glycosylation: Advancements, Challenges, and Future Directions

Abstract

Artificial Intelligence (AI) is revolutionizing the diagnosis and treatment of Congenital Disorders of Glycosylation (CDG), a group of over 130 rare genetic conditions affecting glycosylation, a critical biological process. This paper explores the advancements AI has brought to CDG diagnosis and treatment, highlighting how AI tools, such as PredictSNP, REVEL, and Face2Gene, enhance diagnostic accuracy, facilitate early detection, and provide new insights into disease mechanisms. AI's role in predicting glycosylation sites, identifying Golgi proteins, and classifying disease phenotypes is examined, along with its potential for repurposing drugs to treat CDG. Despite these advancements, challenges like data quality, model interpretability, and ethical concerns remain. The paper emphasizes the need for data integration, ethical frameworks, and interdisciplinary collaboration to fully harness AI's potential in managing CDG and other rare genetic disorders.