Skip to main content

Correction of dysregulated lipid metabolism normalizes gene expression in oligodendrocytes and prolongs lifespan in female poly-GA C9orf72 mice.

Nature communications

Authors: Ali Rezaei, Virág Kocsis-Jutka, Zeynep I Gunes, Qing Zeng, Georg Kislinger, Franz Bauernschmitt, Huseyin Berkcan Isilgan, Laura R Parisi, Tuğberk Kaya, Sören Franzenburg, Jonas Koppenbrink, Julia Knogler, Thomas Arzberger, Daniel Farny, Brigitte Nuscher, Eszter Katona, Ashutosh Dhingra, Chao Yang, Garyfallia Gouna, Katherine D LaClair, Aleksandar Janjic, Wolfgang Enard, Qihui Zhou, Nellwyn Hagan, Dimitry Ofengeim, Eduardo Beltrán, Ozgun Gokce, Mikael Simons, Sabine Liebscher, Dieter Edbauer

Clinical and genetic research links altered cholesterol metabolism with ALS development and progression, yet pinpointing specific pathomechanisms remain challenging. We investigated how cholesterol dysmetabolism interacts with protein aggregation, demyelination, and neuronal loss in ALS. Bulk RNAseq transcriptomics showed decreased cholesterol biosynthesis and increased cholesterol export in ALS mouse models (GA-Nes, GA-Camk2a GA-CFP, rNLS8) and patient samples (spinal cord), suggesting an adaptive response to cholesterol overload. Consequently, we assessed the efficacy of the cholesterol-binding drug 2-hydroxypropyl-β-cyclodextrin (CD) in a fast-progressing C9orf72 ALS mouse model with extensive poly-GA expression and myelination deficits. CD treatment normalized cholesteryl ester levels, lowered neurofilament light chain levels, and prolonged lifespan in female but not male GA-Nes mice, without impacting poly-GA aggregates. Single nucleus transcriptomics indicated that CD primarily affected oligodendrocytes, significantly restored myelin gene expression, increased density of myelinated axons, inhibited the disease-associated oligodendrocyte response, and downregulated the lipid-associated genes Plin4 and ApoD. These results suggest that reducing excess free cholesterol in the CNS could be a viable ALS treatment strategy.

© 2025. The Author(s).

PMID: 40216746

Participating cluster members