The EXPAND study is a prospective observational study designed to investigate the biological mechanisms underlying the heterogeneity of type 2 diabetes and related metabolic disorders.
The study will enroll adults with and without pancreatic disease, including patients undergoing pancreatic surgery, individuals with chronic pancreatitis, subjects at high risk of type 2 diabetes, and patients with newly diagnosed type 2 diabetes. Clinical, metabolic, imaging, genetic, microbiome, and molecular data will be integrated to identify distinct metabolic endotypes and to investigate the interactions between the exocrine pancreas, endocrine pancreas, and adipose tissue. The ultimate goal is to improve the understanding of diabetes pathophysiology and support the development of precision medicine approaches.
Adults aged 20 to 78 years.
Ability and willingness to provide written informed consent.
Individuals undergoing pancreatectomy for non-endocrine pancreatic disease.
Individuals with pancreatic ductal adenocarcinoma undergoing pancreatectomy.
Age <20 years or >78 years.
Inability or unwillingness to provide informed consent.
Pregnancy or breastfeeding.
Diagnosis of type 1 diabetes mellitus.
Participants will be recruited from patients receiving care at Fondazione Policlinico Universitario A. Gemelli IRCCS (Rome, Italy). The study population includes adults with and without pancreatic disease, including individuals undergoing pancreatic resection, patients with chronic or previous pancreatitis, subjects at increased risk of type 2 diabetes mellitus, and individuals with newly diagnosed type 2 diabetes mellitus. Participants will be consecutively enrolled from the Departments of Endocrinology, Diabetology, Gastroenterology, and Pancreatic Surgery according to the predefined eligibility criteria.
Cohort
Prospective
Not listed
Identification and Characterization of Metabolic Endotypes
Identification and characterization of physiological endotypes of glucose metabolism using unsupervised clustering and archetype analysis integrating metabolic phenotyping, imaging, and biological/multi-omic variables.
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