Hospital General de Tomelloso Secures National Funding for Eosinophilic Esophagitis Study
The Health Research Institute of Castilla-La Mancha (IDISCAM) has secured a provisional 75,000-euro grant from the Carlos III Health Institute to fund a project on eosinophilic esophagitis. The research will be conducted from the General Hospital of Tomelloso, focusing on predicting the clinical course of the chronic inflammatory esophageal disease from the moment of diagnosis.
Grant Allocation and Multi-Center Collaboration
The research initiative is led by Emilio José Laserna Mendieta from the Eosinophilic Enteropathies and Mucosal Immunology Group (EIMIRlab) of IDISCAM, which is integrated into the Research Unit of the General Hospital of Tomelloso and CIBERehd. The project received support from IDISCAM’s Science College program, helping it secure one of four proposed funding allocations in Castilla-La Mancha in this call.
Emilio José Laserna Mendieta conducts his activity within the Clinical Laboratory Service of the hospital and works in collaboration with the Digestive Service, directed by Alfredo José Lucendo Villarín. Furthermore, the study involves teams from the Hospital Universitario de Cáceres, the Hospital Universitario de La Princesa, in Madrid, and the Hospital Universitari Vall d’Hebron, in Barcelona.
Clinical Challenge and Genetic Sequencing Methodology
Eosinophilic esophagitis (EoE) is characterized by the accumulation of eosinophils—a type of white blood cell tied to allergic and inflammatory responses—leading to symptoms such as swallowing difficulties, food impactions, and progressive narrowing of the esophageal walls. The condition affects approximately one in every 840 people in Spain, with incidence rates climbing over recent years. Confirmation of the disease relies on endoscopies and biopsies, which also track treatment efficacy over time.
To address the variable nature of how the disease progresses among patients, the research team aims to build a predictive model. This model will combine standard clinical variables—such as age, sex, and reported symptoms—with genetic data extracted from blood samples. Researchers will deploy massive sequencing techniques to examine approximately 650,000 DNA variants, mapping how these genetic markers relate to clinical outcomes during the first two years following diagnosis.
If results are favorable, the predictive model could help clinicians distinguish between patients who maintain stable control and those who require intensive monitoring or different treatments. By deploying this personalized approach, medical teams hope to control inflammation earlier, prevent severe structural complications like esophageal strictures, and optimize healthcare resources by avoiding unnecessary tests when clinically possible.
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