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Guetta-Baranes, T.

Publications and source records attributed to Guetta-Baranes, T..

2 recordsLinked to original sources

Genetic variability in response to Aβ deposition influences Alzheimer’s risk

Genetic analysis of late-onset Alzheimers disease risk has previously identified a network of largely microglial genes that form a transcriptional network. In transgenic mouse models of amyloid deposition we have previously shown that the expression of many of the mouse orthologs of these genes are co-ordinately up-regulated by amyloid deposition. Here we investigate whether systematic analysis of other members of this mouse amyloid-responsive network predicts other Alzheimers risk loci. This statistical comparison of the mouse amyloid-response network with Alzheimers disease genome-wide association studies identifies 5 other genetic risk loci for the disease (OAS1, CXCL10, LAPTM5, ITGAM and LILRB4). This work suggests that genetic variability in the microglial response to amyloid deposition is a major determinant for Alzheimers risk.\n\nOne Sentence SummaryIdentification of 5 new risk loci for Alzheimers by statistical comparison of mouse A{beta} microglial response with gene-based SNPs from human GWAS

neuroscience

Complement receptor 1 gene (CR1) intragenic duplication and risk of Alzheimer’s disease

Single nucleotide variants (SNVs) within and surrounding the complement receptor 1 (CR1) gene show some of the strongest genome-wide association signals with late-onset Alzheimers disease. Some studies have suggested that this association signal is due to a duplication allele (CR1-B) of a low copy repeat (LCR) within the CR1 gene, which increases the number of complement C3b/C4b-binding sites in the mature receptor. In this study, we develop a triplex paralogue ratio test (PRT) assay for CR1 LCR copy number allowing large numbers of samples to be typed with a limited amount of DNA. We also develop a CR1-B allele-specific PCR based on the junction generated by an historical non-allelic homologous recombination event between CR1 LCRs. We use these methods to genotype CR1 and measure CR1-B allele frequency in both late-onset and early-onset cases and unaffected controls from the United Kingdom. Our data support an association of late-onset Alzheimers disease with the CR1-B allele, and confirm that this allele occurs most frequently on the risk haplotype defined by SNV alleles. Furthermore, regression models incorporating CR1-B genotype provide a bitter fit to our data compared to incorporating the SNP-defined risk haplotype, supporting the CR1-B allele as the variant underlying the increased risk of late-onset Alzheimers disease.

genetics