Spatial transcriptomics reveals injury-responsive compartments and coordinated immune–fibrotic signaling in ANCA-associated renal vasculitis
Immune dysregulation is a hallmark of anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV), particularly in the kidney; however, the spatial organization of renal microenvironments remains poorly understood. Here, we applied spatial transcriptomics to renal biopsies from pediatric patients with AAV representing distinct histological classes defined by the Berden classification (4 control, 2 focal, and 3 non-focal cases), generating an in situ map of localized disease programs. Four disease-associated compartments—immune/interstitial fibroblasts (IM/Fib), glomeruli, myofibroblasts, and vascular compartments—showed distinct compartment-specific signatures that correlated with patient-level histopathology. We further identified coordinated immune–fibrotic signaling associated with different histopathological classes. Within IM/Fib, the CXCR4–CD74 receptor complex co-localized with IgM⁺ cells, and lumican (LUM) co-localized with collagen I/III; both were validated by immunofluorescence and associated with fibrotic injury. These tissue-anchored signatures represent potential disease-associated molecular features with possible diagnostic relevance, and highlight the value of this foundational spatial transcriptomics map for generating testable hypotheses to be further evaluated in larger, stratified, treatment-annotated cohorts.
from sddb import Catalog
cohort = Catalog().collection("geo-gse302677")
cohort.members # the 3 datasets as a table
print(cohort.licenses()) # check the terms before you download
sdatas = cohort.to_dict() # {uid: SpatialData}, cached locally
# or keep the .zarr files in a folder of your choice:
# sdatas = cohort.to_dict(dest="data/") Needs pip install lamindb and network access to the Lamin database, which is limited during the alpha. If it fails, use the Client tab.
import lamindb as ln
db = ln.DB("scverse/spatialdata-db")
coll = db.Collection.get(key="geo-gse302677")
coll.ordered_artifacts.to_dataframe() # the 3 members, ordered
# download every member .zarr to the local cache:
paths = [a.cache() for a in coll.ordered_artifacts.all()] # sddb client: download every member .zarr into data/
sddb-cli download --collection geo-gse302677 --dest data/ Licenses: 3 NCBI GEO policy
Cite this collection
doi.org/10.3389/fimmu.2026.1884100 ↗@article{Tang_2026,
title = {Spatial transcriptomics reveals injury-responsive compartments and coordinated immune–fibrotic signaling in ANCA-associated renal vasculitis},
volume = {17},
ISSN = {1664-3224},
url = {http://dx.doi.org/10.3389/fimmu.2026.1884100},
DOI = {10.3389/fimmu.2026.1884100},
journal = {Frontiers in Immunology},
publisher = {Frontiers Media SA},
author = {Tang, Yucheng and Zhu, Chunhua and Chen, Shuang and Chen, Huimei and Qian, Hai and Zhang, Aihua and Petretto, Enrico},
year = {2026},
month = July
}