Single-cell RNA sequencing data reveals rewiring of transcriptional relationships in Alzheimer's Disease associated with risk variants.
Gerard A BoulandKevin I MarinusRonald E van KesterenAugust B SmitAhmed MahfouzMarcel J T ReindersPublished in: medRxiv : the preprint server for health sciences (2023)
Understanding how genetic risk variants contribute to Alzheimer's Disease etiology remains a challenge. Single-cell RNA sequencing (scRNAseq) allows for the investigation of cell type specific effects of genomic risk loci on gene expression. Using seven scRNAseq datasets totalling >1.3 million cells, we investigated differential correlation of genes between healthy individuals and individuals diagnosed with Alzheimer's Disease. Using the number of differential correlations of a gene to estimate its involvement and potential impact, we present a prioritization scheme for identifying probable causal genes near genomic risk loci. Besides prioritizing genes, our approach pin-points specific cell types and provides insight into the rewiring of gene-gene relationships associated with Alzheimer's.
Keyphrases
- single cell
- genome wide
- copy number
- gene expression
- rna seq
- dna methylation
- genome wide identification
- cognitive decline
- induced apoptosis
- high throughput
- oxidative stress
- mesenchymal stem cells
- electronic health record
- endoplasmic reticulum stress
- cell proliferation
- cell cycle arrest
- atomic force microscopy
- climate change