Research
Why is treating metabolic diseases so challenging?
Disease
heterogeneity
Obesity, diabetes and their complications are driven by diverse genetic, biological and environmental factors, resulting in different disease trajectories and responses to treatment.
Fragmented expertise
Understanding metabolic disease requires the integration of life sciences, systems medicine, computational analytics and clinical translation, but these disciplines are rarely combined.
Biological complexity
Metabolic diseases arise from complex interactions between multiple biological factors, many of which are still not fully understood.
Interdisciplinary
skills gap
There is a growing need for researchers who can bridge scientific disciplines and sectors to translate scientific discoveries into improved patient care.
Limited precision medicine approaches
The lack of robust biomarkers, patient stratification strategies and therapeutic targets limits personalized prevention and treatment.
Work packages
Work package 2 (WP2)
Molecular Mechanisms of Disease Heterogeneity
WP2 investigates the molecular and cellular mechanisms underlying differences in the onset, progression and complications of metabolic diseases, with a particular focus on diabetes. By integrating clinical cohorts, experimental models and computational approaches, the projects uncover key drivers of disease heterogeneity to advance precision medicine.
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Lead: IDIBAPS/HMGU
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DCs 1-5
Work package 3 (WP3)
Markers and Targets of Disease Heterogeneity
WP3 investigates tissue- and organ-specific drivers of heterogeneity across the disease spectrum, from obesity to type 2 diabetes and their complications. By integrating clinical data, multi-omics, spatial profiling and AI, the projects identify disease subtypes, biomarkers and therapeutic targets, laying the foundation for precision diagnostics and personalized therapies.
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Lead: WUT/ULEI
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DCs 6-11
Work package 4 (WP4)
Unravelling and Targeting Treatment Response Heterogeneity
WP4 translates mechanistic insights into precision therapies by investigating why individuals respond differently to treatment, integrating biological and psychosocial perspectives. Combining molecular and structural biology, AI-guided therapeutic approaches and patient-centered research, the projects develop personalized interventions to improve treatment outcomes and quality of life across diverse patient groups.
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Lead: UAM/MUW
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DCs 12-15