Identification, Prioritisation and Validation of Genetic Associations with Alzheimer's Disease

Chair: Professor Elizabeth Tunbridge

Abstract: Genome-wide association studies (GWAS) have discovered numerous genomic loci associated with Alzheimer’s disease (AD), yet the causal genes and variants remain incompletely identified. We performed an updated genome-wide AD meta-analysis, that identifies novel associations near genes CCDC6, TSPAN14, NCK2, and SPRED2. We then used three SNP-level fine-mapping methods, colocalisation analyses across 109 gene expression quantitative trait loci (eQTL) datasets, and prioritization of genes using protein interaction networks and tissue-specific expression. Combining this information into a quantitative score, we find that evidence converges on likely causal genes. We then narrow down causative alleles for functional follow up, using a novel arrayed CRISPR screening method, Genome engineering-based Interrogation of Enhancers (GenIE). This assesses the effects of defined alleles on transcription or splicing when introduced in their endogenous genomic location. We use this sensitive assay to validate the activity of transcriptional enhancers and splice regulatory elements in human induced pluripotent stem cells (hiPSCs), and develop a software package (R-GenIE) to analyse the data. We screen the 99% credible set of Alzheimer’s disease (AD) GWAS variants identified at the clusterin (CLU) locus to identify a subset of likely causal variants.

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