Spatial transcriptomics from paired pancreas and associated draining lymph nodes reveals a lymphotoxin-beta signature in human type 1 diabetes
This study explores the inflammatory response involved in type 1 diabetes (T1D) using multi-cell resolution spatial transcriptomics (ST) to assay paired pancreas and pancreatic lymph node (pLN) samples from human donors across the natural history of T1D. Integration of ST with public single-cell RNA sequencing data enabled interrogation of transcriptional alterations in T1D across both tissues at the cellular scale. In the T1D pancreas, we identified global upregulation of inflammation-associated transcripts, including multiple regenerating islet-derived (REG) family genes, complement factor 3 (C3), SOD2, and OLFM4, and highlighted cellular candidates potentially contributing to these signatures. Within the T1D pLN, we observed spatially restricted upregulation of lymphotoxin- (LTB) alongside follicular dendritic cell (FDC)-associated transcripts including FDCSP, CLU, and FCER2. Collectively, these findings highlight a distinct inflammation signature in the pancreas and evidence of enhanced follicular activity in the associated pLN.
import lamindb as ln
import spatialdata as sd
coll = ln.Collection.get(key="geo-gse296626")
coll.ordered_artifacts.df() # the 35 members, ordered
# download every member .zarr to the local cache:
paths = [a.cache() for a in coll.ordered_artifacts.all()]
# …or load each straight into memory as a SpatialData object:
sdatas = {a.key: sd.read_zarr(a.cache()) for a in coll.ordered_artifacts.all()} Cite this collection
No linked publication found — please cite the data source.