Seeking consortium on obesity-related metabolic diseases (MASLD/MASH) for Horizon Europe call

1. Research group profile and main research lines

BRU-OB is a clinical and translational research group focused on severe obesity and obesity-related metabolic diseases, particularly metabolic dysfunction-associated steatotic liver disease (MASLD/MASH). Its research combines clinical and metabolic phenotyping with biochemical, histopathological and multi-omics approaches to investigate disease mechanisms, identify biomarkers and characterize metabolic and tissue-related changes associated with disease progression and therapeutic interventions.

2. Interest in the topic and expertise offered

The group is interested in HORIZON-HLTH-2027-02-TOOL-01-two-stage, particularly in the development of predictive biomarkers of disease progression and treatment response in obesity and related metabolic diseases.

A major asset of the group is an established cohort of approximately 1,400 patients with severe obesity, recruited since June 2008. Perioperative biological samples include plasma, serum, buffy coat and liver biopsies, together with extensive clinical, biochemical and histopathological phenotyping. Samples are carefully preserved in the institutional Biobank and Department of Pathology. The long recruitment period enables longitudinal follow-up and investigation of long-term disease evolution and clinical outcomes. Patient recruitment is ongoing, with no predefined end date.

Additional resources include:

• Forty-four patients who underwent revisional bariatric surgery due to an insufficient response to their initial procedure, with liver biopsies collected at both the initial and revisional surgeries. These paired samples provide an opportunity to investigate long-term histopathological and molecular changes associated with the clinical course and response to the initial intervention.

• Seventy-nine patients with pre- and post-surgical CT imaging, allowing the characterization of changes in adipose tissue compartments.

• Extensive experience in clinical biochemistry, liver histopathology, molecular biomarker characterization and multi-omics analyses, including metabolomics, lipidomics and proteomics.

• Expertise in statistical analysis, data integration and interpretation using R and Python.

The group also has experience in the identification and characterization of circulating protein biomarkers, and their association with metabolic and liver disease phenotypes.

These figures reflect the resources available as of November 2026 and are expected to increase as patient recruitment and sample collection continue.

Additional research interests

A further area of interest is research on new and emerging pharmacological treatments for obesity, particularly in the identification of biomarkers predictive of treatment response and the characterization of metabolic and hepatic changes associated with these therapies. This represents a potential area for future collaboration, building on our expertise in clinical and metabolic phenotyping, biomarker research and liver disease.

3. Expected role in the consortium

The group could contribute as a clinical and translational research partner, providing its well-characterized patient cohort, biological samples, clinical and histopathological data, and expertise in biomarker discovery and validation.

It would also consider leading a work package focused on clinical phenotyping, longitudinal biomarker characterization and validation, or the integration of molecular and clinical data.

4. Added value

BRU-OB offers a combination of a large, well-characterized clinical cohort, long-term recruitment and follow-up, extensive biological sample collections and complementary expertise in biochemical, histopathological and multi-omics analyses.

The availability of paired tissue samples and longitudinal imaging data provides additional opportunities to investigate disease progression and tissue-specific changes following bariatric surgery. This integrated clinical and molecular research capacity can provide high-quality data for the development, training and validation of AI-based predictive models, in collaboration with partners specializing in artificial intelligence and computational methodologies.

5. Contact

Name: Jordi Camps
Email: jorge.camps@salutsantjoan.cat

Name: David Parada
Email: david.parada@salutsantjoan.cat