Multiplexed imaging analysis of human pancreatic islets from donors with and without type 2 diabetes

This record contains tabular data from traditional and multiplexed immunohistochemistry experiments presented in the manuscript Genetic risk converges on regulatory networks mediating early type 2 diabetes (Walker, Saunders & Rai et al., Nature 2023), a body of work that includes tissue imaging, sorted islet cell transcriptomics, and islet functional analysis of donors with early-stage type 2 diabetes (T2D) and control donors. Images can be viewed interactively on Pancreatlas (RRID:SCR_018567): https://pancreatlas.org/datasets/904/explore.
All immunohistochemistry was performed on lightly PFA-fixed human pancreatic tissue (sample characteristics available in Supplementary Table 1). For traditional immunohistochemistry, islets were imaged at 20× with 2× digital zoom using a FV3000 confocal laser scanning microscope (Olympus) or full cross-sections were scanned on a ScanScope FL (Leica/Aperio). Quantitative analysis was carried out using HALO™ (Indica Labs) or Metamorph (Molecular Devices) software. For multiplexed immunohistochemistry, images were acquired using the PhenoCycler (CODEX) Open system (Akoya Biosciences) integrated with a BZ-X810 epifluorescence microscope (Keyence) with a CFI plan Apo I 20x/0.75 objective (Nikon). Image alignment, stitching, background subtraction, and deconvolution were performed using the CODEX Processor v1.7.0.6 (Akoya Biosciences). Cell segmentation and cell type annotations were generated using the HALO HighPlex FL v3.2.1 module (Indica Labs). For cell neighborhood (CN) analysis, two methods were applied in parallel to CODEX data from annotated islets: a community detection method, termed Dynamic CF-IDF, and a k-means approach. Packages used for cell neighborhood analyses are published in Github.