bioRxivBioinformaticsPreprint
The Human Pancreas Cell Atlas defines a healthy reference framework for disease contextualization and translational benchmarking
Shrey ParikhiD, Daniel C. StrobliD, Sara JiméneziD, Julia Beckmann, Lucas ArnoldtiD, Eljas RoelliniD, Valerie VandenbemptiD, Michael Sterr, Mandala Aije, Ha T.H. VuiD, Rebecca L. MeltoniD, Jie Liu, FAN FENG, JP CARTAILLER, Kyle J. GaultoniD, Stephen C.J. ParkeriD, Juergen Rüland, Christian ConradiD, Marcela BriššováiD, Françoise CarlottiiD, Heiko LickertiD, Roland EilsiD, Diego BalboaiD, Malte D. LueckeniD, Fabian Joachim TheisiD
Abstract
A central challenge in single-cell biology is distinguishing disease-associated remodeling from normal cellular heterogeneity. Addressing this challenge requires healthy reference frameworks that capture cellular diversity across individuals, technologies, and biological contexts. Here we present the Human Pancreas Cell Atlas (HPCA), a reference atlas of the healthy human pancreas integrating 815,126 single-cell and single-nucleus transcriptomes from 109 donors across 12 studies, diverse technologies, and demographics. Using benchmarked integration and community-driven annotations, HPCA defines 94 cell types and transcriptional states spanning endocrine, exocrine, immune, and stromal compartments. The atlas identifies rare endocrine populations, including a putative, spatially supported polyhormonal alpha-beta-delta state, and provides a unified framework for interpreting pancreatic cellular variation across diverse biological and demographic covariates. Projection of disease and model-system datasets onto HPCA contextualized endocrine and epithelial remodeling relative to healthy pancreatic states. Diabetes-associated endocrine cells remained embedded within the healthy endocrine state space while exhibiting disease-specific changes, as supported by spatial and eQTL concordance analyses. Integration with a pancreatic ductal adenocarcinoma atlas resolved injury-associated and malignant epithelial ecosystem regions across donors. Finally, the HPCA enables quantitative benchmarking of murine diabetes models and stem-cell-derived islets against human pancreatic reference states. Together, the HPCA establishes a healthy transcriptional coordinate system for interpreting disease-associated pathophysiology, experimental perturbation, and regenerative fidelity, illustrating how reference atlases can function as analytical frameworks rather than static cell catalogs.
- organism: human
- assay: scRNA-seq
- research focus: cell type annotation
- research focus: benchmarking
- approach: statistical model
- Citations
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