27Novel blood metabolomic tests for the diagnosis of Primary Sclerosing Cholangitis and associated Cholangiocarcinoma
Ainhoa Lapitz, Elisa Catanzaro, Anne Echebarria, Ibon Martínez-Arranz, Piotr Milkiewicz, Marco Carbone, Rocío Macías, Cristina Alonso, Alejandro Montilla, Malgorzata Milkiewicz, Ahmed Fowsiyo, Mohamad Elgozair, Laura Izquierdo-Sánchez, Adelaida La Casta, Raul Jimenez-Aguero, Maria Jesus Perugorria, Laura Cristoferi, Johannes R Hov, Christoph Schramm, Gonzalo Crespo, Marco Arrese, Javier Chahuan, Javier Bustamante, Angela Lamarca, Michael Dill, Domingo Balderramo, Luis Bujanda, Lewis Roberts, Tom Hemming Karlsen, Trine Folseraas, Pedro Miguel Rodrigues, Jesus Maria BanalesAbstract
Background and Aims
Primary sclerosing cholangitis (PSC) increases the risk of developing cholangiocarcinoma (CCA), which is the leading cause of premature death in these patients. Current diagnostic methods for early detection of either condition remain largely suboptimal. This study investigates serum metabolites as potential non-invasive diagnostic biomarkers.
Methods
This multicenter international study analyzed 459 serum samples from 13 international centers, including patients with PSC (n = 216), PSC who developed CCA during follow-up (PSC to CCA; n = 24), PSC with concomitant CCA (PSC-CCA; n = 88), ulcerative colitis (UC; n = 14), and healthy individuals (n = 79). Serum metabolomics was evaluated by ultra-high-performance liquid chromatography-mass spectrometry (UHPLC-MS) and the accuracy of the single candidate metabolite biomarkers was further assessed. Machine learning was used to generate the best diagnostic and predictive algorithms.
Results
Fifty-two serum metabolites were identified as markers of PSC, independent of age, biological sex, cirrhosis, UC, or ursodeoxycholic acid (UDCA) treatment. A diagnostic model based on only six lipids distinguished PSC patients from healthy controls with high accuracy (AUC 0.952 discovery, 0.918 validation), independently of the levels of transaminases or cholestasis markers (i.e., GGT, AP, bilirubin) in blood. Subgroup analyses were performed in PSC patients with and without inflammatory bowel disease (IBD), confirming the model’s consistent performance across both subgroups when compared with their respective control groups – UC and healthy controls (AUC 0.959 and 0.939, respectively). The PSC model also confirmed its diagnostic performance in patients with established PSC-CCA or progression to CCA within 2 years, when compared to UC and healthy controls, showing AUC values ranging from 0.911 to 0.976.
Additionally, 20 metabolites were significantly altered in PSC patients with CCA (PSC-CCA), regardless of demographics, cirrhosis, UDCA treatment, IBD status, or CCA subtype, and independently of serum transaminases and cholestatic markers levels. A model incorporating six lipids accurately identified PSC-CCA cases compared to PSC patients (AUC = 0.912 discovery; 0.896 validation), showing excellent performance in early-stage tumor detection (AUC 0.921) and outperforming CA19-9 (AUC 0.708). Importantly, the model retained high accuracy even in CCA patients with low CA19-9 levels (AUC 0.905) and in PSC patients who developed CCA within a year of clinical diagnosis (AUC 0.792).
Conclusion
The PSC and PSC-CCA blood tests provide a non-invasive approach for diagnosing PSC and PSC-CCA, addressing an important need in this population. Their integration into clinical practice could enhance risk stratification, early detection, personalized surveillance, and treatment decision-making in PSC patients.