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Diabetes and Vascular Disease

SAT-515 - Defining endocrine cell-type-specific lipid expression in human pancreatic islets using MALDI imaging mass spectrometry

Saturday, June 13, 2026
9:30 AM - 4:30 PM CT
Pancreatic islet cell loss or dysfunction is critical to all forms of diabetes. New molecular imaging technologies have enhanced our understanding of the role of protein, RNA, and DNA species in human islet physiology and pathophysiology, but lipid species remain incompletely defined, largely due to difficulties in quantifying and spatially resolving them. Our group has overcome these challenges in human pancreatic tissues using a workflow that integrates lipid imaging mass spectrometry (IMS) with multiplexed protein imaging, providing unprecedented spatial detail that links lipid profiles to specific cell types. However, because islets usually constitute less than 5% of the pancreas, tissue sections yield limited endocrine-cell-specific lipid data. This study aims to develop an analytical workflow to define lipid profiles of human islet endocrine cells (EC) from isolated islets, enabling more comprehensive lipid profiling of these key cell types.

Human islets from adult donors with no diabetes (ND, n=3) and type 2 diabetes (T2D, n=1) were obtained through the Integrated Islet Isolation Program (IIDP) and analyzed by the Human Islet Phenotyping Program for secretory function and EC composition. Matrix-assisted laser desorption/ionization (MALDI) IMS was performed on cryosections of gels of Collagen I-embedded islets to obtain untargeted spatial lipidomics. This spatial omics approach detects hundreds of lipids in a single MALDI IMS experiment and produces heatmap-style ion images of each individual analyte across a section. Co-registration with post-IMS immunofluorescence (IF) microscopy of the same sections yielded average spectra for each EC type (α, β, δ) in situ.

Initial unsupervised k-means clustering of MADLI IMS spectra from islet gels was used to separate the background Collagen I matrix from embedded islets. Further clustering of islets revealed distinct molecular heterogeneity, correlating with different EC types on corresponding post-IMS IF images. When comparing IMS spatial resolution, 5 µm pixels provided a clear distinction between EC types that 10 µm did not. Comparison of T2D with ND islets revealed differences in islet lipid expression, particularly in sphingomyelin species (e.g., m/z 906.6 and 904.6). Though limited to a single donor, this proof-of-concept suggests the utility of this method in identifying pathological changes in lipid species in diabetes.

Here, we demonstrate the ability to spatially resolve distinct EC-specific lipid profiles in isolated human islets. We showed that there is no Collagen I matrix interference and that distinct lipid profiles can be observed between EC types. This approach will enable future studies evaluating lipid heterogeneity in ND islet cells and changes in type 1 and type 2 diabetes, potentially leading to the discovery of new targets for early detection and/or treatment.

*Unless otherwise noted, all abstracts presented at ENDO must not be released to the press or the public until the date and time of presentation. For oral presentations, the abstracts are embargoed until the session begins. The Endocrine Society reserves the right to lift the embargo on specific abstracts that are selected for promotion prior to or during ENDO.*