Focal cortical dysplasia (FCD) is a severe neurodevelopmental malformation that often manifests as medically refractory epilepsy. A key histological hallmark of FCD is the presence of cytomegalic dysmorphic neurons (CDNs), which are considered to be major contributors to cortical network hyperexcitability. However, the relatively low frequency of CDNs within resected lesions has challenged their unbiased molecular characterization. Here, we leverage deep learning approaches to objectively map key anatomical compartments of FCD and guide regional spatial transcriptomic profiling. Using this approach, we generate an anatomical transcriptional catalog of type IIb FCD, and uncover non-canonical markers of signaling and neurotransmitter pathways in CDNs that may serve as new therapeutic targets for this debilitating disorder.
import lamindb as ln
import spatialdata as sd
coll = ln.Collection.get(key="geo-gse300645")
coll.ordered_artifacts.df() # the 4 members, ordered
# download every member .zarr to the local cache:
paths = [a.cache() for a in coll.ordered_artifacts.all()]
# …or load each straight into memory as a SpatialData object:
sdatas = {a.key: sd.read_zarr(a.cache()) for a in coll.ordered_artifacts.all()}
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