Back

Single nuclei RNAseq analysis of HD mouse models and human brain reveals impaired oligodendrocyte maturation and potential role for thiamine metabolism

Lim, R. G.; Al-Dalahmah, O.; Wu, J. M.; Gold, M. P.; Reidling, J. C.; Tang, G.; Adam, M.; Dansu, D. K.; Park, H.-J.; Casaccia, P.; Miramontes, R.; Reyes-Ortiz, A. M.; Lau, A.; Khan, F.; Paryani, F.; Tang, A.; Ofori, K. N. A.; Miyoshi, E.; Michael, N.; Geller, N.; Flowers, X. E.; Vonsattel, J. P.; Davidson, S.; Menon, V.; Swarup, V.; Fraenkel, E.; Goldman, J. E.; Thompson, L. M.

2022-06-30 neuroscience
10.1101/2022.06.27.497613 bioRxiv
Show abstract

The complexity of affected brain regions and cell types is a challenge for Huntingtons disease (HD) treatment. Here we used single nucleus RNA sequencing (snRNAseq) to investigate mechanism of pathology in the cortex and striatum from R6/2 mice at 8 and 12w and in three regions of human HD post-mortem tissue. We identified cell type-specific and cell agnostic signatures and found changes suggesting oligodendrocytes (OLs) and oligodendrocyte precursors (OPCs) were arrested in intermediate maturation states. OL-lineage regulators OLIG1 and OLIG2 were negatively correlated with CAG length in human OPCs, and ATACseq analysis of HD mouse NeuN-negative cells showed decreased accessibility of sites regulated by OL maturation genes. Glucose and lipid metabolism were implicated in abnormal cell maturation and PRKCE and Thiamine Pyrophosphokinase 1 were identified as central genes. High dose thiamine/biotin treatment of R6/1 HD mice to target thiamine metabolism not only restored OL maturation, but also rescued pathology in neurons. These findings reveal insights into HD OL pathology that spans multiple brain regions and link OL maturation deficits to abnormal thiamine metabolism.

Matching journals

The top 7 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.