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Single-cell RNA sequencing data reveals rewiring of transcriptional relationships in Alzheimer's Disease associated with risk variants

Bouland, G. A.; Marinus, K. I.; van Kesteren, R. E.; Smit, A. B.; Mahfouz, A.; Reinders, M. J. T.

2023-05-16 genetic and genomic medicine
10.1101/2023.05.15.23289992 medRxiv
Show abstract

Understanding how genetic risk variants contribute to Alzheimers 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 Alzheimers 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 Alzheimers.

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