Back

Targeting complement C3a receptor resolves mitochondrial hyperfusion and subretinal microglial activation in progranulin-deficient frontotemporal dementia

Tan, L. X.; Oertel, F. C.; Cheng, A.; Cobigo, Y.; Keihani, A.; Bennett, D.; Abdelhak, A.; Montes, S. C.; Chapman, M.; Chen, R.; Cordano, C.; Ward, M.; Casaletto, K.; Kramer, J.; Rosen, H. H.; Boxer, A. L.; Miller, B. L.; Green, A.; Elahi, F.; Lakkaraju, A.

2024-06-01 neuroscience
10.1101/2024.05.29.595206 bioRxiv
Show abstract

Mutations in progranulin (GRN) cause frontotemporal dementia (GRN-FTD) due to deficiency of the pleiotropic protein progranulin. GRN-FTD exhibits diverse pathologies including lysosome dysfunction, lipofuscinosis, microgliosis, and neuroinflammation. Yet, how progranulin loss causes disease remains unresolved. Here, we report that non-invasive retinal imaging of GRN-FTD patients revealed deficits in photoreceptors and the retinal pigment epithelium (RPE) that correlate with cognitive decline. Likewise, Grn-/- mice exhibit early RPE dysfunction, microglial activation, and subsequent photoreceptor loss. Super-resolution live imaging and transcriptomic analyses identified RPE mitochondria as an early driver of retinal dysfunction. Loss of mitochondrial fission protein 1 (MTFP1) in Grn-/- RPE causes mitochondrial hyperfusion and bioenergetic defects, leading to NF-kB-mediated activation of complement C3a-C3a receptor signaling, which drives further mitochondrial hyperfusion and retinal inflammation. C3aR antagonism restores RPE mitochondrial integrity and limits subretinal microglial activation. Our study identifies a previously unrecognized mechanism by which progranulin modulates mitochondrial integrity and complement-mediated neuroinflammation.

Matching journals

The top 8 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.