Celiac Disease (CD) is an autoimmune disorder triggered by gluten ingestion in genetically susceptible individuals. Its heterogeneous presentation, especially in pediatric patients, limits the effectiveness of current symptom-based classifications such as the Oslo definitions. This study proposes a framework based on Topological Data Analysis (TDA) to identify new, clinically meaningful sub-phenotypes of pediatric CD. We used a multicentric dataset of over 3,000 children. Compared with standard clustering (DBSCAN, Agglomerative, K-Medoids), our TDA Mapper revealed stable, interpretable communities reflecting serological and clinical patterns. Results indicate that serology, histology, and comorbidities jointly define distinct pediatric phenotypes, supporting data-driven approaches for precision medicine in CD.

(2026). Sub-Phenotyping of Pediatric Celiac Disease with Topological Data Analysis . Retrieved from https://hdl.handle.net/10446/329266

Sub-Phenotyping of Pediatric Celiac Disease with Topological Data Analysis

Pala, Daniele;Brembilla, Valentina;Medolago, Emanuele;Sirtoli, Chiara;
2026-01-01

Abstract

Celiac Disease (CD) is an autoimmune disorder triggered by gluten ingestion in genetically susceptible individuals. Its heterogeneous presentation, especially in pediatric patients, limits the effectiveness of current symptom-based classifications such as the Oslo definitions. This study proposes a framework based on Topological Data Analysis (TDA) to identify new, clinically meaningful sub-phenotypes of pediatric CD. We used a multicentric dataset of over 3,000 children. Compared with standard clustering (DBSCAN, Agglomerative, K-Medoids), our TDA Mapper revealed stable, interpretable communities reflecting serological and clinical patterns. Results indicate that serology, histology, and comorbidities jointly define distinct pediatric phenotypes, supporting data-driven approaches for precision medicine in CD.
2026
Pala, Daniele; Albi, Giuseppe; Brembilla, Valentina; Lenzi, Erika; Medolago, Emanuele; Sirtoli, Chiara; Dagliati, Arianna
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10446/329266
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