Fig. 4: Spatial transcriptomics of Nageotte nodules identifies non-myelinating Schwann cells and satellite glia as prominent cell types.

A VISIUM spatial transcriptomics was conducted on 16 DRG sections from 6 DPN donors. Barcodes touching Nageotte nodules (1094) and nearby neurons (1087) were selected for downstream analysis. B) Key gene ontology themes were related to neurodegeneration. C RNAscope in situ hybridization for SOX10 (green, satellite glia and Schwann cells), FABP7 (red, satellite glia), CD68 (purple, macrophages), and DAPI (blue) in a DPN DRG. Confocal, 40X. Sample size: DPN n = 6. D Digitally zoomed overlay images of Nageotte nodule 1 (cyan arrow in (C)) and Nageotte nodule 2 (yellow arrow in (C)). Nageotte nodule 1 had higher content of FABP7+ nuclei, while Nageotte nodule 2 had little-to-no FABP7 signal, indicating that there are differences in the composition of cell types between Nageotte nodules. E Deconvolution using single-nuclear sequencing datasets revealed that the potential sources of the majority of the non-neuronal mRNA transcripts in Nageotte nodules come from Satellite glial cells and non-myelinating (NM) Schwann cells. The remaining percentage of transcripts in Nageotte nodules arise from neurons, likely axonally trafficked mRNAs. Data points are not shown on graph as they represent individual barcodes (n = 1041, 1064, and 39191 for nodules, nearby neurons, and other barcodes, respectively). F Clustering analysis of Nageotte nodule barcodes identified 5 subclusters. G Deconvolution reveals differences in the distribution of estimated mRNA sources between clusters. Statistical tests: B: Fisher’s exact test with correction for multiple comparisons run in Enrichr. Adjusted p-values shown. E: Error bars = mean +/- SD. Scale bars: C: 50 μm. D: 10 μm. Graphic in (A): Created in BioRender. Shiers, S. (2025) https://BioRender.com/5u9g7kp. Source data are provided as a Source Data file.