To investigate effects of IGF-1 on human-like coronary atherosclerosis we used high fat diet-fed Rapacz pigs with familial hypercholesterolemia (FH pigs). We used spatial transcriptomics (ST) analysis to identify global transcriptome changes in advanced plaque compartments and to obtain mechanistic insights into IGF-1 effects. IGF-1-injected FH pigs had 1.8-fold increase in total circulating IGF-1 levels compared to control. IGF-1 decreased relative coronary atheroma (data obtained by serial intravascular ultrasound) and lesion cross-sectional area (post-mortem histology). IGF-1 increased fibrous cap thickness, and reduced necrotic core size, macrophage content, and cell apoptosis, changes consistent with promotion of a stable plaque phenotype. ST analysis revealed that IGF-1 suppressed FOS/FOSB factors and gene expression of MMP9 and CXCL14 suggesting possible involvement of these molecules in IGF-1’s effect on atherosclerosis.
from sddb import Catalog
cohort = Catalog().collection("geo-gse220218")
cohort.members # the 4 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-gse220218")
coll.ordered_artifacts.to_dataframe() # the 4 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-gse220218 --dest data/Licenses: 4 NCBI GEO policy
No linked publication found — please cite the data source.