bioRxivNeurosciencePreprint
WFS1E864K in humans and mice causes Wolfram-like syndrome optic atrophy via early axonal mitochondrial dysfunction
Hernán H. DiégueziD, Kevin Dubois, Élodie ReboussiniD, Cansu de MuijnckiD, Jérôme Sarniguet, Chantal CazevieilleiD, Stacy L. AlvesiD, Julie DégardiniD, Valérie Fradot, Serge A. PicaudiD, Stéphane Melik ParsadaniantziD, Maria Michielde van GendereniD, Andrea Louise VincentiD, Benjamin DelpratiD, Élodie M. RichardiD
Abstract
Wolfram-like syndrome leads to retinal ganglion cell degeneration and vision loss. Wolfram-like syndrome is primarily caused by variants in the WFS1 gene, which encodes an endoplasmic reticulum resident transmembrane protein, Wolframin. To date, the disease mechanism remains unclear, and no therapies are available. Here, we generated a mouse model carrying the pathogenic WFS1E864K allele that recapitulated key features of human Wolfram-like syndrome, including bilateral optic atrophy, retinal nerve fiber thinning and lamination of the outer plexiform layer. We demonstrated, using the Wfs1E864K mouse model, that alteration of the protein leads to impairments of retinal ganglion cell function, associated with a thinning of the inner retina layer and nerve fibers. These alterations are associated with myelin disorganization, axonal death, mitochondrial alterations in the axons, and impairment of endoplasmic reticulum-mitochondria communication in the soma. Our data showed that primary deficits are localized in the optic nerve before progressing towards the retinal ganglion cell soma. RNAseq analysis identified several altered signaling pathways such as in lipid metabolism, glia activation response, metabolic stress, organelle transport and quality control. These findings highlighted the critical role of Wolframin in optic nerve mitochondrial physiology, providing us with a pertinent model to develop novel innovative therapeutic strategies.
- organism: mouse
- organism: human
- assay: bulk RNA-seq
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 0
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