Single-nucleus RNA-sequencing of autosomal dominant Alzheimer disease and risk variant carriers.
Logan BraseShih-Feng YouRicardo D'Oliveira AlbanusJorge L Del-AguilaYaoyi DaiBrenna C NovotnyCarolina Soriano-TarragaTaitea DykstraMaria Victoria FernandezJohn P BuddeKristy BergmannJohn C MorrisRandell J BatemanRichard J PerrinEric McDadeChengjie XiongAlison Mary GoateMartin Farlownull nullGreg Trevor SutherlandJonathan KipnisCeleste M KarchBruno A BenitezOscar HarariPublished in: Nature communications (2023)
Genetic studies of Alzheimer disease (AD) have prioritized variants in genes related to the amyloid cascade, lipid metabolism, and neuroimmune modulation. However, the cell-specific effect of variants in these genes is not fully understood. Here, we perform single-nucleus RNA-sequencing (snRNA-seq) on nearly 300,000 nuclei from the parietal cortex of AD autosomal dominant (APP and PSEN1) and risk-modifying variant (APOE, TREM2 and MS4A) carriers. Within individual cell types, we capture genes commonly dysregulated across variant groups. However, specific transcriptional states are more prevalent within variant carriers. TREM2 oligodendrocytes show a dysregulated autophagy-lysosomal pathway, MS4A microglia have dysregulated complement cascade genes, and APOEε4 inhibitory neurons display signs of ferroptosis. All cell types have enriched states in autosomal dominant carriers. We leverage differential expression and single-nucleus ATAC-seq to map GWAS signals to effector cell types including the NCK2 signal to neurons in addition to the initially proposed microglia. Overall, our results provide insights into the transcriptional diversity resulting from AD genetic architecture and cellular heterogeneity. The data can be explored on the online browser ( http://web.hararilab.org/SNARE/ ).
Keyphrases
- single cell
- genome wide
- rna seq
- cell therapy
- copy number
- genome wide identification
- multiple sclerosis
- dna methylation
- mass spectrometry
- gene expression
- stem cells
- cell death
- mild cognitive impairment
- early onset
- mesenchymal stem cells
- immune response
- type diabetes
- adipose tissue
- metabolic syndrome
- spinal cord injury
- social media
- big data