This application describes a robust Southern California-based Clinical Center for participation in the Type 1
Diabetes in Acute Pancreatitis Consortium (T1DAPC). Proposed protocols address the metabolic mechanisms
and the genetic, protein, and imaging signature of patients with acute pancreatitis (AP) and recurrent acute
pancreatitis (RAP) who are at high risk for future development of diabetes. AP is the most common cause of
pancreatogenic diabetes. While meta-analyses have revealed an incidence rate of 23% for diabetes arising after
AP, they have not shed light on the type of diabetes that develops, which may comprise autoimmune or idiopathic
type 1 diabetes (T1DM), type 2 diabetes (T2DM), or a unique diabetes pathobiology. A detailed understanding
of diabetes developing after AP will yield great benefit by facilitating novel approaches to predict, prevent, and
treat this form of diabetes. The following aims are proposed to address these goals:
Specific Aim 1. Recruit a cohort of non-diabetic patients with a recent episode of AP or RAP and prospectively
characterize their islet autoimmunity and glucose/insulin homeostasis using the frequently sampled intravenous
glucose tolerance test and mixed meal tolerance tests performed 1 month after hospital discharge, and at 3, 6,
12, 18, and 24 months, and yearly thereafter. The goals of this aim are to (a) determine the incidence of diabetes
after AP, (b) identify the types of diabetes that develop after AP, (c) identify early metabolic trajectories
associated with post-AP diabetes, (d) assemble the cohort that will be the platform for Aims 2-4.
Specific Aim 2. Evaluate genetic and protein risk factors for diabetes in patients with AP or RAP. This Aim
will evaluate association of genetic risk scores for T1DM and T2DM with post AP diabetes. Thirteen candidate
proteins, associated with post AP diabetes in preliminary studies, will be assessed for association with incident
diabetes after AP, yielding a key set of proteins with utility not only in diabetes prediction but also targets for
future preventive or therapeutic measures.
Specific Aim 3. Characterize the imaging phenotype that predicts development of diabetes after AP or RAP.
Retrospective CT scans obtained during hospitalization for AP as well as CT and novel multiparametric MRI
scans obtained 1 and 12 months afterward will undergo artificial intelligence analysis to identify the imaging
biomarkers that signal diabetes risk.
Specific Aim 4. Develop a multi-factorial model to predict development of diabetes after AP or RAP. A wealth
of data will be collected from Aims 1-3, which will be combined with clinical factors to build and validate (in
independent datasets) an integrative predictive model of post AP diabetes. The goal is to create a model that
can be used in clinical settings to identify those at highest risk, facilitating targeted measures to prevent diabetes.
This innovative research will be conducted by an experienced team of investigators in endocrinology,
gastroenterology, imaging, physiology, and epidemiology to solve a problem of great public health significance.