Antineutrophil cytoplasmic antibody (ANCA)–associated vasculitis is a life-threatening autoimmune disease that often results in kidney failure caused by crescentic glomerulonephritis (ANCA-GN). To date, treatment of most patients with ANCA-GN relies on unspecific immunosuppressive agents that harbor serious adverse effects and limited efficiency. Using spatial and single-cell transcriptome analysis we characterized inflammatory niches in the kidneys of 34 patients with ANCA-GN and idenjpgied proinflammatory cytokine producing CD4+ and CD8+ T cells as a key pathogenic tissue signature. By employing digital pharmacology we then idenjpgied ustekinumab, a monoclonal antibody targeting IL-12 and IL-23 in these T cells, as promising therapeutic avenue. Based on these findings, four patients with relapsing ANCA-GN were treated with ustekinumab in combination with low-dose cyclophosphamide. Ustekinumab was given subcutaneously (90 mg) at weeks 0, 4, 12, and 24 and clinical and renal response were evaluated at week 26. Treatment induced substantial clinical response in all ANCA-GN patients, with improvements in kidney function, and Birmingham Vasculitis Activity Score, and was well tolerated. Our findings suggest that the pathogenesis-based treatment of ANCA-GN patients with ustekinumab is efficacious and warrants further investigation in clinical trials.
from sddb import Catalog
cohort = Catalog().collection("geo-gse250138")
cohort.members # the 23 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-gse250138")
coll.ordered_artifacts.to_dataframe() # the 23 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-gse250138 --dest data/Licenses: 23 NCBI GEO policy
@article{Engesser_2024,
title = {Immune profiling-based targeting of pathogenic T cells with ustekinumab in ANCA-associated glomerulonephritis},
volume = {15},
ISSN = {2041-1723},
url = {http://dx.doi.org/10.1038/s41467-024-52525-w},
DOI = {10.1038/s41467-024-52525-w},
number = {1},
journal = {Nature Communications},
publisher = {Springer Science and Business Media LLC},
author = {Engesser, Jonas and Khatri, Robin and Schaub, Darius P. and Zhao, Yu and Paust, Hans-Joachim and Sultana, Zeba and Asada, Nariaki and Riedel, Jan-Hendrik and Sivayoganathan, Varshi and Peters, Anett and Kaffke, Anna and Jauch-Speer, Saskia-Larissa and Goldbeck-Strieder, Thiago and Puelles, Victor G. and Wenzel, Ulrich O. and Steinmetz, Oliver M. and Hoxha, Elion and Turner, Jan-Eric and Mittrücker, Hans-Willi and Wiech, Thorsten and Huber, Tobias B. and Bonn, Stefan and Krebs, Christian F. and Panzer, Ulf},
year = {2024},
month = Sept
}