Beta cell dysfunction occurs independently of insulitis in type 1 diabetes pathogenesis.

During type 1 diabetes (T1D) progression, beta cells become dysfunctional and exhibit reduced first-phase insulin release. While this period of beta cell dysfunction is well established, its cause and underlying mechanism remain unknown. To address this knowledge gap, live human pancreas tissue slices were prepared from autoantibody- negative organ donors without diabetes (ND), donors positive for one or more islet autoantibodies (AAb+), and donors with T1D within 0-4 years of diagnosis (T1D+).

Mapping histological and functional maturation of human endocrine pancreas across early postnatal periods.

Human endocrine cell differentiation and islet morphogenesis play critical roles in determining islet cell mass and function, but the events and timeline of these processes are incompletely defined. To better understand early human islet cell development and maturation, we collected 115 pediatric pancreata and mapped morphological and spatiotemporal changes from birth through the first ten years of life. Using quantitative analyses and a combination of complementary tissue imaging approaches, including confocal microscopy and whole-slide imaging, we developed an integrated model for endocrine cell formation and islet architecture, including endocrine cell type heterogeneity and abundance, endocrine cell proliferation, and islet vascularization and innervation.

Serological markers of exocrine pancreatic function are differentially informative for distinguishing individuals progressing to type 1 diabetes.

Introduction: Altered serum levels of growth hormones, adipokines, and exocrine pancreas enzymes have been individually linked with type 1 diabetes (T1D). We collectively evaluated seven such biomarkers, combined with islet autoantibodies (AAb) and genetic risk score (GRS2), for their utility in predicting AAb/T1D status.

Research Design And Methods: Cross-sectional serum samples (n=154 T1D, n=56 1AAb+, n=77 ≥2AAb+, n=256 AAb-) were assessed for IGF1, IGF2, adiponectin, leptin, amylase, lipase, and trypsinogen (n=543, age range 2.

Characterizing cell-type spatial relationships across length scales in spatially resolved omics data.

Spatially resolved omics (SRO) technologies enable the identification of cell types while preserving their organization within tissues. Application of such technologies offers the opportunity to delineate cell-type spatial relationships, particularly across different length scales, and enhance our understanding of tissue organization and function. To quantify such multi-scale cell-type spatial relationships, we present CRAWDAD, Cell-type Relationship Analysis Workflow Done Across Distances, as an open-source R package.