From photosensitivity to autoimmunity: the role of AI metabolomics in PCT–celiac disease overlap

Porphyria cutanea tarda (PCT), caused by hepatic uroporphyrinogen decarboxylase deficiency, may rarely overlap with undiagnosed celiac disease (CD), complicating diagnosis due to shared hepatic and dermatologic features. Both conditions present with skin manifestations such as photosensitivity, blistering, or dermatitis herpetiformis-like lesions, often leading to misclassification. AI-driven metabolomics provides a novel strategy to identify metabolic biomarkers, predict CD with high accuracy through machine learning, and uncover hidden comorbidities in PCT patients. Despite challenges including limited datasets, bioinformatics demands, and regulatory barriers, integrating metabolomics with AI could enhance diagnostic precision and enable personalized management. Multidisciplinary collaboration is critical to translating these technologies into clinical practice for early detection and improved outcomes in PCT-CD overlap.