Ethiopian cutaneous leishmaniasis (CL) shows remarkably heterogeneous clinical presentations, but the underlying immunopathological mechanisms driving this heterogeneity in disease presentation remains poorly understood. To characterise the local immune response in Ethiopian CL, we performed spatial transcriptomics (Visium, 10x Genomics) on paired (lesional and non lesional) skin punch biopsies from five Ethiopian CL patients. We used reference-free deconvolution, morphology-guided regional analyses, and immunohistochemistry to identify five5 dominant patient-defined immunopathological responses: i) epithelial hyperplasia with interferon-stimulated keratinocytes, ii) cytotoxicity with tertiary lymphoid structures, iii) granulomatous inflammation with proinflammatory response iv) granulomatous inflammation with M2-polarised myeloid cell responses , and v) fibrotic remodelling with active collagen synthesis. Future longitudinal studies are needed to distinguish whether these patterns represent discrete pathotypes or stages of disease progression. Improved understanding of disease pathotypes in Ethiopian CL directly supports the WHO 2030 roadmap for leishmaniasis control and informs future immune-based therapeutic strategies.
from sddb import Catalog
cohort = Catalog().collection("geo-gse317987")
cohort.members # the 10 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-gse317987")
coll.ordered_artifacts.to_dataframe() # the 10 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-gse317987 --dest data/Licenses: 10 NCBI GEO policy
@article{Dey_2026,
title = {Spatial mapping of Ethiopian cutaneous leishmaniasis lesions reveals distinct tissue level immune programs},
volume = {17},
ISSN = {1664-3224},
url = {http://dx.doi.org/10.3389/fimmu.2026.1870524},
DOI = {10.3389/fimmu.2026.1870524},
journal = {Frontiers in Immunology},
publisher = {Frontiers Media SA},
author = {Dey, Nidhi S. and Pham, Thao-Thy and Dey, Shoumit and Kassa, Mekibib and Mekonnen, Tigist and Fikre, Helina and Monsieurs, Pieter and Consortium, Spatial CL and Pareyn, Myrthe and van Griensven, Johan and Domagalska, Malgorzata and Dujardin, Jean-Claude and Asres, Mezgebu Silamsaw and Woldetensay, Mikias and Kaye, Paul M. and Adriaensen, Wim},
year = {2026},
month = July
}