Multiple sclerosis (MS) is an inflammatory disease of the central nervous system characterised by myelin loss and progressive neurodegeneration. To better understand MS lesion initiation and progression, we generated spatial gene activity maps of white (WM) and grey matter (GM) MS lesions. In different MS lesion types, we detected novel transcriptional domains, including an identifiable rim around active WM lesions. These active lesion rims were characterised by changes in astrocytic, oligodendrocytic, and microglial gene activity. Furthermore, we identified three novel WM lesion trajectories, predicting how normal appearing WM could progress into WM lesions, with lesion rims, active lesion cores, and mixed active/inactive lesion cores as potential outcomes. Our findings offer new insights into MS lesion progression, and the dynamic molecular and cellular processes that underlie MS.
from sddb import Catalog
cohort = Catalog().collection("geo-gse208747")
cohort.members # the 26 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-gse208747")
coll.ordered_artifacts.to_dataframe() # the 26 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-gse208747 --dest data/Licenses: 26 NCBI GEO policy
No linked publication found — please cite the data source.