Spatial Gene Expression of Human Coronary Arteries Revealed the Molecular Features of Diffuse Intimal Thickening in Explanted Hearts
Diffuse intimal thickening (DIT) is a preclinical stage of atherogenesis in humans that does not exist in commonly used mouse models of atherosclerosis. Vascular smooth muscle cells (SMCs) are the predominant cell type that occupies the intimal and medial layers of human coronary arteries. The intimal layer of DIT is particularly prone to developing atherosclerosis later in life. Differences in the molecular features between the intimal and medial layers of DIT regions may represent the earliest changes that promote atherogenesis in humans, and can be studied by spatial molecular phenotyping.
from sddb import Catalog
cohort = Catalog().collection("geo-gse283269")
cohort.members # the 6 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-gse283269")
coll.ordered_artifacts.to_dataframe() # the 6 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-gse283269 --dest data/ Licenses: 6 CC BY 4.0
Cite this collection
doi.org/10.3390/ijms26051949 ↗@article{Li_2025,
title = {Spatial Gene Expression of Human Coronary Arteries Revealed the Molecular Features of Diffuse Intimal Thickening in Explanted Hearts},
volume = {26},
ISSN = {1422-0067},
url = {http://dx.doi.org/10.3390/ijms26051949},
DOI = {10.3390/ijms26051949},
number = {5},
journal = {International Journal of Molecular Sciences},
publisher = {MDPI AG},
author = {Li, Boaz and Leung, Samuel and Elishaev, Maria and Cheng, Wan Hei and Mocci, Giuseppe and Björkegren, Johan L. M. and Lai, Chi and Singh, Amrit and Wang, Ying},
year = {2025},
month = Feb,
pages = {1949}
}