Targeted ASO-mediated Atp1a2 knockdown in astrocytes reduces SOD1 aggregation and accelerates disease onset in mutant SOD1 mice

Astrocyte-specific ion pump a2-Na+/K+-ATPase plays a critical role in the pathogenesis of amyotrophic lateral sclerosis (ALS). Here, we test the effect of Atp1a2 mRNA-specific antisense oligonucleotides (ASOs) to induce a2-Na+/K+-ATPase knockdown in the widely used ALS animal model, SOD1*G93A mice. Two ASOs led to efficient Atp1a2 knockdown and significantly reduced SOD1 aggregation in vivo. Although Atp1a2 ASO-treated mice displayed no off-target or systemic toxicity, the ASO-treated mice exhibited an accelerated disease onset and shorter lifespan than control mice. Transcriptomics studies reveal downregulation of genes involved in oxidative response, metabolic pathways, trans-synaptic signaling, and upregulation of genes involved in glutamate receptor signaling and complement activation, suggesting a potential role for these molecular pathways in de-coupling SOD1 aggregation from survival in Atp1a2 ASO-treated mice. Together, these results reveal a role for a2-Na+/K+-ATPase in SOD1 aggregation and highlight the critical effect of temporal modulation of genetically validated therapeutic targets in neurodegenerative diseases. Overall design: RNA-sequencing was performed on total RNA extracted from SOD1*G93A primary mouse astrocytes nucleofected with either control ASO or Atp1a2 ASO and harvested 96 hours later. Samples were prepared according to library kit manufacturer's protocol, indexed, pooled, and sequenced on an Illumina NovoSeq. Basecalls and demultiplexing were performed with Illumina's bcl2fastq software and a custom python demultiplexing program with a maximum of one mismatch in the indexing read. RNA-seq reads were then aligned to the Ensembl release 76 primary assembly with STAR version 2.5.1a. Gene counts were derived from the number of uniquely aligned unambiguous reads by Subread:featureCount version 1.4.6-p5.Sequencing performance was assessed for the total number of aligned reads, total number of uniquely aligned reads, and features detected. The ribosomal fraction, known junction saturation, and read distribution over known gene models were quantified with RSeQC version 2.6.2. All gene counts were then imported into the R/Bioconductor package EdgeR and TMM normalization size factors were calculated to adjust for samples for differences in library size. Ribosomal genes and genes not expressed in the smallest group size minus one samples greater than one count-per-million were excluded from further analysis. The TMM size factors and the matrix of counts were then imported into the R/Bioconductor package Limma. The performance of all genes was assessed with plots of the residual standard deviation of every gene to their average log-count with a robustly fitted trend line of the residuals. Differential expression analysis was then performed to analyze for differences between conditions. KEGG and WikiPathways (species: Mus musculus, year queried: 2019) were used to derive functional annotations of the differentially expressed genes into pathways.